Redhill

<h3><b>REST and RESTCONF training course description</b></h3>
      <p> An introduction to REST and RESTCONF using
Python. The course progresses from how to use them
onto how they work and then looks at using them from
within Python all the time on network devices.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
     <li>Explain what REST and RESTCONF are.</li>
					<li>Use the REST API on network device.</li>
					<li>Use RESTCONF.</li>
                  </ul>
        <h5>
        <b>REST and RESTCONF 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>1 day
						</p>
              
							
              
              
						</ul>
					</div>
				</div>
      <h3><b>REST and RESTCONF training course contents</b></h3>
      <ul>
				<li>Using REST  </li><p>
Curl, Browser plugins, Postman, RESTClient,
Python. <br /><span>Hands on</span> Using the REST API on
network devices.
</p><li>What is REST?</li><p>
What is REST? Architecture, APIs, RESTful APIs,
APIs over HTTP/HTTPS, URIs, resources, HTTP
methods, GET, POST, PUT, DELETE. CRUD.
Comparison with other APIs. <br /><span>Hands on</span> REST
analysis with Wireshark.
</p><li>Rest conventions </li><p>
Passing parameters, return values, HTTP status,
JSON. XML. <br /><span>Hands on</span> Configuring REST on
network devices, changing format of responses,
POST requests, using parameters.
</p><li>Configuring network devices with REST </li><p>
Invoking multiple RPCs. <br /><span>Hands on</span> Device
configuration with REST.
</p><li>The request library </li><p>
RESTFUL APIs in Python, the request library,
Installation, example to retrieve the interface
configuration. <br /><span>Hands on</span> Using the Python
requests library on network devices.
</p><li>RESTCONF </li><p>
What is RESTCONF? YANG and NETCONF,
relationship with REST, RESTCONF URIs, A
RESTCONF example with ietf-interfaces,
RESTCONF responses. PATCH. <br /><span>Hands on</span>
Using RESTCONF to update a network device
configuration.
</p>
      </ul>

Systems & Network Training

Network & Security

Network Engineer

REST and RESTCONF

General Admission

<h3><b>Network automation training course description</b></h3> 
				<p> This course concentrates on the technical side of tools
and languages for network DevOps rather than the soft
skills. These tools include Python, Ansible, Git and
NAPALM
By the end of the course delegates should be able to
recognise the tools that they can use to automate their
networks and be able to use the knowledge gained to
feel confident approaching network automation.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
          <li>Describe network DevOps.</li>
					<li>Choose network automation tools.</li>
                    <li>Explain the role of various network automation
technologies including:<br />

                    Python<br />
                   Ansible<br />
                    Git<br />
											NAPALM</li>
                    </ul>
       
        <h5>
        <b>Network automation training course details</b> </h5>
				<div>
					<div>
						<ul>
							<li><b> Who will benefit:</b> </li>
							
              <p>Those wishing to learn about the tools of network
automation.</p>
              
							<li><b>Prerequisites:</b></li>
							
              <p>Introduction to data communications.</p>
              
							<li><b>Duration</b></li>
							
              <p>1 day
						</p>
              
							
              
              
						</ul>
					</div>
				</div>
      <h3><b>Network automation training course contents</b></h3>
      <ul>
				<li>What is DevOps and network automation</li><p>
Programming and automating networks, networks
and clouds, AWS, OpenStack, SDN, DevOps for
network operations. Unit testing. Hype vs reality.
Benefits and features.
				</p><li>Network monitoring and troubleshooting</li><p>
Traditional methods, SNMP. Netflow and xflow.
Traditional automation. Streaming telemetry.
Event driven automation. gRPC, Protocol buffers.
</p><li>Configuration management</li><p>
Catch 22 and initial configuration. ZTP, POAP.
Traditional automation. TFTP. Ansible vs the rest
(chef, salt, puppet). Jinja2 and templating. How
ansible works.
</p><li>Network programmability</li><p>
Programming languages. Linux, shell scripting.
Python vs the rest. Off box vs on box automation.
</p><li>Python network libraries</li><p>
Sockets pysnmp, ncclient, paramiko, netmiko,
pyez, NAPALM.
</p><li>APIs</li><p>
Proprietary APIs, CLI, NETCONF, RETCONF.
YANG, XML, YAML, JSON.
</p><li>Other tools</li><p>
Git, GitHub, Jenkins, JIRA and others.

