39 Educators providing Python courses in London

This Python BootCamp is Instructor-led, Practical. In the12-week Python course, learn start to in-depth, leading to a good Python career. -------------------------------------------------------------------------------- PYTHON BOOTCAMP: This 12-week Python Boot Camp is a practical, instructor-lead program, covering Python from start to in-depth. You will be fully fluent and confident as a Python programmer. If you have more questions goto https://pcworkshopslondon.co.uk/contact.html  [http://pcworkshopslondon.co.uk/contact.html], Or contact us on training@pcworkshopslondon.co.uk [https://pcworkshopslondon.co.uk/] Customise dates, course outline, arrange installments [https://pcworkshopslondon.co.uk/contact.htm] This course will give you enough practical experience and practical projects to code, to give you full confidence to enter into the coding profession.    Duration: 3 months: * 1 Python class per week, * Plus pratical work, * Plus personal trainer-mentor for 1-1 training, * Plus e-learning materials. Final project : Practical to upload to GitHub and show-case Date and times, choose: * Fridays in London or Online , 10am - 5pm, * or Saturdays in London or Online , 12noon-6pm, * or negotiate your date Study level: Start from beginners level to in-depth, ready to work professionally. Virtual attendance:  online instructor-led  Download: Anaconda.com Pre-requisites: General computer literacy. Oracle Qualification: PCWorkshops Python Programmer Certificate Payments:  You may apply to pay in installments for this Python Training course COURSE OUTLINE Week 1 - 4: Essentials 1. Python Coding Basics 2. Object Oriented programming: Python Object Orientated programming (OOP) 3. UX Principles: UX Principles and applying it on Front-ends with TKinter 4. Specialised topics: Dates, Localization, Strings, Maths Operation , Random Number, Lambdas Week 5 - 10 : All about data 1. Python Data Structures: Lists, Tuples, Sets, Exceptions, I/O Fundamentals , Reading and Writing file 2. Database: Database principles and SQL. Database Project: Python database connections and creating a database driven project 3. Data Analytics: Numpy. Pandas for data analytics and data queries. 4. Data Analytics: Pandas data cleaning and restructuring, interacticting with Excel, Csv, Json,etc. 5. Data visualisation: MatPlotLib 6. Prediction: Machine Learning Basics Week 11 and 12: The final touch 1. Python Concurrency and Multi-threading: Threads vs. Processes, Threading Module, Threading Event, Stop a Thread, Daemon Threads, Thread-safe Queue, Thread Pools, Locks 2. Python Unit Testing 3. Optional : Replace Week 11 or 12 with Scraping using Python, ot Tkinter Front-ends INCLUDED: * PCWorkshops Python Course Certificate on completion. * Python Course notes. * Practical Course exercises, Code Examples, Online Materials. * After the course, continuous assistance with practical and preparation for exams * Max group size on this is 4. * Portfolio: Post your Python project online. * Exam preparation and interview questions MORE ABOUT THE ONLINE CLASSROOM *  Attend from your internet connection *  Instructor-led, get instant answers to your questions *  Fully interactive *  Work clearly explained with demonstrations and examples *  Practical exercises to be tried out by delegate WHAT YOU WILL GAIN: * Skills & knowledge: Python coding knowledge and understanding with good practical application   * Certification: Internal PCWorkshops Python certificate * Portfolio: You will have an online portfolio of Python projects  * Experience: Our comprehensive practical makes you job ready -------------------------------------------------------------------------------- REFUND POLICY No Refunds

