Python Course Online — Live Classes from Basics to AI
A live, mentor-led Python course online for beginners and career switchers anywhere in India or abroad. Twenty weeks take you from your first script through every core Python topic, data structures, MySQL, MongoDB and FastAPI to your first Generative AI app — with weekly labs, GitHub code reviews and a verifiable certificate.
Updated- Live online classes + recordings
- Senior Python developers as mentors
- Certificate with a verifiable ID
Choosing a Python course online usually means picking between a recorded playlist you never finish and a live class whose syllabus nobody will show you. The Ezibell AI Academy, run by Ezibell Tech, a software company based in Jaipur, takes a third route: live online classes taught by senior Python developers, every session recorded, and a week-by-week syllabus published on each programme page before you pay. Join from any city or country, on weekday evenings or weekends.
Beginners start with the 20-week Python to AI Launchpad, about 150 live hours with no coding experience needed. The first twelve weeks are the language itself: syntax, data types, strings, collections, control flow, functions, object-oriented Python, the standard library, errors, file handling, testing, and data structures and algorithms. Then you put it to work with MySQL and MongoDB, a FastAPI web service and an AI app that answers from your own documents.
After the Launchpad, the path branches by goal. The 16-week Backend programme adds Django, Django REST Framework, FastAPI, PostgreSQL, Redis, Celery and Docker; the 8-week REST API programme goes deep on authentication, rate limiting and versioning; the 4-week Interview Bootcamp prepares experienced developers with three mock interviews. Prefer personal guidance? Work 1:1 with a mentor. Fees and EMI options are shared on WhatsApp at +91 82097 16316.
What this Python course online covers
Foundations, set up like a professional
Weeks 1 to 3: Python, VS Code and the REPL, Git and GitHub from day one, variables and every operator family, casting, input(), and strings in depth — slicing, methods, f-strings, escape characters and Unicode. Labs include a unit converter and a text analyser.
Collections and control flow
Weeks 4 to 6: lists, tuples, sets and dictionaries with their methods, comprehensions and the array module, then if/elif/else, match statements, loops, enumerate, zip and iterators. You learn which collection to choose, and build a student-grades manager and a menu-driven app.
Functions and object-oriented Python
Weeks 7 to 9: *args and **kwargs, LEGB scope, lambdas, recursion, generators, decorators and type hints, then classes, class and static methods, properties, magic methods, inheritance, polymorphism, encapsulation, dataclasses and abstract base classes, ending in a library-management system.
Standard library, errors and testing
Weeks 10 and 11: packages, pip and venv, datetime, JSON, regular expressions, pathlib and requests; then exceptions, context managers, CSV files, logging instead of print() and unit testing with pytest, applied in an expense tracker with automated tests.
Data structures and algorithms
Week 12: stacks, queues, linked lists, hash tables, trees and binary search trees, graphs with BFS and DFS, searching, seven sorting algorithms and Big-O notation. You implement the structures from scratch and benchmark the sorts yourself.
Working with data and databases
Weeks 13 and 14: NumPy, Pandas, Matplotlib charts, SQL with MySQL including joins, and MongoDB through PyMongo, plus when to choose SQL or NoSQL. This is practical data handling for developers, not data science, ending in a report on a public dataset.
FastAPI and your first AI apps
Weeks 15 to 18: REST fundamentals, FastAPI routes, Pydantic models, CRUD, token authentication and API tests; then prompting, OpenAI and Claude APIs, structured outputs, embeddings, RAG with citations, LangChain basics and an introduction to agents.
Capstone, portfolio and certificate
Weeks 19 and 20: Docker and cloud deployment, a capstone with weekly mentor reviews, a README recruiters will read, resume, LinkedIn and GitHub reviews and a mock interview, then a certificate verifiable at /certificates.
Choose your programme
Every track is live, mentor-led and project-based. Tap one for the full syllabus, duration and FAQ.
Python to AI Launchpad
Twenty weeks and about 150 live hours: every core Python topic, data structures and algorithms, MySQL, MongoDB, FastAPI and Generative AI, with a RAG capstone, resume review and a mock interview.
Python learners aiming for backend developer rolesBackend Engineering with Django & FastAPI
Sixteen weeks of Django, Django REST Framework, FastAPI, PostgreSQL, Redis, Celery, testing, security and Docker deployment to AWS, ending in a multi-tenant SaaS backend reviewed by a team lead.
Developers who already build APIsREST API Engineering with Python
Eight weeks on API design, JWT rotation, OAuth2 scopes, rate limiting, idempotency, caching, versioning and observability, built in Django REST Framework and FastAPI and load-tested with Locust.
Python developers with 1–8 years’ experience facing interviewsPython Interview Bootcamp
Four weeks on Python internals, DSA patterns and backend and AI system design, with three recorded mock interviews, written feedback and a resume and LinkedIn rewrite.