</p>
      </ul>

Network automation demystified

<h4>Overview</h4>
						<hr />
						<div></div>
							<p>
							</p><p>Data and visual analytics are emerging fields concerned with analysing, modelling, and visualizing complex high-dimensional data. It can be analysed and visualised with many languages like Python, R Programming and more. This course will help to attain the skills and give in-depth knowledge to the participant's enhanced way of modelling, analysing and visualizing techniques. </p>

<p>The course will highlight practical challenges including composite real-world data and will also comprise several practical studies</p>
<p>
							
							</p><div>
						
					</div>

GBA Corporate

Data Analysis and Visualisation

Online

On Site

<div>
</div>
<section>
<div>
<h2>About this training course</h2>
<p><strong>Business Impact:</strong> The main aim is to provide insight and understanding of data analytics and machine learning principles through applications. Field data is used to explain data-analysis workflows. Using easy to follow solution scripts, the participants will assess and extract value from the data sets. Hands-on solution approach will give them confidence to try out applicable techniques on data from their field assets.</p>
<p>Data analysis means cleaning, inspecting, transforming, and modeling data with the goal of discovering new, useful information and supporting decision-making. In this hands-on 2-day training course, the participants learn some data analysis and data science techniques and workflows applied to petroleum production (specifically artificial lift) while reviewing code and practicing. The focus is on developing data-driven models while keeping our feet closer to the underlying oil and gas production principles.</p>
<p><strong>Unique Features:</strong></p>
<ul>
<li><strong><em>Eight business use cases</em></strong> covering their business impact, code walkthroughs for most all and solution approach.</li>
<li><strong><em>Industry data sets</em></strong> for participants to practice on and take home.</li>
<li>No software or complicated Python frameworks required.</li>
</ul>
</div>
</section>
<section>
<div id="accordion">
<div>
<div>

Training Objectives 

</div>
<div id="collapseOne">
<div>
<p>After the completion of this training course, participants will be able to:</p>
<ul>
<li>Understand digital oil field transformation and its impact on business</li>
<li>Examine machine learning methods</li>
<li>Review workflows and code implementations</li>
<li>After completing the course, participants will have a set of tools and some pathways to model and analyze their data in the cloud, find trends, and develop data-driven models</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Target Audience 

</div>
<div id="collapseTwo">
<div>
<p>This training course is suitable and will greatly benefit the following specific groups:</p>
<ul>
<li>Artificial lift, production and facilities engineers and students to enhance their knowledge base, increase technology awareness, and improve the facility with different data analysis techniques applied on large data sets</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Course Level 

</div>
<div id="collapsecl">
<div>
<ul>
<li>Intermediate</li>
<li>Advanced</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Training Methods 

</div>
<div id="collapseThree">
<div>
<p><span>The course discusses several business use-cases that are amenable to data-driven workflows. For each use case, the instructor will show the solution using a data analysis technique with Python code deployed in the Google cloud. Trainees will solve a problem and tweak their solution.</span></p>
<p><em><span>Course Duration: 2 days in total (14 hours).</span></em></p>
<p><strong><span>Training Schedule</span></strong></p>
<p><span>0830 - Registration </span><span>0900 - Start of training </span><span>1030 - Morning Break </span><span>1045 - Training recommences </span><span>1230 - Lunch Break </span><span>1330 - Training recommences </span><span>1515 - Evening break </span><span>1530 - Training recommences </span><span>1700 - End of Training</span></p>
<p><span>The maximum number of participants allowed for this training course is 20.</span></p>
<p>This course is also available through our Virtual Instructor Led Training (VILT) format.</p>
<p><strong>Prerequisites:</strong></p>
<ul>
<li>Understanding of petroleum production concepts</li>
<li>Knowledge of Python is not a must but preferred to get the full benefit.</li>
<li>The training will use the Google Collaboratory environment available in Google-Cloud for hands-on exercises</li>
<li>Trainees will need to bring a computer with a Google Chrome browser and a Google email account (available for free)</li>
</ul>
</div>
</div>
</div>
<div>
<div>