This Python Machine Learning online instructor led course is an excellent introduction to popular machine learning algorithms. -------------------------------------------------------------------------------- Python Machine Learning 2-day Course Prerequisites: Basic knowledge of Python coding is a pre-requisite. Who Should Attend? This course is an overview of machine learning and machine learning algorithms in Python SciKitLearn. Practical: * We cover the below listed algorithms, which is only a small collection of what is available. However, it will give you a good understanding, to plan your Machine Learning project * We create, experiment and run machine learning sample code to implement a short selected but representative list of available the algorithms.  Course Outline: Supervised Machine Learning: * Classification Algorithms: Naive Bayes, Decision Tree, Logistic Regression, K-Nearest Neighbors, Support Vector Machine * Regression Algorithms: Linear, Polynomial Unsupervised Machine Learning: * Clustering Algorithms: K-means clustering, Hierarchical Clustering * Dimension Reduction Algorithms: Principal Component Analysis Latent Dirichlet allocation (LDA) * Association Machine Learning Algorithms: Apriori, Euclat Other machine learning Algorithms: * Ensemble Methods ( Stacking, bagging, boosting ) Algorithms: Random Forest, Gradient Boosting * Reinforcement learning Algorithms: Q-Learning * Neural Networks and Deep Leaning Algorithms: Convolutional Network (CNN) Data Exploration and Preprocessing: * The first part of a Machine Learning project understands the data and the problem at hand. * Data cleaning, data transformation and data pre-processing are covered using Python functions to make data exploration and preprocessing relatively easy. What is included in this Python Machine Learning: * Python Machine Learning Certificate on completion   * Python Machine Learning notes * Practical Python Machine Learning exercises and code examples * After the course, 1 free, online session for questions or revision Python Machine Learning. * Max group size on this Python Machine Learning is 4. -------------------------------------------------------------------------------- REFUND POLICY No Refunds

PYTHON BASICS: COURSE DESCRIPTION Excellent for beginners, practical, in small groups of max 4 people, 1 Day Online Instructor-led. You could contact us for your prefereed date. Session 1: Python Data Types and Variables: * Primitive types; Characters & Strings; Boolean; Working with variables and its scope; Conversion and casting types in Python. * Operators and Expressions: * Introduction of operators; Arithmetic operators; Relational operators; Assignment operator; Logical operators; Increment and decrement operators.. * Exercise: Calculate Movie Tickets for a Party, Are there enough seats in the cinema? Decision Making & Loops * If statement; If - else statement; If- elif - else statement; Nested if - else; * Exercise: Calculate the travel fee to deliver goods * The while, For loop * Jump statements: break, continue; * Nesting loops. * Exercise: Enter a password, if incorrect 3 times, you are blocked. Session 2: Data Structures * Lists. * Tuples. * Exercise: Hangman Game * Exercise: Get a word for the game from a Json File, store the high score in a Dictionary file Session 3: Files and exceptions * Exception Handling, Exception types; Using try and Except. * Files, streams: Open, Traverse, Read and Create Files: Csv, txt and Json Files. * API: Connecting to API’s. Session 4: OOP * Creating and using custom Functions. * Using parameters and return values. * Creating a Class; Creating an Object; Using an Object; Adding Instance variables; * Class Constructors; Parameterized Constructors. * Inheritance. Override. Session 5: Pandas Dataframe Basics * Getting data into a dataframe: Dict to Dataframe, Dataframe to Dict. Excel To Dict, Dict to Excel , working with Excel data, multiple Excel sheets. * Getting information about the dataframe, * Filter, sort and query a Dataframes, Slicing Dataframes, * Duplicate values,Working with null-values, Sampling. * Exercise: Query the top 1000 grossing movies of the last century Session 6: Built in Functions: String, Math, Random * Python built-in functions: * Strings functions. Maths functions. Random Functions. * Exercise: Find information in prose, to get the sentiment of the prose. * Exercise: Get a word for the game from a txt File * Exercise: Win the lottery INCLUDED: * PCWorkshops's Python Programming Basics Certification * Course notes, exercises and code examples * Revision session after the course -------------------------------------------------------------------------------- REFUND POLICY No Refunds

