Name: Data Understanding and Data Visualization with Python
Price: 59.99 GBP
Availability: InStock

Packt

Docker

Web Development

Flask

Python

This course will show you how to create simple, intermediate, and advanced REST APIs for authentication, deployment, caching, and much more. You will also cover essential technologies such as Flask and popular extensions such as Flask-Smorest, Flask-JWT-Extended, and Flask-SQLAlchemy; we will dive right into developing complete, solid, production-ready REST APIs.

REST APIs with Flask and Python in 2023

General Admission

<div id="course-pills-1">Duration<p>5 Days</p><p>30 CPD hours</p>This course is intended for<p>Experienced Programmers and Systems Administrators.</p>Overview<p>Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. This course is ?skills-centric?, designed to train attendees in core Python and web development skills beyond an intermediate level, coupling the most current, effective techniques with best practices.  Working within in an engaging, hands-on learning environment, guided by our expert Python practitioner, students will learn to:<br />? Create working Python scripts following best practices<br />? Use python data types appropriately<br />? Read and write files with both text and binary data<br />? Search and replace text with regular expressions<br />? Get familiar with the standard library and its work-saving modules<br />? Use lesser-known but powerful Python data types<br />? Create 'real-world', professional Python applications<br />? Work with dates, times, and calendars <br />? Know when to use collections such as lists, dictionaries, and sets<br />? Understand Pythonic features such as comprehensions and iterators<br />? Write robust code using exception handling</p><p>An introductory and beyond-level practical, hands-on Python training course that leads the student from the basics of writing and running Python scripts to more advanced features.</p></div><div id="course-pills-2"><h4>An Overview of Python</h4><ul><li>What is python?<br />1 -- An overview of Python<br />What is python?<br />Python Timeline <br />Advantages/Disadvantages of Python <br />Getting help with pydoc</li></ul><h4>The Python Environment</h4><ul><li>Starting Python <br />Using the interpreter <br />Running a Python script <br />Python scripts on Unix/Windows<br />Editors and IDEs</li></ul><h4>Getting Started</h4><ul><li>Using variables <br />Built-in functions <br />Strings <br />Numbers<br />Converting among types <br />Writing to the screen <br />Command line parameters</li></ul><h4>Flow Control</h4><ul><li>About flow control <br />White space <br />Conditional expressions <br />Relational and Boolean operators <br />While loops <br />Alternate loop exits</li></ul><h4>Sequences</h4><ul><li>About sequences <br />Lists and list methods <br />Tuples <br />Indexing and slicing <br />Iterating through a sequence <br />Sequence functions, keywords, and operators <br />List comprehensions <br />Generator Expressions<br />Nested sequences </li></ul><h4>Working with files</h4><ul><li>File overview<br />Opening a text file <br />Reading a text file <br />Writing to a text file<br />Reading and writing raw (binary) data<br />Converting binary data with struct</li></ul><h4>Dictionaries and Sets</h4><ul><li>About dictionaries <br />Creating dictionaries <br />Iterating through a dictionary <br />About sets <br />Creating sets <br />Working with sets</li></ul><h4>Functions</h4><ul><li>Defining functions <br />Parameters  <br />Global and local scope<br />Nested functions <br />Returning values</li></ul><h4>Sorting</h4><ul><li>The sorted() function<br />Alternate keys <br />Lambda functions <br />Sorting collections<br />Using operator.itemgetter() <br />Reverse sorting</li></ul><h4>Errors and Exception Handling</h4><ul><li>Syntax errors <br />Exceptions <br />Using try/catch/else/finally<br />Handling multiple exceptions <br />Ignoring exceptions</li></ul><h4>Modules and Packages</h4><ul><li>The import statement <br />Module search path <br />Creating Modules <br />Using packages<br />Function and Module aliases</li></ul><h4>Classes</h4><ul><li>About o-o programming<br />Defining classes<br />Constructors<br />Methods<br />Instance data<br />Properties<br />Class methods and data</li></ul><h4>Regular Expressions</h4><ul><li>RE syntax overview <br />RE Objects <br />Searching and matching <br />Compilation flags <br />Groups and special groups<br />Replacing text<br />Splitting strings</li></ul><h4>The standard library</h4><ul><li>The sys module <br />Launching external programs <br />Math functions <br />Random numbers <br />The string module<br />Reading CSV data</li></ul><h4>Dates and times</h4><ul><li>Working with dates and times<br />Translating timestamps<br />Parsing dates from text<br />Formatting dates<br />Calendar data</li></ul><h4>Working with the file system</h4><ul><li>Paths, directories, and filenames <br />Checking for existence<br />Permissions and other file attributes<br />Walking directory trees <br />Creating filters with fileinput<br />Using shutil for file operations<br />17 ? Advanced data handling<br />Defaultdict and Counter<br />Prettyprinting data structures<br />Compressed archives (zip, gzip, tar, etc.)<br />Persistent data</li></ul><h4>Advanced data handling</h4><ul><li>Defaultdict and Counter<br />Prettyprinting data structures<br />Compressed archives (zip, gzip, tar, etc.)<br />Persistent data</li></ul><h4>Network services</h4><ul><li>Grabbing web content<br />Sending email<br />Using SSH for remote access<br />Using FTP</li></ul><h4>Writing real-life applications</h4><ul><li>Parsing command-line options<br />Detecting the current platform<br />Trapping signals<br />Implementing logging<br />Python Timeline <br />Advantages/Disadvantages of Python <br />Getting help with pydoc</li></ul></div>

Nexus Human

Computing Skills

Programming Fundamentals

Computer Programming

Computer Skills

Python Scripting

Trainers Course

Python 3 Essentials

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			<h2><b>Course Overview</b></h2>		</div>
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					<div><p><span>Learn how to create and code maps using the quickest and easiest techniques when you take this course on creating </span><b>Maps in Folium and Python. </b><span>The Folium library allows you to build high-quality maps in Python in a few short steps, and you will become proficient in its use after completing this course.</span></p><p><span>This comprehensive </span>Python and Folium <span>tutorial delivers the complete learning curve for controlling mapping processes, making it ideal for beginners and professionals alike. With expert tuition, you will be shown how to create a folium map from scratch and significantly enhance your programming knowledge. In passing the final assessment, you will raise your employment profile in the IT sector. </span></p></div>
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					<div><p>This best selling <strong>Maps in Folium and Python </strong>has been developed by industry professionals and has already been completed by hundreds of satisfied students. This in-depth <strong>Maps in Folium and Python </strong>is suitable for anyone who wants to build their professional skill set and improve their expert knowledge.</p>
<p>The <strong>Maps in Folium and Python </strong>is CPD-accredited, so you can be confident you're completing a quality training course will boost your CV and enhance your career potential. The <strong>Maps in Folium and Python </strong>is made up of several information-packed modules which break down each topic into bite-sized chunks to ensure you understand and retain everything you learn.</p>
<p>After successfully completing the<strong> Maps in Folium and Python</strong>, you will be awarded a certificate of completion as proof of your new skills. If you are looking to pursue a new career and want to build your professional skills to excel in your chosen field, the certificate of completion from the <strong>Maps in Folium and Python </strong>will help you stand out from the crowd. You can also validate your certification on our website.</p>
<p>We know that you are busy and that time is precious, so we have designed the <strong>Maps in Folium and Python </strong>to be completed at your own pace, whether that's part-time or full-time. Get full course access upon registration and access the course materials from anywhere in the world, at any time, from any internet-enabled device. </p>
<p>Our experienced tutors are here to support you through the entire learning process and answer any queries you may have via email.</p></div>
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Course Cloud

Maps in Folium and Python

Redhill

<h3><b>Advanced Python training course description</b></h3>
      <p> This course caters to network engineers aiming to
enhance both their Python proficiency and network
automation skills. Delving deeper into key areas such
as netmiko, Nornir, and ncclient, we also focus on
automating network testing and validation. Participants
gain greater confidence working with Python functions,
classes, objects, and error handling. The course
additionally introduces more libraries like Scrapli, TTP,
pyATS, Genie, pybatfish, and Suzieq, which cover
parsing strategies, automation testing, validation,
network analysis, observability, and telemetry. The
curriculum also encompasses concurrency techniques.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
   <li>Write Python modules and functions.</li>
<li>Evaluate techniques to parse unstructured data.</li>
<li>Use NETCONF filters.</li>
<li>Handle Python errors effectively (try, assertâ¦).</li>
<li>Use postman.</li>
<li>Automate testing and validation of the network.</li>
<li>Use scrapli, Genie, batfish and Suzieq. </li>
                  </ul>
        <h5>
        <b>Advanced Python training course details</b> </h5>
				<div>
					<div>
						<ul>
							<li><b> Who will benefit:</b> </li>
							
              <p>Network engineers.</p>
              
							<li><b>Prerequisites:</b></li>
							
              <p>Python for network engineers</p>
              
							<li><b>Duration</b></li>
							
              <p>5 days
						</p>
              
							
              
              
						</ul>
					</div>
				</div>
      <h3><b>Advanced Python training course contents</b></h3>
      <ul>
		<li>Review</li><p>
CLI, NETCONF, RESTCONF, structured versus
unstructured data, gNMI and when to use which.
PEP 8. Naming conventions. Packages, modules,
Classes and methods. The scrapli library. Netmiko
versus scrapli. <br /><span>Hands on:</span> scrapli, Dictionaries
versus Regular Expressions.

		  </p><li>Modules and Functions</li><p>
Writing your own modules, containers versus
packages, virtual environments. Best practices,
calling functions, writing your own functions.
Parameters, arguments. Named arguments,
dictionaries as arguments. Builtins. Docstrings.
Main. __name__, __main__ . Program arguments.
<br /><span>Hands on:</span> Getting interfaces, showing interface
status using Netmiko and functions. Using
dictionaries as arguments. Writing your own
modules.

		  </p><li>Parsing strategies</li><p>
Turning unstructured data into structured data.
textfsm, PyATS Genie parser, NAPALM getters,
Template Text Parser. <br /><span>Hands on:</span> Genie parser,
TTP. Accessing structured data with lists and
dictionaries.

				</p><li>Classes, objects and Python</li><p>
Python classes in Genie, PyEZ and others .
<br /><span>Hands on:</span> studying network automation classes,
objects, methods and attributes.

			</p><li>Configuration management - more nornir, ncclient,
requests</li><p>
Nornir tasks. Nornir results, Nornir functions,
Nornir plugins. Nornir processors. YANG, YANG
models, pyang. NETCONF hello. Capabilities.
Schemas. Filters. Subtrees. XPATH. Exploring
available YANG data models. NETCONF and
network wide transactions. Asserting NETCONF
capabilities. Configuration types. Locking
configurations, commits. NETCONF data stores.
Netconf-console. RESTCONF differences from
NETCONF. URI construction. Postman. More XML
and JSON. Git and configuration versions. <br /><span>Hands
on:</span> Nornir and Jinja2. Exploring available models,
NETCONF filters. Using postman.

		</p><li>Python error handling and debugging</li><p>
Context handlers, try, assert, logging, pdb, pytest,
unit testing, chatgpt. <br /><span>Hands on:</span> Writing code with
each of the error handling methods, investigating
what happens on an error. Use chatgpt to debug
your code.

	</p><li>Python Automation Testing</li><p>
Testing and validation. pyATS, Genie. Testbed
file. Genie parse, genie learn, genie diff. Genie
conf, Genie ops, Genie SDK, Genie harness.
Xpresso. <br /><span>Hands on:</span> Using Genie for state
comparisons of the network.

	</p><li>Network analysis</li><p>
Batfish, pybatfish, configuration analysis,
analysing routing, analysing ACLs. Pandas.
Pandas dataframe. Filtering and selecting values
of interest. <br /><span>Hands on:</span> Use Batfish to analyse
network snapshots, find network adjacencies, flow
path analysis.

	</p><li>Network observability</li><p>
Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server.
Namespaces and seeing devices, network state
and Asserts. Time based analysis, snapshots and
changes. <br /><span>Hands on:</span> Suzieq: Gathering data from
the network, analysing data from the network.
Network state assertion.