Trainer

</div>
<div id="collapseFive">
<div>
<p>Your expert course leader has over 35 years' work-experience in multiphase flow, artificial lift, real-time production optimization and software development/management. His current work is focused on a variety of use cases like failure prediction, virtual flow rate determination, wellhead integrity surveillance, corrosion, equipment maintenance, DTS/DAS interpretation. He has worked for national oil companies, majors, independents, and service providers globally. He has multiple patents and has delivered a multitude of industry presentations. Twice selected as an SPE distinguished lecturer, he also volunteers on SPE committees. He holds a Bachelor's and Master's in chemical engineering from the Gujarat University and IIT-Kanpur, India; and a Ph.D. in Petroleum Engineering from the University of Tulsa, USA.</p>
<p><strong>Highlighted Work Experience: </strong></p>
<ul>
<li>At Weatherford, consulted with clients as well as directed teams on digital oilfield solutions including LOWIS - a solution that was underneath the production operations of Chevron and Occidental Petroleum across the globe.</li>
<li>Worked with and consulted on equipment's like field controllers, VSDs, downhole permanent gauges, multiphase flow meters, fibre optics-based measurements.</li>
<li>Shepherded an enterprise-class solution that is being deployed at a major oil and gas producer for production management including artificial lift optimization using real time data and deep-learning data analytics.</li>
<li>Developed a workshop on digital oilfield approaches for production engineers.</li>
</ul>
<p><strong>Patents:</strong></p>
<ul>
<li>Principal inventor: 'Smarter Slug Flow Conditioning and Control'</li>
<li>Co-inventor: 'Technique for Production Enhancement with Downhole Monitoring of Artificially Lifted Wells'</li>
<li>Co-inventor: 'Wellbore real-time monitoring and analysis of fracture contribution'</li>
</ul>
<p><strong>Worldwide Experience in Training / Seminar / Workshop Deliveries:</strong></p>
<ul>
<li>Besides delivering several SPE webinars, ALRDC and SPE trainings globally, he has taught artificial lift at Texas Tech, Missouri S&amp;T, Louisiana State, U of Southern California, and U of Houston.</li>
<li>He has conducted seminars, bespoke trainings / workshops globally for practicing professionals:
<ul>
<li><u>Companies:</u> Basra Oil Company, ConocoPhillips, Chevron, EcoPetrol, Equinor, KOC, ONGC, LukOil, PDO, PDVSA, PEMEX, Petronas, Repsol, , Saudi Aramco, Shell, Sonatrech, QP, Tatneft, YPF, and others.</li>
<li><u>Countries:</u> USA, Algeria, Argentina, Bahrain, Brazil, Canada, China, Croatia, Congo, Ghana, India, Indonesia, Iraq, Kazakhstan, Kenya, Kuwait, Libya, Malaysia, Oman, Mexico, Norway, Qatar, Romania, Russia, Serbia, Saudi Arabia, S Korea, Tanzania, Thailand, Tunisia, Turkmenistan, UAE, Ukraine, Uzbekistan, Venezuela.</li>
<li>Virtual training provided for PetroEdge, ALRDC, School of Mines, Repsol, UEP-Pakistan, and others since pandemic.</li>
</ul>
</li>
</ul>
</div>
</div>
</div>
<div>
<div>

POST TRAINING COACHING SUPPORT (OPTIONAL)

</div>
<div id="collapseCS">
<div>
<p>To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster.<br />
Request for further information post training support and fees applicable</p>
</div>
</div>
</div>
<div>
<div>

Accreditions And Affliations

</div>
<div id="collapseSeven">
<div>
               </div>
</div>
</div>
</div>
</section>

EnergyEdge - Training for a Sustainable Energy Future

Renewable Energy

Oil & Gas

Data Analytics Workflows for Artificial Lift, Production and Facility Engineers

Team of 10, pp

Normal Fee, pp

Loughborough

<div>
		

		<div>
			
			<p>This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.</p>
			<div><i></i> 3 Days</div>
			<div><i></i>  £350.00 incl. VAT</div>
			
			
		</div>
	</div>

	

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	</div>

	

    <div>

		
		 
		

		<div></div>

		<div>
			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
		</div>

		<div>
			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
		</div>
	</div>
	<div></div>
	