Python coding, interactive, instructor-led, hands-on, practical. From basics to working with professionals. Python Part Time. Python Coding. -------------------------------------------------------------------------------- Python Beginners Evenings Course COURSE SUMMARY This Python Programming course has become essential to all professional who would like to do code using Python. Learn evenings, work while studying. Work and study Python Part Time. It is a Python beginners course and teaches Python coding from scratch to intermediate. Hands-on, practical. We code some real life examples in this course. Duration: 3 Evenings, once per week for 3 weeks 6pm-8pm, of which the first date only shows on the booking. Virtual Classroom: You could attend in our classroom, or attend online via virtual classroom, by select the appropriate ticket. Who Should Attend? This course is intended for beginner programmers who need to code in Python. Fast-paced, Quite intensive. Course Outline: Session 1: Basics * Python Data Types, Variables, * Operators and Expressions: Arithmetic operators; Relational operators; Assignment operator; Logical operators. * Decision Making: If statement; If - else statement; If- elif - else statement; Nested if - else; * Using Loops: The while, while-else; do-while and the for loop; Enhanced for loop; Jump statements: break, continue; Nesting loops. Session 2: Lists. Dictionaries, Json * Python Data Structures: Lists. Data Structures: 2-d Lists, Tuples. Dictionary, Nested Disctionary. Session 3: Built-in functions: * Python Date Functions. Random. Math Functions. String Functions. Python Regex. Session 4: Database: * Connect to a database, create Database, create a table, insert, delete, update records, query a database and display results. Drop database, drop table. Session 5: Files * Exception Handling in Python: Fundamentals of exception handling; Exception types; Using try and except. * Files, streams: Create, Open, Traverse and Read Files: Csv, txt and Json Files. * API: Connecting to API’s Session 6: M ethods, Classes and Objects * Creating and using Function, Working with parameters, Calling functions. * Object-Oriented Programming (OOP) principles. Modules and Classes, Creating an Object; Using an Object; Adding Instance variables; Controlling accessibility; Naming conventions for class member.s FAQ Do I need Python on my Laptop? Ideally spoken yes, but if not possible, you could use our online platform. Can I pay by BACS? Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com Can I pay with PayPal? Yes, simply email us, a course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com Do I get an invoice? Yes, on request. Can I pay with a PO (Purchase Order Number)? Yes, simply email us, a Python course consultant will contact you. training@pcworkshopslondon.co.uk or pcworkshopslondon@gmail.com Do I get a certificate? Yes, a PCWorkshops Certificate Can I attend in classroom? Yes, on request, and it would incur an additional charge, depending on your location. We have offices in London, Manchester, Birmingham, Portmouth, Southend-on-Sea, Milton Keynes. Can beginners follow this course? Yes, this is a Python beginner friendly course. We offer Python courses with max 4 people, so we make sure each delegates fully understand the material covered Can I customise the course? Yes, all our Python courses are customisable. We can customise the dates, times, location. course outline. -------------------------------------------------------------------------------- REFUND POLICY No Refunds

COMPLETE PYTHON TRAINING COURSE DESCRIPTION Python is an agile, robust, expressive, fully objectoriented, extensible, and scalable programming language. It combines the power of compiled languages with the simplicity and rapid development of scripting languages. This course covers Python from the very basics of 'hello world!' through to object oriented programming and advanced topics such as multi threading. Hands on follows all the major sections in order to reinforce the theory. WHAT WILL YOU LEARN * Read Python programs. * Write Python programs. * Debug Python programs. * Use Python's objects and memory model as well as its OOP features. COMPLETE PYTHON PROGRAMMING TRAINING COURSE DETAILS * Who will benefit: Anyone wishing to learn Python. * Prerequisites: None. * Duration 5 days COMPLETE PYTHON PROGRAMMING TRAINING COURSE CONTENTS * Welcome to Python: What is