	</p><li>Telemetry</li><p>
gRPC, gNMI. CAP, GET, SET. Subscriptions.
Model Driven telemetry.<br /><span> Hands on:</span> Analysing
telemetry data with Python.

		</p><li>Concurrency</li><p>
asyncio, threads, processes. Nornir concurrency.
Scrapli and netmiko concurrency. <br /><span>Hands on:</span>
Multiple SSH connections to devices at same
time. Scarpli asyncio.
		

</p>
      </ul>

Systems & Network Training

Network & Security

Network Engineer

Advanced Python for network engineers

<strong>Learn how to implement EC2 and VPC resources on AWS using the Python API: Boto3! Implement your infrastructure with code!</strong>
        <p>In this course, we'll start by taking a look at the tools and the environment that we need to work with AWS resources. We will teach you how you can set up your environment on both MacOS and Windows. Once we're ready with our environment setup, we'll start implementing our solution on AWS.Then we will create two subnets; Public and Private.We will develop a startup bash script to automatically run when we launch our EC2 Instance. In this script, we will first update our packages with yum package manager so we can stay up-to-date with the latest updates and security patches. Then we will install a HTTP server on it and make sure it's working by a startup check command. After we prepare our HTTP server, we will develop a simple HTML page as a greeting and we will write this page to disk to be served when we try to access our Public EC2 Instance. And remember, we will again do all of this with our Python code!
After finishing up launching our EC2 Instances, we'll move on to learn how to describe EC2 Instances on AWS in detailed way; from their IP addresses to the subnet which they belong to. Then we'll learn how to learn how to manage EC2 Instances in various ways. We'll Stop, Start and Terminate EC2 Instances and again the best part is we will do all of that with our Python code!

All the code and caption files for this course are available at: https://github.com/PacktPublishing/Managing-EC2-and-VPC-AWS-with-Python-and-Boto3-Series</p>
        <h2>What You Will Learn</h2><p>You ll be able to implement any sort of infrastructure on AWS with Python using VPCs, Subnets and EC2s!<br>You ll learn how to code against AWS API using Python and Boto3!<br>You ll learn how to launch EC2 Instances on AWS using Python and Boto3!<br>You ll learn how to isolate and control your own infrastructure with Python using Route Tables, Internet Gateways, Security Groups and Rules!<br>You ll have very good understanding of VPC concepts like Subnets, Route Tables and Internet Gateways by putting all into real-world practice with Python code!<br>You ll be confident to work with AWS APIs using Python for any kind of AWS Resource on VPC and EC2 Instances!<br>You ll learn how to read and code against an API documentation!<br>You ll be able to launch your own infrastructure on AWS without even signing-in to AWS!<br></p>
        <h2>Audience</h2><p>This course is for Beginners on AWS who wants to put their theory in practice, AWS Cloud Architect Associate Exam Preppers who wants to practice their theories with real projects, Who wants to learn how to implement Infrastructure-as-a-Code or IaaS on AWS, Who wants to learn how to develop infrastructures on AWS using Python, Who wants to learn how to launch Virtual Private Clouds, Public-Private Subnets and more with Python code on AWS, Who wants to learn how to launch EC2 Instances publicly and privately using Python on AWS, Who wants to learn AWS Python API or namely Boto3.</p>
        <h2>Approach</h2><p>This course start by taking a look at the tools and the environment that you need to work with AWS resources. Lots of information, hands-on practice and experience is waiting for you in this course on AWS. </p>
        <h2>Key Features</h2><p>Learn to implement EC2 and VPC resources on AWS using Python API, Boto3, and launch your own infrastructure on AWS. * Learn how to read and code against API documentation. * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/managing-ec2-and-vpc-aws-with-python-and-boto3-series</p>
        <h2>About the Author</h2><h3>Niyazi Erdogan</h3><p>Niyazi Erdogan is an AWS Certified Solutions architect and software engineer with over ten years of experience in various fields. He is living in one of the most beautiful cities in the world-Istanbul. He is a self-taught programmer and has been programming since he was in middle school. His experience ranges from embedded development to server-side and client-side development technologies. He started his career while he was only a student as a Java developer in the healthcare industry as a private contractor. Then he moved into the largest telecommunication company in Turkey, which is Turkcell.

After several years and various different positions at Turkcell, he moved to Portugal and worked for another large telecommunication company for several years with Java technologies. After the telecommunication industry experience and several different experiences, he joined one of the largest companies in its sectors, which is Siemens. He currently works at Siemens with various Java and cloud technologies. Besides his day job, he really enjoys developing software with lots of different technologies. On the other hand, he loves to follow tech conferences and blogs about the latest technologies and tools.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Introduction: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. About This Course</p><p style='margin: 0'>Introduction: About This Course</p></td></tr><tr><td style='padding: 15px;'><p>3. What We Will Build In This Course?</p><p style='margin: 0'>Introduction: What We Will Build In This Course?</p></td></tr><tr><td style='padding: 15px;'><p>4. What Do You Need For This Course?</p><p style='margin: 0'>Introduction: What Do You Need For This Course?</p></td></tr></tbody></table><br><h4>2. Preparing The Environment for Development</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Preparing The Environment for Development: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. About Tools and Environment</p><p style='margin: 0'>Preparing The Environment for Development: About Tools and Environment</p></td></tr><tr><td style='padding: 15px;'><p>3. Create an AWS Account If You Don't Already Have It!</p><p style='margin: 0'>Preparing The Environment for Development: Create an AWS Account If You Don't Already Have It!</p></td></tr><tr><td style='padding: 15px;'><p>4. Logging in to AWS Console and A Walkthrough</p><p style='margin: 0'>Preparing The Environment for Development: Logging in to AWS Console and A Walkthrough</p></td></tr><tr><td style='padding: 15px;'><p>5. Let's Create Our AWS Credentials!</p><p style='margin: 0'>Preparing The Environment for Development: Let's Create Our AWS Credentials!</p></td></tr></tbody></table><br><h4>3. Windows Environment Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Installing Python 3 and Pip</p><p style='margin: 0'>Windows Environment Setup: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing AWS SDK (CLI)</p><p style='margin: 0'>Windows Environment Setup: Installing AWS SDK (CLI)</p></td></tr><tr><td style='padding: 15px;'><p>3. Preparing CLI with AWS Credentials</p><p style='margin: 0'>Windows Environment Setup: Preparing CLI with AWS Credentials</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Boto3</p><p style='margin: 0'>Windows Environment Setup: Installing Boto3</p></td></tr><tr><td style='padding: 15px;'><p>5. Verifying The Setup</p><p style='margin: 0'>Windows Environment Setup: Verifying The Setup</p></td></tr></tbody></table><br><h4>4. MacOS Environment Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Installing Python 3 and Pip</p><p style='margin: 0'>MacOS Environment Setup: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing AWS SDK (CLI)</p><p style='margin: 0'>MacOS Environment Setup: Installing AWS SDK (CLI)</p></td></tr><tr><td style='padding: 15px;'><p>3. Preparing CLI with AWS Credentials</p><p style='margin: 0'>MacOS Environment Setup: Preparing CLI with AWS Credentials</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Boto3</p><p style='margin: 0'>MacOS Environment Setup: Installing Boto3</p></td></tr><tr><td style='padding: 15px;'><p>5. Verifying The Setup</p><p style='margin: 0'>MacOS Environment Setup: Verifying The Setup</p></td></tr></tbody></table><br><h4>5. Virtual Private Cloud (VPC) with Boto3 - Part 1</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Scenario: AWS Console Perspective of What We'll Build</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Scenario: AWS Console Perspective of What We'll Build</p></td></tr><tr><td style='padding: 15px;'><p>3. Setting Up Our Project with PyCharm IDE</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Setting Up Our Project with PyCharm IDE</p></td></tr><tr><td style='padding: 15px;'><p>4. Let's Check Out Boto3 API Docs!</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Let's Check Out Boto3 API Docs!</p></td></tr><tr><td style='padding: 15px;'><p>5. [Tip] Auto-Complete Magic with Pyboto3 on PyCharm IDE!</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: [Tip] Auto-Complete Magic with Pyboto3 on PyCharm IDE!</p></td></tr><tr><td style='padding: 15px;'><p>6. Creating a Virtual Private Cloud (VPC)</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Creating a Virtual Private Cloud (VPC)</p></td></tr><tr><td style='padding: 15px;'><p>7. Adding Name Tag To An AWS Resource (VPC)</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Adding Name Tag To An AWS Resource (VPC)</p></td></tr><tr><td style='padding: 15px;'><p>8. Create an Internet Gateway (IGW)</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Create an Internet Gateway (IGW)</p></td></tr><tr><td style='padding: 15px;'><p>9. Attaching the Internet Gateway to VPC</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Attaching the Internet Gateway to VPC</p></td></tr><tr><td style='padding: 15px;'><p>10. Section Summary</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 1: Section Summary</p></td></tr></tbody></table><br><h4>6. Virtual Private Cloud (VPC) with Boto3 - Part 2</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating a Public Subnet</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Creating a Public Subnet</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating a Route Table for Public Routes</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Creating a Route Table for Public Routes</p></td></tr><tr><td style='padding: 15px;'><p>4. Adding IGW Route to Route Table</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Adding IGW Route to Route Table</p></td></tr><tr><td style='padding: 15px;'><p>5. Associating Public Subnet with Public Route Table</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Associating Public Subnet with Public Route Table</p></td></tr><tr><td style='padding: 15px;'><p>6. Allowing Auto-Assign Public IP Address on Subnet</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Allowing Auto-Assign Public IP Address on Subnet</p></td></tr><tr><td style='padding: 15px;'><p>7. Creating a Private Subnet</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Creating a Private Subnet</p></td></tr><tr><td style='padding: 15px;'><p>8. Section Summary</p><p style='margin: 0'>Virtual Private Cloud (VPC) with Boto3 - Part 2: Section Summary</p></td></tr></tbody></table><br><h4>7. Elastic Compute Cloud (EC2) with Boto3 - Part 1</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Scenario: AWS Console Perspective of What We'll Build</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Scenario: AWS Console Perspective of What We'll Build</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating a Key Pair</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Creating a Key Pair</p></td></tr><tr><td style='padding: 15px;'><p>4. Creating a Security Group</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Creating a Security Group</p></td></tr><tr><td style='padding: 15px;'><p>5. Adding a Rule to Security Group</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Adding a Rule to Security Group</p></td></tr><tr><td style='padding: 15px;'><p>6. Creating a Startup Script for EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Creating a Startup Script for EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>7. Launching an EC2 Instance Within Our Public Subnet</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Launching an EC2 Instance Within Our Public Subnet</p></td></tr><tr><td style='padding: 15px;'><p>8. Launching an EC2 Instance Within Our Private Subnet</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Launching an EC2 Instance Within Our Private Subnet</p></td></tr><tr><td style='padding: 15px;'><p>9. It's Time to Launch the Whole Infrastructure!</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1:!!! It's Time to Launch the Whole Infrastructure!</p></td></tr><tr><td style='padding: 15px;'><p>10. Let's Check if Everything is Running on AWS Console!</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Let's Check if Everything is Running on AWS Console!</p></td></tr><tr><td style='padding: 15px;'><p>11. Connecting to EC2 Instance and Verifying Startup Script Works</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Connecting to EC2 Instance and Verifying Startup Script Works</p></td></tr><tr><td style='padding: 15px;'><p>12. Checking Public Access for Private EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Checking Public Access for Private EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>13. Section Summary</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 1: Section Summary</p></td></tr></tbody></table><br><h4>8. Elastic Compute Cloud (EC2) with Boto3 - Part 2</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Describing EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Describing EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>3. Modifying EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Modifying EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>4. Stopping EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Stopping EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>5. Starting EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Starting EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>6. Terminating EC2 Instance</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Terminating EC2 Instance</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Elastic Compute Cloud (EC2) with Boto3 - Part 2: Section Summary</p></td></tr></tbody></table><br><h4>9. Wrapping Up</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. What Have We Learned?</p><p style='margin: 0'>Wrapping Up: What Have We Learned?</p></td></tr><tr><td style='padding: 15px;'><p>2. Thank You!</p><p style='margin: 0'>Wrapping Up: Thank You!</p></td></tr></tbody></table>

Security

Learn how to implement EC2 and VPC resources on AWS using the Python API: Boto3! Implement your infrastructure with code!