		
        <div>
			
		</div>
				

	
		<h3>Description</h3>
		<p></p><p>The stakes for software security are very high, and yet many development teams deal with software security only after the code has been developed and the software is being prepared for delivery. As with any aspect of software quality, to ensure successful implementation, security and privacy issues should be managed throughout the entire software development lifecycle. </p>
<p>This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects. You will learn general strategies for dealing with security defects and misconfiguration, how to design software to deal with the human element in security, and how to incorporate security into all phases of development. </p>
<h3>Course Objectives:</h3>
<p>In this course, you will employ best practices in software development to develop secure software. You will:</p>
<ul>
<li>Identify the need for security in your software projects.</li>
<li>Eliminate vulnerabilities within software.</li>
<li>Use a Security by Design approach to design a secure architecture for your software.</li>
<li>Implement common protections to protect users and data.</li>
<li>Apply various testing methods to find and correct security defects in your software.</li>
<li>Maintain deployed software to ensure ongoing security.</li>
</ul>
<p><b><i>This course includes hands-on activities for each topic area. The goal of these activities is to demonstrate concepts utilizing two universal languages Python and JavaScript. Developers who use alternate languages will be able to apply the principles from the activities to any coding languages.</i></b></p>
<p><b><i>Hands-on exercises are designed to keep the typing of code to a bare minimum. We provide students with all of the code they need to complete activities. The activities do not require a 'deep dive' into code to understand the principles being covered.</i></b></p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for software developers, testers, and architects who design and develop software in various programming languages and platforms, including desktop, web, cloud, and mobile, and who want to improve their ability to deliver software that is of high quality, particularly regarding security and privacy.</p>
<p>This course is also designed for students who are seeking the CertNexus Cyber Secure Coder certification.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>This course presents secure programming concepts that apply to many different types of software development projects. Although this course uses Python®, HTML, and JavaScript® to demonstrate various programming concepts, you do not need to have experience in these languages to benefit from this course. However, you should have some programming experience, whether it be developing desktop, mobile, web, or cloud applications. </p>
<div>
<h3>Course-specific Technical Requirements</h3>
</div>
<h4>Hardware</h4>
<p>For this course, you will need one computer for each student and one for the instructor. Each computer will need the following minimum hardware configurations:</p>
<ul>
<li>1 GHz or faster 32-bit (x86) or 64-bit (x64) processor</li>
<li>2 gigabytes (GB) RAM (32-bit or 64-bit)</li>
<li>20 GB available hard disk space (32-bit or 64-bit)</li>
<li>Keyboard and mouse (or other pointing device)</li>
<li>1,024 x 768 resolution monitor recommended</li>
<li>Projection system to display the instructor's computer screen</li>
<li>Local area network and Internet connection</li>
</ul>
<h4>Software</h4>
<ul>
<li>Windows® 10/8.1/8/7/Vista (64-bit). This course was successfully keyed on Windows 10. Some activity steps may not key exactly as written if students key on a different version of Windows.</li>
<li>Python version 3.8.1 (python-3.8.1.amd64.msi, provided with the course data files).</li>
<li>PyCharm Community Edition version 2019.3.3 (pycharm-community-2019.3.3.exe, provided with the course data files). Python is distributed under the Python Software Foundation License (PSFL). PyCharm Community Edition is distributed under the Apache® License 2.0.</li>
</ul>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4>Lesson 1: Identifying the Need for Security in Your Software Projects</h4>
<p>Topic A: Identify Security Requirements and Expectations <br />Topic B: Identify Factors That Undermine Software Security <br />Topic C: Find Vulnerabilities in Your Software<br />Topic D: Gather Intelligence on Vulnerabilities and Exploits</p>
<h4>Lesson 2: Handling Vulnerabilities</h4>
<p>Topic A: Handle Vulnerabilities Due to Software Defects and Misconfiguration <br />Topic B: Handle Vulnerabilities Due to Human Factors<br />Topic C: Handle Vulnerabilities Due to Process Shortcomings</p>
<h4>Lesson 3: Designing for Security</h4>
<p>Topic A: Apply General Principles for Secure Design <br />Topic B: Design Software to Counter Specific Threats</p>
<h4>Lesson 4: Developing Secure Code</h4>
<p>Topic A: Follow Best Practices for Secure Coding <br />Topic B: Prevent Platform Vulnerabilities<br />Topic C: Prevent Privacy Vulnerabilities</p>
<h4>Lesson 5: Implementing Common Protections</h4>
<p>Topic A: Limit Access Using Login and User Roles <br />Topic B: Protect Data in Transit and At Rest <br />Topic C: Implement Error Handling and Logging <br />Topic D: Protect Sensitive Data and Functions <br />Topic E: Protect Database Access</p>
<h4>Lesson 6: Testing Software Security</h4>
<p>Topic A: Perform Security Testing<br />Topic B: Analyze Code to find Security Problems<br />Topic C: Use Automated Testing Tools to Find Security Problems</p>
<h4>Lesson 7: Maintaining Security in Deployed Software</h4>
<p>Topic A: Monitor and Log Applications to Support Security <br />Topic B: Maintain Security after Deployment</p>
<p></p>

Mpi Learning - Professional Learning And Development Provider

This course presents an approach for dealing with security and privacy throughout the entire software development lifecycle. You will learn about vulnerabilities that undermine security, and how to identify and remediate them in your own projects.