Python? Origins, features. Downloading and installing Python, Python manuals, comparing Python, other implementations. * Getting started: Program output, the print statement, "hello world!", Program input, raw_input(), comments, operators, variables and assignment, numbers, strings, lists and tuples, dictionaries, indentation, if statement, while Loop, for loop. range(), list comprehensions. Files, open() and file() built-in functions. Errors and exceptions. Functions, Classes, Modules, useful functions. * Python basics: Statements and syntax, variable assignment, identifiers, basic style guidelines, memory management, First Python programs, Related modules/developer tools. * Python Objects: Other built-in types, Internal Types, Standard type operators, Standard type built-in functions, Categorizing standard types, Unsupported types. * Numbers: Integers, Double precision floating point numbers, Complex numbers, Operators, Built-in and factory functions, Other numeric types. * Sequences: strings, lists, and tuples: Sequences, Strings, Strings and operators, String-only operators, Built-in functions, String built-in methods, Special features of strings, Unicode, Summary of string highlights, Lists, Operators, Built-in functions, List type built-in methods, Special features of lists, Tuples, Tuple operators and built-in functions, Tuples special features, Copying Python objects and shallow and deep copies. * Mapping and set types: Mapping Type: dictionaries and operators, Mapping type built-in and factory functions, Mapping type built-in methods, Dictionary keys, Set types, Set type operators, Built-in functions, Set type built-in methods. * Conditionals and loops: If, else and elif statements, Conditional expressions, while, for, break, continue and pass statements, else statement . . . take two, Iterators and iter(), List comprehensions, Generator expressions. * Files and input/output: File objects, File built-in functions [open() and file()], File built-in methods and attributes, Standard files, Command-line arguments, File system, File execution, Persistent storage modules. * Errors and exceptions: What are exceptions? Detecting and handling exceptions, Context management, Exceptions as strings, Raising exceptions, Assertions, Standard exceptions, Creating Exceptions, Why exceptions, Exceptions and the sys module. * Functions: Calling, creating and passing functions, formal arguments, variable-length arguments, functional programming, Variable scope, recursion, generators. * Modules: Modules and files, Namespaces, Importing modules, Module import features, Module built-in functions, Packages, Other features of modules. * Object-Oriented Programming (OOP): Classes, Class attributes, Instances, Instance attributes, Binding and method invocation, Static methods and class methods, Composition, Sub-classing and derivation, Inheritance, Built-in functions for classes, and other objects, Customizing classes with special methods, Privacy, Delegation, Advanced features of new-style classes (Python 2.2+), Related modules and documentation. * Execution environment: Callable and code Objects, Executable object statements and built-in functions, Executing other programs. 'Restricted' and 'Terminating' execution, operating system interface. * Regular expressions: Special symbols and characters, REs and Python, Regular expressions example. * Network programming: Sockets: communication endpoints, Network programming in Python, SocketServer module, Twisted framework introduction. * Internet client programming: What are internet clients? Transferring files, Network news, E-mail. * Multithreaded Programming: Threads and processes Python, threads, and the global interpreter lock, The thread and threading Modules. * GUI programming: Tkinter and Python programming, Tkinter Examples, Brief tour of other GUIs. * Web programming: Web surfing with Python: creating simple web clients, Advanced Web clients, CGI: helping web servers process client data, Building CGI applications, Using Unicode with CGI, Advanced CGI, Web (HTTP) Servers. * Database programming: Python database application programmer's interface (DB-API), ORMs. * Miscellaneous Extending Python by writing extensions, Web Services, programming MS Office with Win32 COM, Python and Java programming with Jython.