Managing EC2 and VPC: AWS with Python and Boto3 Series

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					<div><p><span>Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step training course. This Python: Higher Order Functions</span><span> has been specially designed to help learners gain a good command of Python: Higher Order Functions</span><span>, providing them with a solid foundation of knowledge to become a qualified professional.</span></p><p><span>Through this Python: Higher Order Functions</span><span>, you will gain both practical and theoretical understanding of Python: Higher Order Functions</span><span> that will increase your employability in this field, help you stand out from the competition and boost your earning potential in no time.</span></p><p><span>Not only that, but this training includes up-to-date knowledge and techniques that will ensure you have the most in-demand skills to rise to the top of the industry. This qualification is fully accredited, broken down into several manageable modules, ideal for aspiring professionals. </span></p></div>
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				<h2>Learning outcome</h2>
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										<span>Get a deep understanding of the Python: Higher Order Functions just in hours not years</span>
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										<span>Familiar yourself with the recent development and updates of the relevant industry</span>
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										<span>Know how to use your theoretical and practical knowledge to adapt in any working environment</span>
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										<span>Get help from our expert tutors anytime you need</span>
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										<span> Access to course contents that are designed and prepared by industry professionals</span>
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										<span>Study at your convenient time and from wherever you want </span>
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										<span>No formal qualifications required, anyone from any academic background can take this course.</span>
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										<span>Access to any internet-enabled smart device.</span>
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										<span>1 hours of on-demand video lectures and downloadable resources.</span>
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										<span>Affordable premium-quality E-learning content, you can learn at your own pace.</span>
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										<span>You will receive a completion certificate upon completing the course.</span>
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										<span>Internationally recognized Accredited Qualification will boost up your resume.</span>
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										<span>You will learn the researched and proven approach adopted by successful salespeople to transform their careers.</span>
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										<span>You will be able to incorporate various practical sales techniques successfully and understand your customers better.</span>
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                                <h2>Course Curriculum</h2>
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					<td colspan="4"><strong> Module 01: Course Introduction</strong></td>
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					<td>Introduction</td><td><span>🕐 00:01:00</span></td>
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					<td colspan="4"><strong>Module 03: Sorting with Keys</strong></td>
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					<td>Sorting with Keys</td><td><span>🕐 00:09:00</span></td>
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					<td colspan="4"><strong>Module 04: Map Function</strong></td>
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					<td colspan="4"><strong>Module 06: List Comprehension Alternative</strong></td>
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					<td>List Comprehension Alternative</td><td><span>🕐 00:04:00</span></td>
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					<td colspan="4"><strong>Module 07: Recursion Introduction</strong></td>
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					<td>Introduction to Recursion</td><td><span>🕐 00:07:00</span></td>
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Skill Up

Gain the skills and credentials to kickstart a successful career and learn from the experts with this step-by-step

Python: Higher Order Functions

<strong>Learn how you can develop and deploy Java, Python, NodeJS Lambda Functions and manage them using Python and Boto3!</strong>
        <p>AWS Lambda is one of the fastest growing services of AWS! This course is part of a series of courses on AWS solutions with Python and Boto3 and now it's time to implement serverless functions! AWS Lambda is a cornerstone service for serverless architectures on AWS. You do not manage an infrastructure like CPU, memory, OS or patches you name it! All you have to do and worry about is your implementation and code! Let's take a closer look at what we're going to cover in this course step-by-step. In this course, we will start off with what we'll build throughout the course and what you need to have on your computer to follow along with me. Don't worry; I'll explain everything you need very clearly and I'll show you what you need to install and setup on your computer to work with AWS Lambda. There will be two different sections for Windows and MacOS users. These sections are basically identical and show how you can prepare your computer environment to be ready to work with AWS Lambda! I'll show you how to install Python, Boto3 and configure your environments for these tools. I'll also show you how you can create your own AWS account step-by-step and you'll be ready to work AWS in no time! When we're done with preparing our environment to work AWS with Python and Boto3, we'll start implementing our solutions for AWS.
All the code and supporting files for this course are available at https://github.com/PacktPublishing/Build-and-Deploy-Lambda-Functions-AWS</p>
        <h2>What You Will Learn</h2><p>You ll learn how to develop Python, NodeJS and Java Lambda Functions!<br>You ll learn how to give necessary IAM Roles and Policies for Lambda Functions!<br>You ll learn how to configure Python, NodeJS and Java Lambda Functions!<br>You ll learn how to package and deploy Python, NodeJS and Java Lambda Functions!<br>You ll learn how to invoke Python, NodeJS and Java Lambda Functions!<br>You ll be able to implement any sort of infrastructure with Lambda on AWS with Python!<br>You ll learn how to code against AWS API using Python and Boto3!<br>You ll be confident to work with AWS APIs using Python for any kind of AWS Resource on Lambda!</p>
        <h2>Audience</h2><p>This course is for whoever wants to learn how to implement Python, NodeJS and Java Lambda Functions, how to deploy Python, NodeJS and Java Lambda Functions, how to configure and package Python, NodeJS and Java Lambda Functions. Beginners on AWS who wants to put their theory in practice and AWS Cloud Architect Associate Exam. This can also be useful for who wants to learn how to implement Infrastructure-as-a-Code or IaaS on AWS, how to develop infrastructures on AWS using Python, and learn AWS Python API or namely Boto3.</p>
        <h2>Approach</h2><p>Join the author in this course to learn how you can develop and deploy Python, Node.js or Java Lambda functions using Python and Boto3; manage your serverless functions easily!</p>
        <h2>Key Features</h2><p>Learn how to do things programmatically.  * Great course on AWS Lambda using Python</p>
        
        <h2>About the Author</h2><h3>Niyazi Erdogan</h3><p>Niyazi Erdogan is an AWS Certified Solutions architect and software engineer with over ten years of experience in various fields. He is living in one of the most beautiful cities in the world-Istanbul. He is a self-taught programmer and has been programming since he was in middle school. His experience ranges from embedded development to server-side and client-side development technologies. He started his career while he was only a student as a Java developer in the healthcare industry as a private contractor. Then he moved into the largest telecommunication company in Turkey, which is Turkcell.

After several years and various different positions at Turkcell, he moved to Portugal and worked for another large telecommunication company for several years with Java technologies. After the telecommunication industry experience and several different experiences, he joined one of the largest companies in its sectors, which is Siemens. He currently works at Siemens with various Java and cloud technologies. Besides his day job, he really enjoys developing software with lots of different technologies. On the other hand, he loves to follow tech conferences and blogs about the latest technologies and tools.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>Introduction: Introduction</p></td></tr><tr><td style='padding: 15px;'><p>2. About This Course</p><p style='margin: 0'>Introduction: About This Course</p></td></tr><tr><td style='padding: 15px;'><p>3. What We Will Build in This Course</p><p style='margin: 0'>Introduction: What We Will Build in This Course</p></td></tr><tr><td style='padding: 15px;'><p>4. What Do You Need For This Course?</p><p style='margin: 0'>Introduction: What Do You Need For This Course?</p></td></tr></tbody></table><br><h4>2. Preparing the Environment for Development</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Preparing the Environment for Development: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. About Tools and Environment</p><p style='margin: 0'>Preparing the Environment for Development: About Tools and Environment</p></td></tr><tr><td style='padding: 15px;'><p>3. Create an AWS Account If You Don't Already Have It!</p><p style='margin: 0'>Preparing the Environment for Development: Create an AWS Account If You Don't Already Have It!</p></td></tr><tr><td style='padding: 15px;'><p>4. Logging in to AWS Console and a Walkthrough</p><p style='margin: 0'>Preparing the Environment for Development: Logging in to AWS Console and a Walkthrough</p></td></tr><tr><td style='padding: 15px;'><p>5. Let's Create Our AWS Credentials!</p><p style='margin: 0'>Preparing the Environment for Development: Let's Create Our AWS Credentials!</p></td></tr></tbody></table><br><h4>3. Windows Environment Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Installing Python 3 and Pip</p><p style='margin: 0'>Learning CSS: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing AWS SDK (CLI)</p><p style='margin: 0'>Learning CSS: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>3. Preparing CLI with AWS Credentials</p><p style='margin: 0'>Learning CSS: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Boto3</p><p style='margin: 0'>Learning CSS: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>5. Verifying the Setup</p><p style='margin: 0'>Learning CSS: Verifying the Setup</p></td></tr></tbody></table><br><h4>4. Mac OS Environment Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Installing Python 3 and Pip</p><p style='margin: 0'>Learning CSS: Installing Python 3 and Pip</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing AWS SDK (CLI)</p><p style='margin: 0'>Learning CSS: Installing AWS SDK (CLI)</p></td></tr><tr><td style='padding: 15px;'><p>3. Preparing CLI with AWS Credentials</p><p style='margin: 0'>Learning CSS: Preparing CLI with AWS Credentials</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Boto3</p><p style='margin: 0'>Learning CSS: Installing Boto3</p></td></tr><tr><td style='padding: 15px;'><p>5. Verifying the Setup</p><p style='margin: 0'>Learning CSS: Verifying the Setup</p></td></tr></tbody></table><br><h4>5. AWS Lambda with Boto3: Implementing Functions</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Setting Up Our Project with PyCharm IDE</p><p style='margin: 0'>Learning CSS: Setting Up Our Project with PyCharm IDE</p></td></tr><tr><td style='padding: 15px;'><p>2. Creating an IAM Lambda Access Policy</p><p style='margin: 0'>Learning CSS: Creating an IAM Lambda Access Policy</p></td></tr><tr><td style='padding: 15px;'><p>3. Creating an IAM Execution Role</p><p style='margin: 0'>Learning CSS: Creating an IAM Execution Role</p></td></tr><tr><td style='padding: 15px;'><p>4. Attaching IAM Access Policy to IAM Execution Role</p><p style='margin: 0'>Learning CSS: Attaching IAM Access Policy to IAM Execution Role</p></td></tr><tr><td style='padding: 15px;'><p>5. Implementing Utility Methods for Source Code Bytes Reading - Part 1</p><p style='margin: 0'>Learning CSS: Implementing Utility Methods for Source Code Bytes Reading - Part 1</p></td></tr><tr><td style='padding: 15px;'><p>6. Implementing Utility Methods for Source Code Bytes Reading - Part 2</p><p style='margin: 0'>Learning CSS: Implementing Utility Methods for Source Code Bytes Reading - Part 2</p></td></tr></tbody></table><br><h4>6. AWS Lambda with Boto3: Developing, Deploying and Invoking Functions</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Developing a Python Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Developing a Python Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>2. Deploying Python Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Deploying Python Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>3. AWS Console Checkpoint: Python Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: AWS Console Checkpoint: Python Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>4. Developing a NodeJS Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Developing a NodeJS Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>5. Deploying NodeJS Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Deploying NodeJS Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>6. AWS Console Checkpoint: NodeJS Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: AWS Console Checkpoint: NodeJS Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>7. Installing Eclipse AWS Plugin</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Installing Eclipse AWS Plugin</p></td></tr><tr><td style='padding: 15px;'><p>8. Creating a Java Lambda Function with Eclipse AWS Plugin</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Creating a Java Lambda Function with Eclipse AWS Plugin</p></td></tr><tr><td style='padding: 15px;'><p>9. Deploying Java Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: Deploying Java Lambda Function</p></td></tr><tr><td style='padding: 15px;'><p>10. AWS Console Checkpoint: Java Lambda Function</p><p style='margin: 0'>AWS Lambda with Boto3: Developing, Deploying and Invoking Functions: AWS Console Checkpoint: Java Lambda Function</p></td></tr></tbody></table><br><h4>7. AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Invoking Functions</p><p style='margin: 0'>AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing: Invoking Functions</p></td></tr><tr><td style='padding: 15px;'><p>2. Passing Environment Variables to a Function</p><p style='margin: 0'>AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing: Passing Environment Variables to a Function</p></td></tr><tr><td style='padding: 15px;'><p>3. Modifying Function Code to Use Environment Variable and Invoking</p><p style='margin: 0'>AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing: Modifying Function Code to Use Environment Variable and Invoking</p></td></tr><tr><td style='padding: 15px;'><p>4. Publishing a New Function Version</p><p style='margin: 0'>AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing: Publishing a New Function Version</p></td></tr><tr><td style='padding: 15px;'><p>5. Creating Aliases for Function Versions</p><p style='margin: 0'>AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing: Creating Aliases for Function Versions</p></td></tr><tr><td style='padding: 15px;'><p>6. Invoking Functions with Aliases</p><p style='margin: 0'>AWS Lambda with Boto3: Updating Function Code, Versioning, Aliasing: Invoking Functions with Aliases</p></td></tr></tbody></table><br><h4>8. AWS Lambda with Boto3: Function Operations</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Getting a Function Configuration</p><p style='margin: 0'>AWS Lambda with Boto3: Function Operations: Getting a Function Configuration</p></td></tr><tr><td style='padding: 15px;'><p>2. Listing All Function Configurations</p><p style='margin: 0'>AWS Lambda with Boto3: Function Operations: Listing All Function Configurations</p></td></tr><tr><td style='padding: 15px;'><p>3. Updating Function Configurations</p><p style='margin: 0'>AWS Lambda with Boto3: Function Operations: Updating Function Configurations</p></td></tr><tr><td style='padding: 15px;'><p>4. Deleting Functions</p><p style='margin: 0'>AWS Lambda with Boto3: Function Operations: Deleting Functions</p></td></tr></tbody></table><br><h4>9. Wrapping Up</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Thank You!</p><p style='margin: 0'>Wrapping Up: Thank You!</p></td></tr></tbody></table>