Cyber Secure Coder

<h3><b>Regular expressions training course description</b></h3>
      <p>Regular expressions are an extremely powerful tool for
manipulating text and data. They are now standard
features in a wide range of languages and popular
tools, including Python and MySQL.
Regular expressions allow you to code complex and
subtle text processing that you never imagined could be
automated. Once you've mastered regular expressions,
they'll become an invaluable part of your toolkit. You
				will wonder how you ever got by without them.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
	   <li>Use Regular Expressions.</li>
																								<li>Troubleshoot Regular Expressions.</li>
                    <li>Compare RE features among different versions.</li>
                    <li>Explain how the regular expression engine
works.</li>
 																							<li>Optimize REs.</li>
																								<li>Match what you want, not what you don't want.</li></ul>
        <h5>
        <b>Regular expressions training course details</b></h5>
				<div>
					<div>
						<ul>
							<li><b> Who will benefit:</b> </li>
							
              <p>Anyone looking to use regular expressions.
							</p>
              
							<li><b>Prerequisites:</b></li>
							
              <p> None.
							</p>
              
							<li><b>Duration</b></li>
							
              <p>1 day
						</p>
              
							
             
              
						</ul>
					</div>
				</div>
       <h3><b>Regular expressions training course contents</b></h3>
     <ul>
				<li>Introduction to Regular Expressions </li><p>
Solving real problems, REs as a language, the filename analogy, language analogy, RE frame of mind, searching text files: egrep, egrep metacharacters, start and end of the line, character classes, matching any character with dot, alternation, ignoring differences in capitalization, word boundaries, optional items, other quantifiers: repetition, parentheses and backreferences, the great escape, expanding the foundation, linguistic diversification, the goal of a RE, more examples, RE nomenclature, Improving on the status quo.

</p><li>Extended introductory examples </li><p>
A short introduction to Perl, matching text with regular expressions, toward a more real-world example, side effects of a successful match, Intertwined regular expression, intermission, modifying text with regular expressions, example: form letter, example: prettifying a stock price, automated editing, a small mail utility, adding commas to a number with lookaround, text-to-HTML conversion, that doubled-word thing.

</p><li>Regular expression features and flavours </li><p>
The regex landscape, origins of REs, care and handling of REs, Integrated handling, procedural and object-oriented handling, search-and-replace example. strings character encodings and modes, strings as REs, character-encoding issues, unicode, regex modes and match modes, common metacharacters and features, character representations, character classes and class-like constructs, anchors and other 'zero-width assertions', comments and mode modifiers, grouping capturing conditionals and control.

</p><li>The mechanics of expression processing </li><p>
Two kinds of engines, new standards, regex engine types, from the department of redundancy department, testing the engine type, match basics, about the examples, rule 1: the match that begins earliest wins, engine pieces and parts, rule 2: the standard quantifiers are greedy, regex-directed versus text-directed, NFA engine: regex-directed, DFA engine: text-directed, first thoughts: NFA and DFA in comparison, backtracking, two important points on backtracking, saved states, backtracking and greediness, more about greediness and backtracking, problems of greediness, multi-character 'quotes', lazy quantifiers, greediness and laziness, laziness and backtracking, possessive quantifiers and atomic grouping, possessive quantifiers ?, +, *+, ++ and {m,n}+, the backtracking of lookaround, is alternation greedy? taking advantage of ordered alternation, NFA DFA and posix, the longest-leftmost', posix and the longest-leftmost rule, speed and efficiency.

</p><li>Practical regex techniques </li><p>
Continuation lines, matching an IP address, working with filenames, matching balanced sets of parentheses, watching out for unwanted matches, matching delimited text, knowing your data and making assumptions, stripping leading and trailing whitespace, matching and HTML tag, matching an HTML link, examining an HTTP URL, validating a hostname, plucking a hostname, plucking a URL, parsing CSV files.

