Advanced Python for network engineers Training in United States of America

  • Delivery Method: Online Instructor-Led / Classroom Based / Onsite
  • Participation Model: Public Training / Private / In-House Training
  • Duration: 5 Days
  • Level: Expert
  • Price: From USD 5,850 +TAX
  • Upcoming Date:
  • UK Based Global Training Provider

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. Save time automating network tasks with python. Postman, automating validation, automating testing.



Prerequisites

There are no formal prerequisite courses, however delegates are advised to know all of the knowledge in our Python for network engineers .


What You Will Learn

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.

Training Outline

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.

Why Choose Us

Experience Advanced Python for network engineers in United States of America through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

  • Delivery Method: Online Instructor-Led
  • Participation Model: Public / Private (In-house)
  • Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
  • Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
  • Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
  • Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
  • Worldwide Access: Join our live virtual classrooms from United States of America or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience Advanced Python for network engineers through face-to-face Classroom Based training in United States of America. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

  • Delivery Method: Classroom Based
  • Participation Model: Public / Private (In-house)
  • Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
  • Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
  • Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
  • Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange Advanced Python for network engineers in United States of America as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

  • Delivery Method: Onsite
  • Participation Model: Private (In-house)
  • Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
  • Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
  • Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
  • Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
  • Worldwide Onsite Delivery: Arrange the training in United States of America or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.


Contact us for more detail about our trainings and for all other enquiries!

Advanced Python for network engineers Training Course in United States of America Schedule

Join our public courses in our United States of America facilities. Private class trainings will be organized at the location of your preference, according to your schedule.

We can organize this training at your preferred date and location.
14 October 2026 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
01 November 2026 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
08 November 2026 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
17 November 2026 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
23 November 2026 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
05 January 2027 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
04 February 2027 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX
14 February 2027 (5 Days)
New York, San Francisco, Austin, Seattle, Chicago
USD 5,850 +TAX

The United States continues to define the global frontier of technology and innovation, serving as the home to the world's most influential tech titans. From the legendary Silicon Valley and San Francisco Bay Area to emerging hubs like Austin, Seattle, and the Silicon Alley in New York, the US ecosystem remains unparalleled. Top-tier institutions such as MIT, Stanford, and Carnegie Mellon provide the research backbone for breakthroughs in Artificial Intelligence, Quantum Computing, and Cybersecurity. Our training programs are meticulously aligned with these industry-leading standards, ensuring that professionals can navigate the complexities of the modern digital landscape. We bridge the gap between academic theory and high-stakes corporate execution in the most competitive tech market on Earth.

By using this website you agree to let us use cookies. For further information about our use of cookies, check out our Cookie Policy.