Learn how you can develop and deploy Java, Python, NodeJS Lambda Functions and manage them using Python and Boto3!

Build and Deploy Lambda Functions: AWS with Python and Boto3

<h2 style="color: var(--text-heading); box-sizing: border-box;" id="isPasted" fr-original-style="color: var(--text-heading);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">This course at a glance</span></strong></h2><ul style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);"><li style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style="color: rgb(0, 0, 0);">Accredited by CPDQE</li><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Learn how to clean, process, wrangle, and manipulate data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Know how to create a resume for a data science job</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Get a grasp of NumPy by learning how to use it for numerical data</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Uncover the secret of different Python libraries, such as Pandas, Matplotlib, SciPy and many more</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Explore machine learning concepts and algorithms</span></li><li fr-original-style="" style="box-sizing: border-box;"><span style="color: rgb(38, 99, 82) !important; box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">Discover developing custom data solutions</span></li></ul><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" id="isPasted" fr-original-style=" color: rgb(38, 99, 82) !important;">You can create various applications for science, math, machine learning, and data science with Python. As a high-level, general-purpose programming language, Python is quite English-like and easy to learn. This&nbsp;<b fr-original-style="" style="box-sizing: border-box;">Python for Data Science and Machine Learning</b>&nbsp;course will show you how to use Python for machine learning and data science.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">During the course, you will master every useful Python skill you need for data science and machine learning. If you find it challenging to write complex Python programs, we&rsquo;ll show you how to do so with our step-by-step instructions based on actual work contexts. You&rsquo;ll also learn how to run the regression, classification, and clustering and the specifics of supervised and unsupervised machine learning. Moreover, this course covers how statistics work for data science, hypothesis testing, and much more.</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">An expert instructor designed this&nbsp;<b fr-original-style="" style="box-sizing: border-box;">&ldquo;Python for Data Science and Machine Learning&rdquo;</b>&nbsp;course to provide you with the best learning experience possible. Our goal is for you to learn and apply the lessons from this course to improve your skills.&nbsp;</p><p style="color: rgb(38, 99, 82) !important; font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(38, 99, 82) !important;">To become a master of Python, Enrol Now!</p><h3 style="color: rgb(0, 0, 0); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Accredited by</span></h3><p style="color: rgb(15, 21, 26); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(15, 21, 26);">This course is <strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">CPDQE&nbsp;</strong>accredited, which serves as an impactful mechanism for skill enhancement.&nbsp;</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">Continuing Professional Development (CPD) stands as a crucial, widely acknowledged method that aids individuals, organisations, and entire industries in staying current with their skills and knowledge.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);">CPD not only facilitates the elevation of global standards and benchmarks, aligning with the growing forces of globalisation and consumer expectations but also transforms learning into a deliberate and proactive process. It motivates professionals to uphold a consistently high level of performance and demonstrates their unwavering commitment to a specific job role or profession.</p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><br fr-original-style="" style="box-sizing: border-box;"></p><p style="color: rgb(0, 0, 0); font-size: var(--font-size); box-sizing: border-box;" fr-original-style=" color: rgb(0, 0, 0);"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;"><span style="font-size: 24px; box-sizing: border-box;" fr-original-style="font-size: 24px;">Course Curriculum</span></strong></p><ul fr-original-style="" style="box-sizing: border-box;"><li id="isPasted" fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Python for Data Science &amp; Machine Learning from A-Z</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science &amp; Machine Learning Concepts</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python For Data Science</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Statistics for Data Science</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Probability and Hypothesis Testing</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">NumPy Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Pandas Data Analysis</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Python Data Visualization</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Introduction to Machine Learning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Loading &amp; Exploration</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Cleaning</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Feature Selecting and Engineering</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Linear and Logistic Regression</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">K Nearest Neighbours</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Decision Trees</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Ensemble Learning and Random Forests</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Support Vector Machines</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">K-Means</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">PCA</strong></li><li fr-original-style="" style="box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">Data Science Career</strong></li></ul>

LearnDrive UK

Data Science

This course aims to teach you how to use Python for machine learning and data science.



Python for Data Science and Machine Learning

Windows 10

Programming

MongoDB

Assuming that you don't know anything about web scraping, Scrapy, Python, web scraping, or even the meaning of web scraping-the author starts from the complete basics.

A well-balanced course with theory and practical content followed by three projects at the end ensures you have the right skills to learn scraping.

Web Scraping Tutorial with Scrapy and Python for Beginners

Data Visualization

Pandas

This course first equips you with the fundamentals of Python and then progresses to teach you how to use various libraries such as NumPy, Pandas, Seaborn, Bokeh, and so on. This course contains several mini projects so that, by the end of this course, you will be equipped with the essential tools you need to become a visualization expert.

Data Understanding and Data Visualization with Python

<div id="course-pills-1">Duration<p>4 Days</p><p>24 CPD hours</p>This course is intended for<p></p><p>This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud.</p><p></p>Overview<p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure.</p><p></p><p>Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow.</p><p></p>Prerequisites<p></p><li>Creating cloud resources in Microsoft Azure.</li>  <li>Using Python to explore and visualize data.</li>  <li>Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow.</li>  <li>Working with containers</li>  <li>AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience.</li><p></p></div><div id="course-pills-2"><h3>1 - Design a data ingestion strategy for machine learning projects</h3> <ul> <li>Identify your data source and format</li> <li>Choose how to serve data to machine learning workflows</li> <li>Design a data ingestion solution</li> </ul> <h3>2 - Design a machine learning model training solution</h3> <ul> <li>Identify machine learning tasks</li> <li>Choose a service to train a machine learning model</li> <li>Decide between compute options</li> </ul> <h3>3 - Design a model deployment solution</h3> <ul> <li>Understand how model will be consumed</li> <li>Decide on real-time or batch deployment</li> </ul> <h3>4 - Design a machine learning operations solution</h3> <ul> <li>Explore an MLOps architecture</li> <li>Design for monitoring</li> <li>Design for retraining</li> </ul> <h3>5 - Explore Azure Machine Learning workspace resources and assets</h3> <ul> <li>Create an Azure Machine Learning workspace</li> <li>Identify Azure Machine Learning resources</li> <li>Identify Azure Machine Learning assets</li> <li>Train models in the workspace</li> </ul> <h3>6 - Explore developer tools for workspace interaction</h3> <ul> <li>Explore the studio</li> <li>Explore the Python SDK</li> <li>Explore the CLI</li> </ul> <h3>7 - Make data available in Azure Machine Learning</h3> <ul> <li>Understand URIs</li> <li>Create a datastore</li> <li>Create a data asset</li> </ul> <h3>8 - Work with compute targets in Azure Machine Learning</h3> <ul> <li>Choose the appropriate compute target</li> <li>Create and use a compute instance</li> <li>Create and use a compute cluster</li> </ul> <h3>9 - Work with environments in Azure Machine Learning</h3> <ul> <li>Understand environments</li> <li>Explore and use curated environments</li> <li>Create and use custom environments</li> </ul> <h3>10 - Find the best classification model with Automated Machine Learning</h3> <ul> <li>Preprocess data and configure featurization</li> <li>Run an Automated Machine Learning experiment</li> <li>Evaluate and compare models</li> </ul> <h3>11 - Track model training in Jupyter notebooks with MLflow</h3> <ul> <li>Configure MLflow for model tracking in notebooks</li> <li>Train and track models in notebooks</li> </ul> <h3>12 - Run a training script as a command job in Azure Machine Learning</h3> <ul> <li>Convert a notebook to a script</li> <li>Run a script as a command job</li> <li>Use parameters in a command job</li> </ul> <h3>13 - Track model training with MLflow in jobs</h3> <ul> <li>Track metrics with MLflow</li> <li>View metrics and evaluate models</li> </ul> <h3>14 - Perform hyperparameter tuning with Azure Machine Learning</h3> <ul> <li>Define a search space</li> <li>Configure a sampling method</li> <li>Configure early termination</li> <li>Use a sweep job for hyperparameter tuning</li> </ul> <h3>15 - Run pipelines in Azure Machine Learning</h3> <ul> <li>Create components</li> <li>Create a pipeline</li> <li>Run a pipeline job</li> </ul> <h3>16 - Register an MLflow model in Azure Machine Learning</h3> <ul> <li>Log models with MLflow</li> <li>Understand the MLflow model format</li> <li>Register an MLflow model</li> </ul> <h3>17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning</h3> <ul> <li>Understand Responsible AI</li> <li>Create the Responsible AI dashboard</li> <li>Evaluate the Responsible AI dashboard</li> </ul> <h3>18 - Deploy a model to a managed online endpoint</h3> <ul> <li>Explore managed online endpoints</li> <li>Deploy your MLflow model to a managed online endpoint</li> <li>Deploy a model to a managed online endpoint</li> <li>Test managed online endpoints</li> </ul> <h3>19 - Deploy a model to a batch endpoint</h3> <ul> <li>Understand and create batch endpoints</li> <li>Deploy your MLflow model to a batch endpoint</li> <li>Deploy a custom model to a batch endpoint</li> <li>Invoke and troubleshoot batch endpoints</li> </ul></div>