</p><li>Crafting an efficient expression </li><p>
Efficiency vs. correctness, localizing greediness, global view of backtracking, more work for POSIX NFA, work required during a non-match, being more specific, alternation can be expensive, benchmarking, know what you re measuring, benchmarking with Python, common optimisations, the mechanics of regex application, pre-application optimizations, optimizations with the transmission, optimization of the regex itself, techniques for faster expressions, common sense techniques, expose literal text, expose anchors, lazy versus greedy: be specific, split into multiple REs, mimic initial-character discrimination, use atomic grouping and possessive quantifiers, lead the engine to a match, unrolling the loop, observations, using atomic grouping and possessive quantifiers, short unrolling examples, unrolling C comments, the free flowing regex, a helping hand to guide the match, a well-guided regex is a fast regex.</p>
			
      </ul>

Regular expressions for engineers

<h3><b>Ansible training course description</b></h3>
      <p> The course focusses on the use of ansible for network
devices instead of its usual server use case. The
course progresses from the basics of ansible and
playbooks onto using network specific modules
including NAPALM. The use Jinja2 templating with
ansible is also studied. Hands on sessions with ansible
configuring routers and switches follow all major
sections.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
  <li>Automate tasks with ansible.</li>
					<li>Write ansible playbooks.</li>
					<li>Configure network devices with ansible.</li>
     	<li>Troubleshoot network devices with ansible.</li>
					<li>Use ansible network modules.</li>
     <li>Use jinja2 templates with ansible.</li>
                  </ul>
        <h5>
        <b>Ansible 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>TCP/IP Foundation</p>
              
							<li><b>Duration</b></li>
							
              <p>2 days
						</p>
              
							
              
              
						</ul>
					</div>
				</div>
      <h3><b>Ansible training course contents</b></h3>
      <ul>
				<li>What is ansible? </li><p>
The language, the engine, the framework. Uses of ansible, orchestration. <br /><span>Hands on</span> Installing ansible, enabling SSH on network devices.

</p><li>Ansible architecture </li><p>
How ansible 'normally' works, Agentless, SSH, ansible and Python, modules, how ansible work on network devices, Configuration management, inventories, playbooks, modules, ansible.cfg.
<br /><span>Hands on</span> Getting started, running ad hoc commands.

</p><li>Playbooks </li><p>
ansible-playbook, users, YAML, plays, tasks, modules. ansible-vault.
<br /><span>Hands on</span> Running playbooks.

</p><li>More playbooks </li><p>
Handlers, variables, environmental variables, playbook variables, inventory variables, variable scope and precedence, accessing variables, facts, ansible vault. Conditionals, wait_for.
<br /><span>Hands on</span> Using variables and conditions in playbooks.

</p><li>Inventories </li><p>
	/etc/ansible/hosts, inventory variables, static inventories, dynamic inventories.
<br /><span>Hands on</span> Inventories and variables.

</p><li>Ansible network modules </li><p>
Built in modules, custom modules, return values. ansible-doc -l. connection: local, Cisco modules, Juniper module, 
<br /><span>Hands on</span> Using modules for your network devices.

</p><li>Ansible templatings  </li><p>
	The template module, the assemble module, jinja2 templates, for, if else.
<br /><span>Hands on</span> Configuring network devices from templates.

</p><li>Roles and includes </li><p>
Dynamic includes, Handler includes, playbook includes. Roles, role parts: handlers, files, templates, cross platform roles, ansible galaxy.
<br /><span>Hands on</span> includes example, building roles.

</p><li>Ansible and NAPALM  </li><p>
	Installation, napalm-ansible, NAPALM modules: napalm_diff-yang, napalm_get_facts, napalm_install_config, napalm_parse_yang, napalm_ping, napalm_translate_yang, napalm_validate.
<br /><span>Hands on</span> Using NAPALM modules in ansible.</p>
      </ul>

Ansible for network engineers

<h3><b>Definitive Salt training course description</b></h3>
      <p>Salt is a remote execution framework and configuration
management system. This course covers Salt from the
basics. After a quick first taste the course moves onto
execution modules, salt states, minion and master data,
jinja, Salt extensions and then topology and
configuration options. Hands on sessions are used to
reinforce the theory rather than teach specific
manufacturer equipment.</p>
        
				<h5><b>What will you learn</b></h5>
				<ul>
				 
		<li>Install and use Salt.</li>
																					<li>Describe the architecture of Salt.</li>
                     <li>Manage configurations with Salt.</li>
																					<li>Extend Salt.</li>
                  </ul>
        <h5>
        <b>Definitive Salt training course details</b> </h5>
				<div>
					<div>
						<ul>
							<li><b> Who will benefit:</b> </li>
							
              <p>Anyone working with Salt.</p>
              
							<li><b>Prerequisites:</b></li>
							
							<p>Linux fundamentals.</p>
              
							<li><b>Duration</b></li>
							
              <p>2 days
						</p>
              
							
              
              
						</ul>
					</div>
				</div>
      <h3><b>Definitive Salt training course contents</b></h3>
      <ul>
				<li>Introduction </li><p>
What is Salt? High- level architecture, Some quick examples, system management, configuration management, A brief history, Topology options, Extending Salt.