PYTHON TRAINING COURSE DESCRIPTION This Python course focusses on teaching Python for use in network automation and network DevOps. We focus on getting delegates up and running with Python and network automation as quickly as possible rather than making them great programmers. In other words we concentrate on enabling delegates to use network automation libraries such as netmiko, NAPALM and Nornir, and APIs such as NETCONF and RESTCONF rather than enabling delegates to produce object oriented programs. Hands on sessions use Cisco and Juniper devices. WHAT WILL YOU LEARN * Run Python programs. * Read Python programs. * Write Python programs. * Debug Python programs. * Automate network tasks with Python programs. * Configure network devices with Python. * Collect data from network devices with Python. PYTHON TRAINING COURSE DETAILS * Who will benefit: Network engineers. * Prerequisites: TCP/IP Foundation * Duration 5 days PYTHON TRAINING COURSE CONTENTS * What is Python? Programming languages, Why Python? Python in interactive mode, Python scripts, ipython, Python version 2 versus version 3. A simple Python script. Comments. Hands on Installing Python, Hello world. * A network example On box vs off box Python. telnet, ssh, NETCONF, HTTP, APIs, manufacturers and API support, analysis of a simple telnetlib program. Hands on Using Python to retrieve the configuration from a network device. Using wireshark to analyse the actions. * Python basics I/O, operators, variables and assignment, types, indentation, loops and conditionals. Hands on Modifying the telnet program, changing configurations on a network devices. * Functions, classes and methods What are functions, calling functions, builtin functions, useful builtin functions, file handling, classes, objects, creating instances. Hands on Storing configurations in files, configuring devices from files, using an inventory file to work on multiple devices. * Libraries and modules Modules, files and packages, import, from-import, Python standard library, other packages, pip install, executing other programs. Managing python libraries. Hands on Using pip, installing and using ipaddress, subprocess to access netsnmp. For the more advanced, using the sockets library. * Paramiko and netmiko SSH, enabling SSH on devices, keys. Paramiko versus netmiko, example scripts. pexpect. Hands on Configuring VLANs from Python. * pySNMP Gathering facts using previous methods, SNMP review, pySNMP GET, pySNMP and SNMPv3. easySNMP library. Hands on Walking a MIB from Python. * NETCONF What is NETCONF? Enabling NETCONF on devices, A first ncclient script, device handlers, get_config, edit_config, copy_config, delete_config, commit, validate, pyEZ, utils_config, utils.sw. Hands on Configuration using ncclient and PyEZ. This session is expanded for those interesting in JunOS automation. * Manipulating configuration files Builtin functions, string handling. Unicode. Sequences, strings, lists, tuples. Dictionaries. TextFSM. Regular expressions. JSON, YAML, XML, YANG, Jinja2, templates. Hands on Jinja2 templating with Python to configure network devices. * NAPALM Getters, configuration operations, supported devices, NAPALM transport, Config-replace, Config-merge, Compare config, Atomic changes, rollback. Example NAPLAM scripts. Hands on Using NAPALM to gather facts, Using NAPALM for configuration management * REST and RESTCONF What is REST, HTTP methods, GET, POST, cURL, Postman, Python requests library. RESTCONF, a RESTCONF example. Hands on Modifying a configuration using RESTCONF. * Scapy What is scapy, Scapy in interactive mode, Scapy as a module. Hands on Packet crafting from Python. * Warning Errors and exceptions, Exception handling, try, except. Memory management. Garbage collection. Context management, With. Hands on Improving Python code. * Nornir What is Nornir? A network automation framework, inventories, connection management and parallelization. Nornir architecture and other libraires. Hands on Setting up nornir, nornir fact gathering, nornir tasks. * Optional Writing your own functions, Writing your own classes. pyntc. Hands on Writing reusable code.