Data Engineering

Microsoft AZ-900

Microsoft Azure

Microsoft AZ-303

Microsoft AZ-700

Azure Machine Learning

DP-100T01 Designing and Implementing a Data Science Solution on Azure

"Start your career as a Certified Python Programmer and earn up to £70,000 per Year."
Are you looking to make your mark in the ever-evolving world of Data Analyst? The demand for Python programmers has never been higher. Just in the UK, job postings for Analysts / Python programmers surged by an astounding 70% in 2022. This exponential growth trend signifies the soaring need for skilled Python programmers. Amid this vibrant job market, our Python Programmer online Training is your golden ticket to a prosperous career in programming or Data Analysis. Regardless of your level - beginner or expert - we ensure a comprehensive learning experience that will enhance your current skills and prepare you for the dynamic tech industry.
We envision being your reliable ally throughout your journey - from imparting quality Python training to ensuring your employability in the programming world.
Our Python Certification Program offers more than just technical know-how. We extend comprehensive career mentoring and support designed to mould you into an industry-ready professional. We'll assist you in creating an impressive resume, preparing for interviews, and landing your dream job. With a vast network of partner companies continually looking for Python programmers, we provide an opportunity to get your foot in the door of your desired companies.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Programmers, so we can help you get your foot in the door.
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So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Certified Python Programmers:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in Python.
One-On-One Consultation: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Python programming field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
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Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Courses we will provide once you enrol in the program:
Course 01: Computer Science With Python
Course 02: Ultimate Python Training for Beginners
Course 03: Python Intermediate Training
Course 04: Python Advanced Training
Course 05: Deep Learning & Neural Networks Python - Keras
Course 06: Complete Python Machine Learning & Data Science Fundamentals
Course 06: Introduction to Data Analysis
Course 07: Business and Data Analytics for Beginners
Course 08: Data Analytics with Tableau
Course 09: Quick Data Science Approach from Scratch
Course 10: Learn MySQL from Scratch for Data Science and Analytics
Course 11: SQL for Data Science, Data Analytics and Data Visualization
Course 12: Statistics & Probability for Data Science & Machine Learning
Course 13: Basic Google Data Studio
Course 14: Machine Learning with Python Course
Course 15: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 16: Web Scraping and Mapping Dam Levels in Python and Leaflet
Course 17: Coding Essentials - Javascript, ASP. Net, C#
Course 19: Master JavaScript with Data Visualization
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Python Certification - IT Training is completed in 9 easy steps:
Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Python Certification Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 19 Premium Courses related to Python Programming. These courses will teach you the knowledge and skills required to become a successful Python Prgrammer. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the programming/development industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.
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We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.
Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
Step 9: Celebrate Your New Job!
Once you've secured your dream job in Python Programming, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Python Programming begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
This Python Certification Course is suitable for:
Beginners with no prior programming experience who are looking to enter the world of coding.
Intermediate programmers who wish to expand their skills and explore Python's extensive usage.
IT professionals seeking to diversify their skill sets and stay relevant in today's tech-driven market.
Data analysts and scientists who want to leverage Python's powerful libraries for their data processing needs.
Students and recent graduates looking to enhance their employability in the thriving tech industry.
Entrepreneurs who wish to understand and utilise Python to automate tasks and analyse data for their businesses.
Anyone with a keen interest in Python programming and a desire to delve into its applications in diverse fields like web development, data science, machine learning, and more.
 Requirements 
No experience required. Just enrol & start learning python.
 Career path 
Upon completion of our Program, the potential career paths include:
Python Developer: £30,000 - £90,000 annually
Data Scientist: £40,000 - £100,000 annually
Machine Learning Engineer: £50,000 - £110,000 annually
Data Analyst: £35,000 - £85,000 annually
Software Engineer: £35,000 - £95,000 annually
Back-end Developer: £40,000 - £95,000 annually
Web Developer: £30,000 -£85,000 annually
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Academy for Health and Fitness

Career Development

IT Certifications

Become an IT professional with our Python Certification - IT Job Ready Program! Gain comprehensive skills in Python programming, data analysis, and automation. We offer a money-back guarantee if you don't secure a job within six months of completion. Enroll now and jumpstart your tech career!


Ready to land your dream job in tech? Our Python Certification - IT Job Ready Program equips you with essential Python programming, data analysis, and automation skills. Plus, we offer a money-back guarantee if you don't get hired within six months of completing the course. Don't miss out – enroll today and take the first step towards a successful IT career! 💻📊 #PythonCertification #TechTraining #CareerReady #MoneyBackGuarantee

Python Certification - IT Job Ready Program with Money Back Guarantee

<p><strong>Start your career in Data Science and earn up to £90,000 per month.</strong></p><p>Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring Data <strong>Scientists</strong>, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!</p><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:</p><ul><li><strong>Personalised Guidance:</strong> We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.<br /><br /></li><li><strong>Interview Preparation:</strong> No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a <strong>100% money-back guarantee. </strong>If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.<br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Business and Data Analytics for Beginners</li><li>Course 02: Quick Data Science Approach from Scratch</li><li>Course 03: Learn MySQL from Scratch for Data Science and Analytics</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Statistics &amp; Probability for Data Science &amp; Machine Learning</li><li>Course 06: R Programming for Data Science</li><li>Course 07: Python Data Science with Numpy, Pandas and Matplotlib</li><li>Course 08: Complete Python Machine Learning &amp; Data Science Fundamentals</li><li>Course 09: 2021 Data Science &amp; Machine Learning with R from A-Z</li><li>Course 10: Python Programming from Scratch with My SQL Database</li><li>Course 11: Level 2 Python Course</li><li>Course 12: Machine Learning for Predictive Maps in Python and Leaflet</li><li>Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI</li><li>Course 14: Python for Spatial Analysis in ArcGIS</li><li>Course 15: Ultimate Python Training for Beginners</li><li>Course 16: PyScript Fundamentals Training</li></ul><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The </strong><strong>Data Scientist with Python </strong><strong>Program is completed in 9 easy steps:<br /><br /></strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.<br /><br /></p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.<br /><br /></p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. <br /><br /></p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.<br /><br /></p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.<br /><br /></p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.<br /><br /></p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.<br /><br /></p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Beginners with an interest in Data Science and Python programming.</li><li>Programmers and Software Engineers looking to transition into Data Science.</li><li>Business Analysts and Project Managers aiming to leverage Data Science in their domains.</li><li>Researchers and Academics who wish to utilise Python for complex data analysis.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Scientist: £60,000 - £90,000</li><li>Machine Learning Engineer: £65,000 - £100,000</li><li>Data Analyst: £40,000 - £60,000</li><li>Business Intelligence Analyst: £45,000 - £70,000</li><li>Data Engineer: £50,000 - £80,000</li><li>Big Data Architect: £70,000 - £120,000</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career in Data Science and earn up to £90,000 per month.
Are you eager to dive into the high-speed world of Data Science powered by Python? In the UK alone, Data Scientist job postings witnessed a dramatic increase of 67% in 2022, emphasising the burgeoning demand for proficient Python programmers. Amid such a dynamic job market, our online course - Data Science with Python, serves as your stepping-stone to a universe of opportunities. Whether you're taking your first step into the realm of Data Science or aiming to augment your existing skills, our program offers peerless support, ensuring you're industry-ready by the time you complete our course.
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Python experience, we will guide you towards honing your skills and developing a strong foundation in both Data Science and Python.
One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. We believe in the value we provide and want you to feel completely satisfied with your decision to join us.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance.
Here are the courses we will provide once you enrol in the program:
Course 01: Business and Data Analytics for Beginners
Course 02: Quick Data Science Approach from Scratch
Course 03: Learn MySQL from Scratch for Data Science and Analytics
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Statistics & Probability for Data Science & Machine Learning
Course 06: R Programming for Data Science
Course 07: Python Data Science with Numpy, Pandas and Matplotlib
Course 08: Complete Python Machine Learning & Data Science Fundamentals
Course 09: 2021 Data Science & Machine Learning with R from A-Z
Course 10: Python Programming from Scratch with My SQL Database
Course 11: Level 2 Python Course
Course 12: Machine Learning for Predictive Maps in Python and Leaflet
Course 13: Python Programming Bible | Networking, GUI, Email, XML, CGI
Course 14: Python for Spatial Analysis in ArcGIS
Course 15: Ultimate Python Training for Beginners
Course 16: PyScript Fundamentals Training
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Scientist with Python Program is completed in 9 easy steps:


Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Science with Python Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Science with Python. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.


Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.


Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Science with Python industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently. 


Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.


Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.


Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.


Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.


Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Science with Python, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science with Python begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Beginners with an interest in Data Science and Python programming.
Programmers and Software Engineers looking to transition into Data Science.
Business Analysts and Project Managers aiming to leverage Data Science in their domains.
Researchers and Academics who wish to utilise Python for complex data analysis.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Scientist: £60,000 - £90,000
Machine Learning Engineer: £65,000 - £100,000
Data Analyst: £40,000 - £60,000
Business Intelligence Analyst: £45,000 - £70,000
Data Engineer: £50,000 - £80,000
Big Data Architect: £70,000 - £120,000
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Big Data Analytics

Data Skills

Data Science with Python - IT Job Ready Program with Career Support & Money Back Guarantee

<strong>Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.</strong>
        <p>This course will teach you Python in a practical manner, complete with examples, quizzes, exercises, and more. You will learn when to use Python 2 and Python 3; both versions are covered in the course and you will learn to program in both. You'll learn how to take tedious and repetitious tasks and turn them into programs that will save you time and simplify your life on Linux, UNIX, or MAC systems. You will learn how to prepare your computer for programming in Python; how to work with various data types including strings, lists, tuples, dictionaries, Booleans; how to perform mathematical operations using Python, and more.</p>
        <h2>What You Will Learn</h2><p>When to use Python 2 and when to use Python 3.<br>How to install Python on Windows, Mac, and Linux.<br>How to prepare your computer for programming in Python.<br>The various ways to run a Python program on Windows, Mac, and Linux.<br>Suggested text editors and Integrated Development Environments to use when coding in Python.<br>How to work with various data types including strings, lists, tuples, dictionaries, Booleans, and more.<br>What variables are and when to use them.<br>How to perform mathematical operations using Python.<br>How to capture input from a user.<br>Ways to control the flow of your programs.<br>The importance of white space in Python.<br>How to organize your Python programs: learn what goes where.<br>What modules are, when you should use them, and how to create your own.<br>How to define and use functions.<br>Important built-in Python functions that you ll use often.<br>How to read from and write to files.<br>The difference between binary and text files.<br>Various ways of getting help, including finding Python documentation.<br></p>
        <h2>Audience</h2><p>This course targets anyone interested in Python programming, Python scripting, or computer programming in general; those who want to become a highly paid Python developer; and those who want to open up doors in their IT career by learning one of the world's most popular and in-demand programming languages.</p>
        <h2>Approach</h2><p>A complete course packed with step-by-step instructions, practice exercises with solutions, and quizzes. This course is clearly divided into small parts to help you understand each part individually and learn at your own pace. Once you've completed this course you'll know how to write programs that will run on the Linux, Mac, and Windows operating systems. You can even take what you've learned and apply it to web applications. </p>
        <h2>Key Features</h2><p>How to install Python on Windows, Mac, and Linux. * A practical tutorial designed for Python beginners. * </p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-for-beginners-learn-python-programming-python-3-</p>
        <h2>About the Author</h2><h3>Jason Cannon</h3><p>Jason Cannon is a professional system administrator, consultant, and author. He started his career as a Unix and Linux System engineer in 1999. Since that time, he has utilized his Linux skills at companies such as Xerox, UPS, Hewlett-Packard, and Amazon.com. Additionally, he has acted as a technical consultant and independent contractor for small businesses and Fortune 500 companies.