</p><li>Quick start: First taste of Salt </li><p>
Single-master setup, from packages, bootstrap scripts, Starting up, Basic commands, salt: the main workhorse, salt-key: key management, salt-call: execution on the minion, salt-run: co-ordination of jobs on the master, summary of commands, Key management, viewing keys, accepting keys, rejecting keys, key files, Minion targeting, minion ID, list (-L), glob, regular expressions (-E), grains (-G), compound (-C), targeting summary, Additional remote execution details, Conclusion.

</p><li>Execution modules: The functional foundation </li><p>
sys: information and documentation about modules, sys.doc basic documentation, sys.list_modules, sys.list_functions: simple listings, cmd: execute via shell, cmd.run: run any command, pkg: manage packages, virtual modules, pkg.lists_pkgs: list all installed packages, pkg.available version: see what version will be installed, pkg.install: install packages, user: manage users, user.add: add users, user.list_users, user info: get user info, saltutil: access various Salt utilities, Summary.

</p><li>Configuration management: Salt states </li><p>
Salt files overview, SLS example: adding a user, working with the multi-layered state system, Highstate and the top file, the top file, State ordering, require: depend on another state, watch: run based on other changes, odds and ends, Summary.

</p><li>Minion data / master data </li><p>
Grains are minion data, performing basic grain operations, setting grains, targeting with grains in the top file, Pillars are data from the master, querying pillar data, querying other sources with external pillars, Renderers give data options.

</p><li>Extending Salt: part I </li><p>
Introduction to Jinja, Jinja basics, Templating with Jinja, filtering by grains, Custom execution module, Custom state modules, Custom grains, External pillars, Summary.

</p><li>More on the matter </li><p>
Runners, manage minions, manage jobs, The orchestrate runner, The event system, The reactor system, Summary.

</p><li>Extending Salt: part II </li><p>
Python client API, reading configuration data on a master and minion, using the master client (localclient) API, Using the caller client API, Custom runners, writing a custom runner, using the runnerclient API, Summary.

</p><li>Topology and configuration options </li><p>
Master configuration, directories and files, logging, access control, files server options, Topology variations, masterless minions, peer systems, syndication masters, multiple masters.

</p><li>Brief introduction to salt-cloud </li><p>
Overview, Setup AWS and salt-cloud, installing salt-cloud, cloud providers, cloud profiles, cloud maps, Introspection via salt cloud, Creating infrastructure, More information.

</p><li>Using vagrant to run Salt examples </li><p>
YAML.</p>
      </ul>

Definitive Salt for engineers

<div>
		

		<div>
			
			<p>This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.</p>
			<div><i></i> 5 Days - 1 Exam</div>
			<div><i></i>  £595.00 incl. VAT</div>
			
			
		</div>
	</div>

	

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		<div></div>

		<div>
			<p>Want to run this event in-house?  Enquire about running this event in-house </p>
			
		</div>

		<div>
			<p>Interested in attending? Have a suggestion about running this event near you?<br />Register your interest now</p>
			
		</div>
	</div>
	<div></div>
	
		
        <div>
			
		</div>
				

	
		<h3>Description</h3>
		<p></p><p>For a business to thrive in our data-driven world, it must treat data as one of its most important assets. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations. This calls for a robust workforce of professionals who can analyze, understand, manipulate, and present data within an effective and repeatable process framework. In other words, the business world needs data science practitioners. This course will enable you to bring value to the business by putting data science concepts into practice. This course includes hands-on activities for each topic area.</p>
<h3>Course Objectives: </h3>
<p>In this course, you will implement data science techniques in order to address business issues. You will:</p>
<p>• Use data science principles to address business issues. <br />• Apply the extract, transform, and load (ETL) process to prepare datasets. <br />• Use multiple techniques to analyze data and extract valuable insights. <br />• Design a machine learning approach to address business issues. <br />• Train, tune, and evaluate classification models. <br />• Train, tune, and evaluate regression and forecasting models. <br />• Train, tune, and evaluate clustering models. <br />• Finalize a data science project by presenting models to an audience, putting models into production, and monitoring model performance.</p>
<p></p>
	