ADVANCED PYTHON TRAINING COURSE DESCRIPTION This course caters to network engineers aiming to enhance both their Python proficiency and network automation skills. Delving deeper into key areas such as netmiko, Nornir, and ncclient, we also focus on automating network testing and validation. Participants gain greater confidence working with Python functions, classes, objects, and error handling. The course additionally introduces more libraries like Scrapli, TTP, pyATS, Genie, pybatfish, and Suzieq, which cover parsing strategies, automation testing, validation, network analysis, observability, and telemetry. The curriculum also encompasses concurrency techniques. WHAT WILL YOU LEARN * Write Python modules and functions. * Evaluate techniques to parse unstructured data. * Use NETCONF filters. * Handle Python errors effectively (try, assert…). * Use postman. * Automate testing and validation of the network. * Use scrapli, Genie, batfish and Suzieq. ADVANCED PYTHON TRAINING COURSE DETAILS * Who will benefit: Network engineers. * Prerequisites: Python for network engineers * Duration 5 days ADVANCED PYTHON TRAINING COURSE CONTENTS * Review CLI, NETCONF, RESTCONF, structured versus unstructured data, gNMI and when to use which. PEP 8. Naming conventions. Packages, modules, Classes and methods. The scrapli library. Netmiko versus scrapli. Hands on: scrapli, Dictionaries versus Regular Expressions. * Modules and Functions Writing your own modules, containers versus packages, virtual environments. Best practices, calling functions, writing your own functions. Parameters, arguments. Named arguments, dictionaries as arguments. Builtins. Docstrings. Main. __name__, __main__ . Program arguments. Hands on: Getting interfaces, showing interface status using Netmiko and functions. Using dictionaries as arguments. Writing your own modules. * Parsing strategies Turning unstructured data into structured data. textfsm, PyATS Genie parser, NAPALM getters, Template Text Parser. Hands on: Genie parser, TTP. Accessing structured data with lists and dictionaries. * Classes, objects and Python Python classes in Genie, PyEZ and others . Hands on: studying network automation classes, objects, methods and attributes. * Configuration management - more nornir, ncclient, requests Nornir tasks. Nornir results, Nornir functions, Nornir plugins. Nornir processors. YANG, YANG models, pyang. NETCONF hello. Capabilities. Schemas. Filters. Subtrees. XPATH. Exploring available YANG data models. NETCONF and network wide transactions. Asserting NETCONF capabilities. Configuration types. Locking configurations, commits. NETCONF data stores. Netconf-console. RESTCONF differences from NETCONF. URI construction. Postman. More XML and JSON. Git and configuration versions. Hands on: Nornir and Jinja2. Exploring available models, NETCONF filters. Using postman. * Python error handling and debugging Context handlers, try, assert, logging, pdb, pytest, unit testing, chatgpt. Hands on: Writing code with each of the error handling methods, investigating what happens on an error. Use chatgpt to debug your code. * Python Automation Testing Testing and validation. pyATS, Genie. Testbed file. Genie parse, genie learn, genie diff. Genie conf, Genie ops, Genie SDK, Genie harness. Xpresso. Hands on: Using Genie for state comparisons of the network. * Network analysis Batfish, pybatfish, configuration analysis, analysing routing, analysing ACLs. Pandas. Pandas dataframe. Filtering and selecting values of interest. Hands on: Use Batfish to analyse network snapshots, find network adjacencies, flow path analysis. * Network observability Suzieq, using docker, using as a package. Sqpoller, suzieq-gui, suzieq-cli, sq-rest-server. Namespaces and seeing devices, network state and Asserts. Time based analysis, snapshots and changes. Hands on: Suzieq: Gathering data from the network, analysing data from the network. Network state assertion. * Telemetry gRPC, gNMI. CAP, GET, SET. Subscriptions. Model Driven telemetry. Hands on: Analysing telemetry data with Python. * Concurrency asyncio, threads, processes. Nornir concurrency. Scrapli and netmiko concurrency. Hands on: Multiple SSH connections to devices at same time. Scarpli asyncio.

Powerful 1-hour Python workshop course understand Python Basics. Practical. Instructor-led. Online. -------------------------------------------------------------------------------- LEARN TO CODE A PASSWORD VALIDATOR IN 1 HOUR.  Basics made simple!  Learn plenty in one day: Code A Password Validator * Essentials of Python programming. * Practical lessons and exercises. * Great Tutors.  * Online. * You may Request a Central London Location, per email Who will the Course Benefit? * This is a fantastic course for beginners * Or for coders, simply fast-track crossing over to Python. Teaching Style: Practical, Interactive, Personalised. Useful examples. What is included? * Course notes, exercises and examples. * Course certificate. LEARN PYTHON BY CODING A PASSWORD VALIDATOR STEP 1: Using variables. Arithmetic operations. Strings. String Functions STEP 2: Getting user input from console. Decision Making(If-else) STEP 3: For and While Loops. Repeat code by using loops. STEP 4: Lists: Create, Update, Iterate Lists. Using indexes to refer to individual values. STEP 5: Object Oriented Programming. Functions. Classes. STEP 6: Create the Password Validator -------------------------------------------------------------------------------- REFUND POLICY No Refunds

Maximize the value of data assets in the oil and gas sector with EnergyEdge's assessment-based training course on Python programming and analytics.