Jason has professional experience with CentOS, RedHat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu. He has used several Linux distributions on personal projects including Debian, Slackware, CrunchBang, and others. In addition to Linux, Jason has experience supporting proprietary Unix operating systems including AIX, HP-UX, and Solaris. He enjoys teaching others how to use and exploit the power of the Linux operating system.</p>
        <h2>Course Outline</h2><h4>1. Course Overview and Downloads</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Course Overview</p><p style='margin: 0'>Course Overview and Downloads: Course Overview</p></td></tr></tbody></table><br><h4>2. Python Setup</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Python 2 vs Python 3</p><p style='margin: 0'>Python Setup: Python 2 vs Python 3</p></td></tr><tr><td style='padding: 15px;'><p>2. Installing Python on Windows</p><p style='margin: 0'>Python Setup: Installing Python on Windows</p></td></tr><tr><td style='padding: 15px;'><p>3. Installing Python on Mac</p><p style='margin: 0'>Python Setup: Installing Python on Mac</p></td></tr><tr><td style='padding: 15px;'><p>4. Installing Python on Linux</p><p style='margin: 0'>Python Setup: Installing Python on Linux</p></td></tr><tr><td style='padding: 15px;'><p>5. Writing Python Programs</p><p style='margin: 0'>Python Setup: Writing Python Programs</p></td></tr><tr><td style='padding: 15px;'><p>6. Running Python Programs</p><p style='margin: 0'>Python Setup: Running Python Programs</p></td></tr></tbody></table><br><h4>3. Strings and Variables</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Strings and Variables: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Variables and Strings</p><p style='margin: 0'>Strings and Variables: Variables and Strings</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions and Printing</p><p style='margin: 0'>Strings and Variables: Functions and Printing</p></td></tr><tr><td style='padding: 15px;'><p>4. String Methods</p><p style='margin: 0'>Strings and Variables: String Methods</p></td></tr><tr><td style='padding: 15px;'><p>5. String Concatenation</p><p style='margin: 0'>Strings and Variables: String Concatenation</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatting Strings</p><p style='margin: 0'>Strings and Variables: Formatting Strings</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Strings and Variables: Section Summary</p></td></tr><tr><td style='padding: 15px;'><p>8. Solutions to the Practice Exercises - #1 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #1 - Video</p></td></tr><tr><td style='padding: 15px;'><p>9. Solutions to the Practice Exercises - #2 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #2 - Video</p></td></tr><tr><td style='padding: 15px;'><p>10. Solutions to the Practice Exercises - #3 - Video</p><p style='margin: 0'>Strings and Variables: Solutions to the Practice Exercises - #3 - Video</p></td></tr></tbody></table><br><h4>4. Numbers and Math</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Numbers and Math: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Numbers, Numeric Operations, and Numeric Functions</p><p style='margin: 0'>Numbers and Math: Numbers, Numeric Operations, and Numeric Functions</p></td></tr><tr><td style='padding: 15px;'><p>3. Comments</p><p style='margin: 0'>Numbers and Math: Comments</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Numbers and Math: Section Summary</p></td></tr></tbody></table><br><h4>5. Booleans and Conditionals</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Booleans and Conditionals: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Booleans</p><p style='margin: 0'>Booleans and Conditionals: Booleans</p></td></tr><tr><td style='padding: 15px;'><p>3. Conditionals</p><p style='margin: 0'>Booleans and Conditionals: Conditionals</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Booleans and Conditionals: Section Summary</p></td></tr></tbody></table><br><h4>6. Functions</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Functions: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Functions, Part I</p><p style='margin: 0'>Functions: Functions, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions, Part II</p><p style='margin: 0'>Functions: Functions, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Functions: Section Summary</p></td></tr></tbody></table><br><h4>7. Lists</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Lists: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Lists</p><p style='margin: 0'>Lists: Lists</p></td></tr><tr><td style='padding: 15px;'><p>3. Slices</p><p style='margin: 0'>Lists: Slices</p></td></tr><tr><td style='padding: 15px;'><p>4. Exception Handling</p><p style='margin: 0'>Lists: Exception Handling</p></td></tr><tr><td style='padding: 15px;'><p>5. Loops</p><p style='margin: 0'>Lists: Loops</p></td></tr><tr><td style='padding: 15px;'><p>6. Sorting and Ranges</p><p style='margin: 0'>Lists: Sorting and Ranges</p></td></tr><tr><td style='padding: 15px;'><p>7. Section Summary</p><p style='margin: 0'>Lists: Section Summary</p></td></tr></tbody></table><br><h4>8. Dictionaries</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Dictionaries: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Dictionaries - Part I</p><p style='margin: 0'>Dictionaries: Dictionaries - Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Dictionaries - Part II</p><p style='margin: 0'>Dictionaries: Dictionaries - Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Dictionaries: Section Summary</p></td></tr></tbody></table><br><h4>9. Tuples</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Tuples: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Tuples</p><p style='margin: 0'>Tuples: Tuples</p></td></tr><tr><td style='padding: 15px;'><p>3. Section Summary</p><p style='margin: 0'>Tuples: Section Summary</p></td></tr></tbody></table><br><h4>10. Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Files: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Files, Part I</p><p style='margin: 0'>Files: Files, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Files, Part II</p><p style='margin: 0'>Files: Files, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Summary</p><p style='margin: 0'>Files: Section Summary</p></td></tr></tbody></table><br><h4>11. Modules</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr><tr><td style='padding: 15px;'><p>2. Modules, Part I</p><p style='margin: 0'>Modules: Modules, Part I</p></td></tr><tr><td style='padding: 15px;'><p>3. Modules, Part II</p><p style='margin: 0'>Modules: Modules, Part II</p></td></tr><tr><td style='padding: 15px;'><p>4. Section Overview</p><p style='margin: 0'>Modules: Section Overview</p></td></tr></tbody></table>

Learn Python Programming the Easy Way, Complete with Examples, Quizzes, Exercises and more. Learn Python 2 and Python 3.

Python for Beginners: Learn Python Programming (Python 3)

<strong>You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.</strong>
        <p>'Python is the future of artificial intelligence and machine learning.'-Adrian Rosebrock, author.

Python is the programming language most loved by developers, data scientists, software engineers, and even hackers.

This Python basic to advanced course covers the fundamental concepts of Python programming and ways to apply this to real-world applications. The course modules, lesson-end quizzes, and lesson-end projects collectively cover the training course topics such as data operations, strings, file I/O, exception handling, error handling, conditional statements, CGI programming, shell scripting, web scraping, and Django.

It also covers Logging Framework, Unittest Framework, Socket Programming, Tornado Framework, and Networking. You will also build a Python chat server.

By the end of this course, you will have the skills to create and send robust Python applications using off-the-rack libraries confidently.

The code bundle for this course is available at: https://github.com/PacktPublishing/Python-Programming</p>
        <h2>What You Will Learn</h2><p>Learn the basics of Python<br>Learn networking and database access using Python and CGI programming<br>Understand the Python debugger<br>Understand web scraping using Beautiful Soup<br>Learn about Python Unittest<br>Build a Python chat server</p>
        <h2>Audience</h2><p>This course is for new Python users looking to make the best of this powerful programming language-college freshers, software developers, programming enthusiasts, and technical leads. Python is widely used in artificial intelligence, so if you are planning to start your career in AI/machine learning then you need to have an understanding of Python as a prerequisite.</p>
        <h2>Approach</h2><p>This course comprises self-paced videos, demos, lesson-end quizzes, and a competitive course-end project. This will help you increase your in-depth understanding of Python's design, memory models, object-arranged highlights, and information, and be industry-prepared.</p>
        <h2>Key Features</h2><p>Go from a beginner level to a confident level of Python programming * Increase your in-depth understanding of Python's design, memory models, and more * Work on a competitive project at the end of the course</p>
        <h2>Github Repo</h2><p>https://github.com/packtpublishing/python-programming</p>
        <h2>About the Author</h2><h3>Learnkart Technology Private Limited</h3><p>Learnkart understands the importance of upskilling and its impact on you. They pride themselves in creating specialized e-learning courses that will not only prepare you for certification exams but also help you gain hands-on knowledge for real-world applications. Thousands of students have developed their skills with Learnkart through a variety of courses, such as PgMP, Risk Management Professional (RMP), speech recognition, Python, Amazon Web Services (AWS), and more. Learnkart regularly adds courses to its portfolio to lend more value to your learning experience.</p>
        <h2>Course Outline</h2><h4>1. Course Introduction</h4><p></p><br><h4>2. Python Basics</h4><p></p><br><h4>3. Data Operations</h4><p></p><br><h4>4. Conditional Statements and Functions</h4><p></p><br><h4>5. Error Handling and File Operations</h4><p></p><br><h4>6. Shell Scripting and Django</h4><p></p><br><h4>7. Course End Project</h4><p></p>

You will master the fundamentals and more advanced principles of Python programming in this beginner's tutorial. This Python course covers every Python fundamental, including installation and more complex material such as Python data science.

Python Programming

<p><strong>Start your career as a Data Scientist and earn upto £90,000/ Year</strong></p><p>Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!</p><p><strong>Our mission is simple</strong> - to be your trusted partner every step of the way, from training to employment.</p><p>In addition to teaching you the technical skills you need, we will also provide you with <strong>career mentoring and support</strong>. We will help you build your resume, prepare for interviews, and land your <strong>dream job</strong>. We also have<strong> partnerships with many companies</strong> that are hiring <strong>Data Scientists</strong>, so we can help you get your foot in the door.</p><p>If you are not happy with our service, we also offer a <strong>100% money-back guarantee</strong>. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!</p><p>If you have any questions, you can <strong>contact us</strong>. We will be happy to provide you with all the information you need.</p><p><strong>Why Choose Us?</strong></p><p>So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:</p><ul><li><strong>Personalised Guidance:</strong> We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some <strong>Data Scientist</strong> experience, we will guide you towards honing your skills and developing a strong foundation in <strong>Data Science</strong>.<br /><br /></li><li><strong>Tailored CV Building:</strong> Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.<br /><br /></li><li><strong>One-On-One Consultation Sessions with Industry Experts:</strong> Gain invaluable insights and guidance from seasoned professionals who have thrived in the <strong>Data Science</strong> field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.<br /><br /></li><li><strong>Extensive Job Opportunities:</strong> We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere. <br /><br /></li><li><strong>Interview Preparation:</strong> No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.<br /><br /></li><li><strong>Money-Back Guarantee:</strong> Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a <strong>100% money-back guarantee. </strong>If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked. <br /><br /></li><li><strong>Continuous Career Support: </strong>Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.</li></ul><p><strong>Here are the courses we will provide once you enrol in the program:</strong></p><ul><li>Course 01: Ultimate Python Training for Beginners</li><li>Course 02: Python Intermediate Training</li><li>Course 03: Python Advanced Training</li><li>Course 04: SQL for Data Science, Data Analytics and Data Visualization</li><li>Course 05: Basic Data Analysis</li><li>Course 06: Develop Big Data Pipelines with R &amp; Sparklyr &amp; Tableau</li><li>Course 07: Develop Big Data Pipelines with R, Sparklyr &amp; Power BI</li><li>Course 08: Customer Analytics Training</li><li>Course 09: Google Analytics for Everyone</li><li>Course 10: Google Data Studio: Data Analytics</li><li>Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB</li><li>Course 12: Big Data Analytics with PySpark Power BI and MongoDB</li><li>Course 13: Excel Data Analysis</li><li>Course 14: Introduction to Data Analytics with Tableau</li><li>Course 15: Machine Learning with Python Course</li><li>Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI</li></ul><p><strong>How Can We Offer Job Guarantees?</strong></p><p>HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.</p> <p><strong>The </strong><strong>Data Scientist with Python </strong><strong>Program is completed in 9 easy steps:</strong></p><p><strong>Step 1: Enrol in the Programme</strong></p><p>Begin your exciting journey with us by enrolling in the <strong>Data Scientist </strong>Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.</p><p>After you enrol in the Program, you will get lifetime access to 16 premium courses related to <strong>Data Scientist</strong>. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!</p><p><strong>Step 2: Initial One-On-One Counselling Session</strong></p><p>Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.</p><p><strong>Step 3 - </strong><strong>Certification upon Course Completion</strong></p><p>After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.</p><p><strong>Step 4: </strong><strong>CV Revamping</strong></p><p>Our team of professionals will build you a compelling CV and <strong>LinkedIn profile</strong>. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the <strong>Data Scientist</strong> industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.</p><p><strong>Step 5: Building Network and Submitting CV</strong></p><p>We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many<strong> high-profile individuals and companies</strong> through your LinkedIn profile.</p><p><strong>Step 6: Interview Preparation</strong></p><p>With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.</p><p><strong>Step 7: Securing Job Interviews</strong></p><p>Leveraging our partnerships with leading companies, <strong>we'll secure job interviews for you</strong>. We'll ensure you get the opportunity to showcase your skills to potential employers and <strong>get the dream job you want</strong>.</p><p><strong>Step 8: Post-Interview Support</strong></p><p>Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.</p><p><strong>Step 9: Celebrate Your New Job!</strong></p><p>Once you've secured your dream job in Data Science, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.</p><p>We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in <strong>Data Science</strong> begins with us.</p> <h2>
        