		<h3>Target Student</h3>
		<p></p><p>This course is designed for business professionals who leverage data to address business issues. The typical student in this course will have several years of experience with computing technology, including some aptitude in computer programming.  However, there is not necessarily a single organizational role that this course targets. A prospective student might be a programmer looking to expand their knowledge of how to guide business decisions by collecting, wrangling, analyzing, and manipulating data through code; or a data analyst with a background in applied math and statistics who wants to take their skills to the next level; or any number of other data-driven situations. </p>
<p>Ultimately, the target student is someone who wants to learn how to more effectively extract insights from their work and leverage that insight in addressing business issues, thereby bringing greater value to the business.  This course is also designed to assist students in preparing for the Certified Data Science Practitioner certification.</p>
<p></p>
	
		<h3>Prerequisites</h3>
		<p></p><p>To ensure your success in this course, you should have at least a high-level understanding of fundamental data science concepts, including, but not limited to: types of data, data science roles, the overall data science lifecycle, and the benefits and challenges of data science.</p>
<p>You should have also have experience with high-level programming languages like Python. Being comfortable using fundamental Python data science libraries like NumPy and pandas is highly recommended.</p>
<p>In addition to programming, you should also have experience working with databases, including querying languages like SQL. </p>
<p></p>
	
		<h3>Modules/Lessons</h3>
		<p></p><h4>Lesson 1: Addressing Business Issues with Data Science</h4>
<div>
<p>Topic A: Initiate a Data Science Project<br />Topic B: Formulate a Data Science Problem</p>
<h4>Lesson 2: Extracting, Transforming, and Loading Data</h4>
<p>Topic A: Extract Data <br />Topic B: Transform Data <br />Topic C: Load Data</p>
<h4>Lesson 3: Analyzing Data</h4>
<p>Topic A: Examine Data<br />Topic B: Explore the Underlying Distribution of Data <br />Topic C: Use Visualizations to Analyze Data<br />Topic D: Preprocess Data</p>
<h4>Lesson 4: Designing a Machine Learning Approach</h4>
<p>Topic A: Identify Machine Learning Concepts<br />Topic B: Test a Hypothesis</p>
</div>
<h4>Lesson 5: Developing Classification Models</h4>
<p>Topic A: Train and Tune Classification Models <br />Topic B: Evaluate Classification Models</p>
<h4>Lesson 6: Developing Regression Models</h4>
<p>Topic A: Train and Tune Regression Models <br />Topic B: Evaluate Regression Models</p>
<h4>Lesson 7: Developing Clustering Models</h4>
<p>Topic A: Train and Tune Clustering Models <br />Topic B: Evaluate Clustering Models</p>
<h4>Lesson 8: Finalizing a Data Science Project</h4>
<p>Topic A: Communicate Results to Stakeholders <br />Topic B: Demonstrate Models in a Web App <br />Topic C: Implement and Test Production Pipelines</p>
<p></p>

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Certified Data Science Practitioner

Bristol

<p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;"><strong fr-original-style="" style="font-weight: 700; box-sizing: border-box;">For pupils aged 9 - 16 | Delivered in UK Schools by Real World App and Games Developers</strong></p><p fr-original-style="" style="color: var(--text); font-size: var(--font-size); box-sizing: border-box;">Our micro:bit Workshop teaches your class about the micro:bit, making some apps and games with them during the workshop (we bring our own micro:bits too if your school doesn&#39;t yet have any!). We&rsquo;ll introduce them to MakeCode, the coding language that the micro:bit uses, and teach them the fundamentals of coding before we work on some really fun projects! For older students, we can even use Python with the micro:bit!</p>

Code Created (Coding Workshops for Schools)

BBC micro:bit Coding Workshop

<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>

Nexus Human

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.
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 Python Certification - IT Program today and start your journey to becoming a successful Python Programmer!
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 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.
Extensive Job Opportunities: We have established partnerships with numerous companies actively seeking Certified Python Programmers. 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.
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.
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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

Programming Fundamentals

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 Science

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>

Packt

Python

Programming

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

Programming Languages

Computing

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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