NETWORK AUTOMATION COURSE DESCRIPTION This course is not a soft skills course covering the concepts of DevOps but instead concentrates on the technical side of tools and languages for network DevOps. Particular technologies focussed on are ansible, git and Python enabling delegates to leave the course ready to starting automating their network. Hands on sessions follow all major sections. More detailed courses on individual aspects of this course are available. WHAT WILL YOU LEARN * Evaluate network automation tools. * Automate tasks with ansible. * Use git for version control. * Use Python to manage network devices. * Use Python libraries for network devices. NETWORK AUTOMATION COURSE DETAILS * Who will benefit: Network engineers. * Prerequisites: TCP/IP foundation for engineers. * Duration 5 days NETWORK AUTOMATION COURSE CONTENTS * What is DevOps Programming and automating networks, networks and clouds, AWS, OpenStack, SDN, DevOps for network operations. * Initial configuration Configuring SSH, ZTP, POAP. Hands on Initial lab configuration. * Getting started with ansible The language, the engine, the framework. Uses of ansible, orchestration. The architecture, Controlling machines, nodes, Agentless, SSH, modules. Configuration management, inventories, playbooks, modules, roles. Hands on Installing ansible, running ad hoc commands. * Ansible playbooks ansible-playbook, YAML, plays, tasks, handlers, modules. Playbook variables. Register module, debug module. Hands on Running playbooks. * Ansible Inventories /etc/ansible/hosts, hosts, groups, static inventories, dynamic inventories. Inventory variables, external variables. Limiting hosts. Hands on Static inventories, variables in inventory files. * Ansible modules for networking Built in modules, custom modules, return values. Core modules for network operations. Cisco and/ or Juniper modules. ansible_connection. Ansible 2.6 CLI. Hands on Using modules. * Ansible templating and roles Configuration management, full configurations, partial configurations. The template module, the assemble module, connection: local, Jinja2 templates, variables, if, for, roles. Hands on Generating multiple configurations from a template. * Network programming and modules Why use Python? Why use ansible? alternatives, ansible tower, Linux network devices. * Programming with Python Scripting versus application development, Python interactive mode, Python scripts, Python 2.7 vs Python 3. A simple Python script. Variables, loops, control statements, operators. PEP style guide. Python IDEs. Hands on Simple Python programs. * More Python programming Functions. Classes, objects and instances, modules, libraries, packages. Python strings, Python file handling, pip list, pip install, Hands on Python programming with pyping. * Git Distributed version control, repositories, Git and GitHub, Alternatives to GitHub, Installing git, git workflows, creating repositories, adding and editing files, branching and merging, merge conflicts. Hands on working with Git. * Python and networking APIs, Sockets, Telnetlib, pysnmp, ncclient, ciscoconfparse. * Paramiko SSH and Netmiko Integrating Python and network devices using SSH. Netmiko, Netmiko methods. Hands on Netmiko. * PyEZ Juniper, NETCONF, installing PyEZ, a first pyEZ script, pyEZ configuration management. Hands on Juniper configuration management with pyEZ. * NAPALM What is NAPALM, NAPALM operations, getters, Replace, merge, compare, commit, discard. Hands on Configuration with NAPALM. Integrating ansible and NAPALM. * Python and REST REST APIs, enabling the REST API. Accessing the REST API with a browser, cURL, Python and REST, the request library. Hands on Using a REST API with network devices.