        <div>CPD</div>
    </h2>

                        <div id="cpd">
                            <div>
                                <div>
                                    <div>
                                        100 CPD hours / points
                                    </div>
                                        <div>
                                            Accredited by CPD Quality Standards
                                        </div>
                                </div>
                            </div>
                        </div> <h2>
        
        <div>Who is this course for?</div>
    </h2>

                        <div id="who_is_this_course_for">
                            <ul><li>Aspiring data scientists looking to enter the exciting field of data science.</li><li>Professionals from other disciplines who want to transition into the data science domain.</li><li>Software engineers or programmers interested in expanding their skill set to include data science.</li><li>Analysts or researchers who want to enhance their data analysis and modeling capabilities.</li><li>Students or graduates seeking to kick-start their careers in data science with a strong foundation.</li></ul>
                        </div> <h2>
        
        <div>Requirements</div>
    </h2>

                        <div id="requirements">
                            <p>No experience required. Just enrol &amp; start learning.</p>
                        </div> <h2>
        
        <div>Career path</div>
    </h2>

                        <div id="career_path">
                            <ul><li>Data Analyst: £25,000 - £55,000 per year</li><li>Data Scientist: £40,000 - £85,000 per year</li><li>Machine Learning Engineer: £50,000 - £100,000 per year</li><li>Data Engineer: £45,000 - £80,000 per year</li><li>Business Intelligence Analyst: £35,000 - £65,000 per year</li><li>Data Science Manager: £70,000 - £120,000 per year.</li></ul>
                        </div> <h2>
        
        <div>Certificates</div>
    </h2>

                        <div id="optional_extras">
                                    <h4>CPD Accredited e-Certificate</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>CPD Accredited Framed (Hardcopy) Certificate</h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Enrolment Letter</h4>
        <p>
            Digital certificate -
            Included
        </p>
        <h4>QLS Endorsed Hard Copy Certificate </h4>
        <p>
            Hard copy certificate -
            Included
        </p>
        <h4>Student ID Card</h4>
        <p>
            Digital certificate -
            Included
        </p>

                        </div>

Start your career as a Data Scientist and earn upto £90,000/ Year
Are you ready to unlock the power of Python and dive into the exciting world of data science? Look no further because we have the ultimate solution for you: Introducing our Data Science with Python Course with Career Support and Job Ready Program!
Our mission is simple - to be your trusted partner every step of the way, from training to employment.
In addition to teaching you the technical skills you need, we will also provide you with career mentoring and support. We will help you build your resume, prepare for interviews, and land your dream job. We also have partnerships with many companies that are hiring Data Scientists, so we can help you get your foot in the door.
If you are not happy with our service, we also offer a 100% money-back guarantee. So what are you waiting for? Enrol in our Data Scientist with Python Training Program today and start your journey to becoming a successful Data Scientist!
If you have any questions, you can contact us. We will be happy to provide you with all the information you need.
Why Choose Us?
So, what sets us apart from other programs? Let's dive into the exceptional benefits you'll experience when you join our Data Scientist with Python:
Personalised Guidance: We believe in the power of individual attention. Our experienced mentors will provide one-on-one counselling sessions tailored to your specific needs. Whether you're a beginner or have some Data Scientist experience, we will guide you towards honing your skills and developing a strong foundation in Data Science.
Tailored CV Building: Crafting an impressive CV is crucial in today's competitive job market. Our team of experts will work closely with you to create a professional CV that showcases your skills and highlights your potential as a Data Scientist. We'll ensure that your CV stands out among the rest, increasing your chances of landing that dream job.
One-On-One Consultation Sessions with Industry Experts: Gain invaluable insights and guidance from seasoned professionals who have thrived in the Data Science field. Our consultation sessions provide you with insider tips, tricks, and advice, empowering you to navigate the industry with confidence and expertise.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Data Scientists. Through our network, we'll connect you with exclusive job openings that are not easily accessible elsewhere.
Interview Preparation: No more stress over unexpected interview questions. We provide you with access to a comprehensive database of potential interview questions curated over years of industry experience. Walk into your interviews confident, well-prepared, and ready to impress.
Money-Back Guarantee: Your satisfaction is our top priority. We are confident in the quality of our training and support, which is why we offer a 100% money-back guarantee. If, for any reason, you're not happy with our services, we'll refund your investment, no questions asked.
Continuous Career Support: Our commitment doesn't end when you secure a job. We'll be there for you throughout your career journey, offering continued support and guidance. Whether you need advice on career advancement, assistance with new projects, or simply a friendly ear to share your achievements, we'll be your trusted partner for long-term success.
Here are the courses we will provide once you enrol in the program:
Course 01: Ultimate Python Training for Beginners
Course 02: Python Intermediate Training
Course 03: Python Advanced Training
Course 04: SQL for Data Science, Data Analytics and Data Visualization
Course 05: Basic Data Analysis
Course 06: Develop Big Data Pipelines with R & Sparklyr & Tableau
Course 07: Develop Big Data Pipelines with R, Sparklyr & Power BI
Course 08: Customer Analytics Training
Course 09: Google Analytics for Everyone
Course 10: Google Data Studio: Data Analytics
Course 11: Big Data Analytics with PySpark Tableau Desktop and MongoDB
Course 12: Big Data Analytics with PySpark Power BI and MongoDB
Course 13: Excel Data Analysis
Course 14: Introduction to Data Analytics with Tableau
Course 15: Machine Learning with Python Course
Course 16: Python Programming Bible | Networking, GUI, Email, XML, CGI
How Can We Offer Job Guarantees?
HF Online provides consultancy, professional and educational services to many of the companies in the UK. During our intense exclusive training program, you will not just gain and complete the industry valuable certification but will gain industry experience as well, which is imperative to get your 1st job in the sector.
The Data Scientist with Python Program is completed in 9 easy steps:
Step 1: Enrol in the Programme
Begin your exciting journey with us by enrolling in the Data Scientist Training program. Complete your registration and make a secure online payment. Remember, we offer a 14-day money-back guarantee if you're not completely satisfied.
After you enrol in the Program, you will get lifetime access to 16 premium courses related to Data Scientist. These courses will teach you the knowledge and skills required to become a successful Data Scientist. Our customer service team will help you and keep in contact with you every step of the way. So you won't have to worry about a thing!
Step 2: Initial One-On-One Counselling Session
Once enrolled, you will be paired with a dedicated career mentor. Schedule your first one-on-one session to discuss your career aspirations, skills, experience, and any areas for potential growth. This conversation will shape your learning and development path.
Step 3 - Certification upon Course Completion
After learning from the courses, you must obtain certificates for each course. There will be exams for every course, and you have to pass them to get your certificate. To pass successfully, you must get 90% marks. Once you pass the exams, you will receive hardcopy certificates. These certificates will prove that you're an expert in the subject.
Step 4: CV Revamping
Our team of professionals will build you a compelling CV and LinkedIn profile. We'll ensure it presents your skills and qualifications effectively and is tailored to the needs and expectations of the Data Scientist industry. With these powerful tools in hand, you'll be fully prepared to tackle job interviews confidently.
Step 5: Building Network and Submitting CV
We understand the power of casting a wide net. We'll strategically submit your CV to various platforms and networks, expanding your reach and connecting you with valuable opportunities that align with your career goals. We will also make connections with many high-profile individuals and companies through your LinkedIn profile.
Step 6: Interview Preparation
With your CV ready, we'll move on to interview preparation. Gain exclusive access to our database of potential interview questions. Through simulated interviews with your mentor, you'll practice your responses and receive valuable feedback to further refine your skills.
Step 7: Securing Job Interviews
Leveraging our partnerships with leading companies, we'll secure job interviews for you. We'll ensure you get the opportunity to showcase your skills to potential employers and get the dream job you want.
Step 8: Post-Interview Support
Post-interview, we'll provide a debriefing session to reflect on your performance and identify areas of improvement for future interviews if necessary. Remember, our commitment extends until you land your dream job.
Step 9: Celebrate Your New Job!
Once you've secured your dream job in Data Science, it's time to celebrate! However, our support doesn't end there. We'll provide you with ongoing career advice to ensure you continue to thrive in your new role.
We're excited to accompany you on this journey to success. Enrol today, and let's get started! Your path to a successful career in Data Science begins with us.
 CPD 
100 CPD hours / points  Accredited by CPD Quality Standards
 Who is this course for? 
Aspiring data scientists looking to enter the exciting field of data science.
Professionals from other disciplines who want to transition into the data science domain.
Software engineers or programmers interested in expanding their skill set to include data science.
Analysts or researchers who want to enhance their data analysis and modeling capabilities.
Students or graduates seeking to kick-start their careers in data science with a strong foundation.
 Requirements 
No experience required. Just enrol & start learning.
 Career path 
Data Analyst: £25,000 - £55,000 per year
Data Scientist: £40,000 - £85,000 per year
Machine Learning Engineer: £50,000 - £100,000 per year
Data Engineer: £45,000 - £80,000 per year
Business Intelligence Analyst: £35,000 - £65,000 per year
Data Science Manager: £70,000 - £120,000 per year.
 Certificates 
CPD Accredited e-Certificate
 Digital certificate - Included 
CPD Accredited Framed (Hardcopy) Certificate
 Hard copy certificate - Included 
Enrolment Letter
 Digital certificate - Included 
QLS Endorsed Hard Copy Certificate
 Hard copy certificate - Included 
Student ID Card
 Digital certificate - Included 

Data Analyst

Data Scientist with Python - IT Job Ready Program + Career Support & Money Back Guarantee

Master Python 3.10 from the experts with this course and demonstrate programming wizardry in Python. Go from a geek to a wizard in no time with this well-structured video course and write Python code like a pro. Learn about the often-forgotten basics and special features of programming and Python in general.

The Ultimate Guide to Python Programming with Python 3.10

<strong>This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.</strong>
        <p>Python is one of the most popular computer programming languages and this hands-on course for beginners will make it easy for someone who wants to get started with learning Python.

This course takes you through the introduction to the course and the learning objectives. You will learn to get started with Replit and write your first Python program. You will learn to store, process, and compare information in Python as well as learn to tidy messy data. You will learn about variables, strings, dictionaries, indexing, and slicing in Python. Further, you will understand loops in Python along with break, continue, and else functions.

Moving ahead, you will understand error handling in Python, get to know the try-and-catch block, and learn to add resources to Replit. You will also understand function parameters and explore the difference between local and global variables, and positional and keyword parameters. You will learn to work with JSON and clean the data along with various numeric functions such as min, max, and sum.

By the end of the course, you will gain a solid foundation in Python programming and be able to write high-quality code in Python.

All resources and code files are placed here: https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>What You Will Learn</h2><p>Master Python programming fundamentals<br>Learn how to install Python to get up and running in no time<br>Learn how to process data to create Olympics Medals Tables<br>Solve multiple specific problems for a customer in the real world<br>Learn all about objects and variables in Python<br>Understand functions and function parameters in Python</p>
        <h2>Audience</h2><p>Whether you are a software engineer, software developer, computer programmer, web developer, transitioning into a new role, or simply someone who wants to understand what makes Python tick, this is the place to start. If you are preparing for a Python certification or job role, this course is for you.</p>
        <h2>Approach</h2><p>This course is video based course with no supporting document necessary. It takes you through the fundamentals of Python and teaches you how to use it with a simple tool so you can master the fundamentals in a day.</p>
        <h2>Key Features</h2><p>Be fluent in writing Python code and working with all the fundamentals of the language such as a list, string, function, dictionary, array, set, and much more * Learn to use Python's data analysis capabilities to analyze data from a real-world data source * A complete overview of the basics with exercises to test your knowledge of storing, processing, and storing information</p>
        <h2>Github Repo</h2><p>https://github.com/PacktPublishing/Python-Bootcamp-in-a-day---Python-Programming-for-Beginners</p>
        <h2>About the Author</h2><h3>Paul Ashun</h3><p>Paul Ashun is the CEO, MD, and chief consultant at Pashun Consulting Ltd., specializing in Scrum coaching and leadership within major global organizations. They are the authors of over 10 books on Scrum such as The Power of Scrum in the Real World, Confessions of a Scrum Master as well as the upcoming Agile User Storybook.

He started as a software developer and over ten years later, he became an Agile portfolio manager. He is a certified Scrum Master and a PMO manager. He has led projects for the BBC, General Electric, Oracle, BSkyB, HiT Entertainment, and Razorfish. He has been coaching product owners and business analysts in international blue-chip companies, dating back to 1999, in Agile and Scrum practices such as writing user stories.</p>
        <h2>Course Outline</h2><h4>1. Introduction</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Introduction</p><p style='margin: 0'>This video is an introduction the course and what you can expect from the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Learning Objectives - Introduction</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>3. What Is Python?</p><p style='margin: 0'>This video explains what Python is and the need for Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Example</p><p style='margin: 0'>This video explains an example of a software engineer working in a media company to support the development team.</p></td></tr></tbody></table><br><h4>2. Getting Set Up</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. How to Get Started with Replit</p><p style='margin: 0'>This video explains how to get started with Replit.</p></td></tr><tr><td style='padding: 15px;'><p>3. Writing Your First Python Program-Hello World</p><p style='margin: 0'>This video explains writing your first Python program-Hello World.</p></td></tr></tbody></table><br><h4>3. Storing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Objects and Variables</p><p style='margin: 0'>This video explains objects and variables in Python using an example of Olympic results.</p></td></tr><tr><td style='padding: 15px;'><p>3. Variable Names</p><p style='margin: 0'>This video explains variable names in Python and the rules to use them.</p></td></tr><tr><td style='padding: 15px;'><p>4. Numbers</p><p style='margin: 0'>This video explains the different types of numbers in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. Strings</p><p style='margin: 0'>This video explains strings in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Showing Output When Running Python</p><p style='margin: 0'>This video explains showing output when running Python.</p></td></tr></tbody></table><br><h4>4. Processing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Information</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Processing Information</p><p style='margin: 0'>This video explains processing information in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Indexing</p><p style='margin: 0'>This video explains indexing in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Slices</p><p style='margin: 0'>This video explains slices in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. String Functions</p><p style='margin: 0'>This video explains string functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. The 'input' Function</p><p style='margin: 0'>This video explains the input function in Python.</p></td></tr><tr><td style='padding: 15px;'><p>7. More String Operations</p><p style='margin: 0'>This video explains more string operations in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Converting Between Different Types</p><p style='margin: 0'>This video explains converting between different types.</p></td></tr></tbody></table><br><h4>5. Comparing Information</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Comparing Information</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Comparing Information</p><p style='margin: 0'>This video explains comparing information in Python.</p></td></tr></tbody></table><br><h4>6. Tidying Messy Data</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Tidying Messy Data</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Tidying Messy Data</p><p style='margin: 0'>This video explains how to tidy messy data.</p></td></tr></tbody></table><br><h4>7. Storing Multiple Things</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Storing Multiple Things</p><p style='margin: 0'>This video explains the learning objectives of this section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Storing Multiple Things</p><p style='margin: 0'>This video explains how to store multiple things.</p></td></tr><tr><td style='padding: 15px;'><p>3. Introducing Python Lists</p><p style='margin: 0'>This video explains lists in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Adding Items to a List</p><p style='margin: 0'>This video explains how to add items to a list.</p></td></tr><tr><td style='padding: 15px;'><p>5. Indexing and Slicing Lists</p><p style='margin: 0'>This video explains indexing and slicing lists.</p></td></tr><tr><td style='padding: 15px;'><p>6. Deleting Items in a List</p><p style='margin: 0'>This video explains how to delete items in a list.</p></td></tr><tr><td style='padding: 15px;'><p>7. Tuples</p><p style='margin: 0'>This video explains tuples in Python.</p></td></tr><tr><td style='padding: 15px;'><p>8. Long Lines in Python</p><p style='margin: 0'>This video explains long lines in Python.</p></td></tr><tr><td style='padding: 15px;'><p>9. Dictionaries</p><p style='margin: 0'>This video explains dictionaries in Python.</p></td></tr><tr><td style='padding: 15px;'><p>10. List Functions - More Ways to Work with Lists</p><p style='margin: 0'>This video explains list functions.</p></td></tr><tr><td style='padding: 15px;'><p>11. Sets</p><p style='margin: 0'>This video explains sets in Python.</p></td></tr></tbody></table><br><h4>8. Processing Collections</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Processing Collections</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. A Simple 'for' Loop</p><p style='margin: 0'>This video explains a simple for loop.</p></td></tr><tr><td style='padding: 15px;'><p>3. More Complex 'for' loops - 'break', 'continue', and 'else'</p><p style='margin: 0'>This video explains more complex 'for' loops.</p></td></tr><tr><td style='padding: 15px;'><p>4. The 'range' Function - How to Create a List of Numbers</p><p style='margin: 0'>This video explains how to create a list of numbers.</p></td></tr><tr><td style='padding: 15px;'><p>5. The 'while' Loop - Do Something for a While</p><p style='margin: 0'>This video explains the while loop.</p></td></tr></tbody></table><br><h4>9. Robust Programs - Handling Errors</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Robust Programs - Handling Errors</p><p style='margin: 0'>This video explains error handling in Python.</p></td></tr><tr><td style='padding: 15px;'><p>3. Look Before You Leap</p><p style='margin: 0'>This video explains one way of making the code more robust, which is called 'look before you leap'.</p></td></tr><tr><td style='padding: 15px;'><p>4. The Try and Except Block</p><p style='margin: 0'>This video explains the try and except block in Python.</p></td></tr><tr><td style='padding: 15px;'><p>5. The Catch-All Block</p><p style='margin: 0'>This video explains the catch-all block.</p></td></tr><tr><td style='padding: 15px;'><p>6. Adding Resources to Replit</p><p style='margin: 0'>This video explains how to add resources to Replit.</p></td></tr><tr><td style='padding: 15px;'><p>7. The Finally Block</p><p style='margin: 0'>This video explains the finally block.</p></td></tr></tbody></table><br><h4>10. Saving the Results - Working with Files</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Saving the Results - Working with Files</p><p style='margin: 0'>This video explains the learning objectives of the course.</p></td></tr><tr><td style='padding: 15px;'><p>2. Adding Bad Data</p><p style='margin: 0'>This video explains adding bad data.</p></td></tr><tr><td style='padding: 15px;'><p>3. Saving the Results - Working with Files</p><p style='margin: 0'>This video explains saving the results and working with files.</p></td></tr><tr><td style='padding: 15px;'><p>4. Binary File Modes</p><p style='margin: 0'>This video explains binary file modes.</p></td></tr><tr><td style='padding: 15px;'><p>5. Text File Modes</p><p style='margin: 0'>This video explains text file modes.</p></td></tr><tr><td style='padding: 15px;'><p>6. The With Statement</p><p style='margin: 0'>This video explains the with statement.</p></td></tr></tbody></table><br><h4>11. Breaking Up Larger Programs, Part 1</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 1</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. About Replit.config</p><p style='margin: 0'>This video explains replit.config.</p></td></tr><tr><td style='padding: 15px;'><p>3. Functions</p><p style='margin: 0'>This video explains functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Function Parameters</p><p style='margin: 0'>This video explains function parameters.</p></td></tr><tr><td style='padding: 15px;'><p>5. Local Versus Global Variables</p><p style='margin: 0'>This video explains local versus global variables.</p></td></tr><tr><td style='padding: 15px;'><p>6. Positional and Keyword Parameters</p><p style='margin: 0'>This video explains positional and keyword parameters.</p></td></tr><tr><td style='padding: 15px;'><p>7. Return Statement</p><p style='margin: 0'>This video explains the return statement.</p></td></tr><tr><td style='padding: 15px;'><p>8. Working With JSON</p><p style='margin: 0'>This video explains working with JSON.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Comments and Clear Code</p><p style='margin: 0'>This video explains code comments in Python.</p></td></tr></tbody></table><br><h4>12. Summarising and Presenting the Results</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Summarising and Presenting the Results</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Summarising and Presenting the Results Part 1</p><p style='margin: 0'>This video explains how to summarise the results using statistics.</p></td></tr><tr><td style='padding: 15px;'><p>3. Cleaning the Data</p><p style='margin: 0'>This video explains cleaning the data in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Summarising and Presenting the Results Part 2</p><p style='margin: 0'>This video explains the code in which we will get a sum of the scores of a country.</p></td></tr><tr><td style='padding: 15px;'><p>5. More Numeric Functions - Min, Max, Sum</p><p style='margin: 0'>This video explains min, max, and sum functions in Python.</p></td></tr><tr><td style='padding: 15px;'><p>6. Formatted Strings, f-strings</p><p style='margin: 0'>This video explains formatted strings and f-strings in Python.</p></td></tr></tbody></table><br><h4>13. Breaking Up Larger Programs, Part 2</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Breaking Up Larger Programs, Part 2</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Splitting Code into Modules</p><p style='margin: 0'>This video explains splitting code into modules.</p></td></tr><tr><td style='padding: 15px;'><p>3. Namespaces</p><p style='margin: 0'>This video explains namespaces in Python.</p></td></tr><tr><td style='padding: 15px;'><p>4. Using Our Modules</p><p style='margin: 0'>This video explains how to use modules in Python.</p></td></tr></tbody></table><br><h4>14. Getting Set Up on a PC or MAC</h4><p></p><table width='100%'><tbody><tr><td style='padding: 15px;'><p>1. Learning Objectives - Getting Set Up on a PC or MAC</p><p style='margin: 0'>This video explains the learning objectives of the section.</p></td></tr><tr><td style='padding: 15px;'><p>2. Getting Set Up</p><p style='margin: 0'>This video explains how to set up Python on our systems.</p></td></tr><tr><td style='padding: 15px;'><p>3. Starting Python on Windows 10</p><p style='margin: 0'>This video explains how to start Python on Windows 10.</p></td></tr><tr><td style='padding: 15px;'><p>4. Starting a Terminal or Command Prompt on Windows</p><p style='margin: 0'>This video explains how to start a terminal or command prompt on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>5. Installing Python on Windows</p><p style='margin: 0'>This video explains the installation of Python on Windows.</p></td></tr><tr><td style='padding: 15px;'><p>6. Installing Python on MacOS</p><p style='margin: 0'>This video explains the installation on Python on MacOS.</p></td></tr><tr><td style='padding: 15px;'><p>7. Quick Python Test - Running Python</p><p style='margin: 0'>This video explains how to run a Python script.</p></td></tr><tr><td style='padding: 15px;'><p>8. Python Scripts and IDLE</p><p style='margin: 0'>This video explains Python scripts and IDE.</p></td></tr><tr><td style='padding: 15px;'><p>9. Code Editors and IDEs</p><p style='margin: 0'>This video explains code editors and IDEs.</p></td></tr><tr><td style='padding: 15px;'><p>10. Running Python Scripts</p><p style='margin: 0'>This video explains how to run Python scripts.</p></td></tr></tbody></table>

This course offers you the exact skills and principles you need to deliver a project using Python along with the tools you can use to create solid Python code. Master the language constructs, tools, and terminology with this carefully designed course for beginners.

Python Bootcamp in a Day - Python Programming for Beginners.

Network

Networking

Cisco

This course is an excellent resource to learn network programming using Python. With the help of practical examples, you will learn how to automate networks with Telnet, Secure Shell (SSH), Paramiko, Netmiko, and Network Automation and Programmability Abstraction Layer with Multivendor support (NAPALM).

Python Network Programming for Network Engineers (Python 3)

<p><strong>Introducing Coding using Python</strong></p>
<p>This course introduces your child to a very advanced, yet easy to learn programming languages &ndash; Python. It&rsquo;s safe to say that many apps we use today have been built using Python &ndash; Instagram Web, Netflix, YouTube, to name a few! This course teaches the fundamentals of coding, and creates a solid foundation to solve more complex real-life problems.</p>

Riva Learning

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Choose this course if your child is new to Python or has done a few hours of Python before. Or, they have a good understanding of block-based platforms like Scratch, and would like to start exploring text-based programming languages.

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