Learners who prefer personal guidance to a batch1:1 AI Career Mentorship
Four one-hour 1:1 sessions a month with a senior developer, a personal roadmap across Python, backend, AWS or AI, pull-request reviews and a monthly mock interview.
Live online Python classes vs recorded courses
Recorded Python courses are good for reference and weak on accountability; live mentor-led classes ask more of your calendar but are much harder to quietly abandon. A video cannot tell you that your loop works for the wrong reason, that your function mutates a default list, or that your project structure will collapse at the third file. A mentor reading your pull request can, and early feedback shapes the habits you keep for years.
Our format keeps the useful parts of both. Classes are live, so you ask questions while the idea is fresh, and every session is recorded for replay. Between classes, doubts go to a private mentor group, and most weeks end with a lab pushed to your own GitHub. If you are disciplined and only need syntax, a free recorded course may be enough; if you have started and stopped before, live review is what changes the outcome.
What “every Python topic, properly” actually means
It means learning the language in the order you will use it, with a lab for every block, instead of racing to a framework in week two. The Launchpad spends twelve weeks on Python itself before databases, APIs or AI, because frameworks are easy once the language is solid and miserable when it is not. Each block, from types and strings to OOP, testing and data structures, ends in a small project committed to GitHub.
It also means covering what many beginner courses skip: identity and membership operators, structural pattern matching, iterators, LEGB scope and nonlocal, generators and decorators, magic methods such as __repr__ and __eq__, name mangling, dataclasses, context managers, regular expressions, virtual environments, logging and pytest. These come up in every code review and interview, and they are the difference between writing Python and understanding it.
From Python to backend and AI roles: a realistic path
Python alone rarely gets you hired; Python plus a specialism and a portfolio gives you a real chance. Backend roles want Django or FastAPI, SQL, authentication, testing and deployment, which the Backend and REST API programmes add. AI engineering roles want the same foundations plus LLM APIs, retrieval and agents, which the Launchpad introduces and the AI Engineer Accelerator develops once you have a year of development experience.
We do not promise placement, and you should be wary of any online course that does. What you get is concrete: a GitHub portfolio of reviewed projects, a deployed capstone, resume, LinkedIn and GitHub reviews and a mock interview on the Launchpad, or three recorded mock interviews with written feedback on the Interview Bootcamp. We share opportunities from our network, but your repository is what convinces an employer.
How the course works
- 1Free counselling call
WhatsApp or call +91 82097 16316. A mentor asks what you already know and what you want to do with Python, then recommends a track — honestly, even if it is shorter than you expected.
- 2Choose your track and timing
Pick a programme and a weekday-evening or weekend batch. The current fee, EMI options and refund and batch-transfer terms are shared in writing before you pay.
- 3Set up and first commit
Week one installs Python, VS Code and Git, and you push your first five scripts to your own GitHub repository — the habit every later lab builds on.
- 4Live classes and weekly labs
Attend live online sessions, ask questions as you go and revise from the recordings. Most modules end with a hands-on lab, from a text analyser to a notes API.
- 5Code reviews and doubt support
Mentors comment on your pull requests, and doubts between classes go to the private mentor group or the weekly doubt-clearing session, so you are never stuck for long.
- 6Capstone, demo day and certificate
Build and deploy a capstone, present it to mentors on demo day, and receive a certificate with a unique ID listed on our public verification page.
Why learn with us
What you’ll work with
What changes the fee and the time you need
We share the current fee within a few hours. These factors change it:
Tracks run from the 4-week Interview Bootcamp to the 20-week Launchpad with about 150 live hours. Longer programmes include more live teaching and mentor review time.
Batches share mentor time across a small group. 1:1 mentorship is four one-hour sessions a month on your schedule, built around your goals and code.
If you already write Python comfortably, skip the Launchpad and join the Backend or REST API programme directly, saving both weeks and fees.
Plan for about eight to ten hours a week on the Launchpad, including live sessions and practice; fees and EMI options are shared on WhatsApp.
Python course online: questions people ask
Is this Python course online live or recorded?
It is live. Mentors teach in real time and answer questions during each session, and every class is also recorded so you can revise or catch up later. Recordings and materials stay available after the programme ends; ask us for the exact access period for your batch.
Is it a Python course for beginners online, with no coding background?
Yes. The Python to AI Launchpad starts from zero and suits college students, freshers and career switchers from any stream, not just computer science. School-level arithmetic is enough. Plan for about eight to ten hours a week, and mentors review your code from the first week so you are never stuck alone.
How long does the Python full course take?
The full beginner course takes 20 weeks, about 150 live hours. Twelve weeks cover core Python and data structures, then databases, FastAPI and Generative AI, and a two-week capstone. If you already know the basics, the Backend programme takes 16 weeks and the REST API programme 8 weeks.
Is this an online Python course with certificate?
Yes. Complete the hands-on labs and the capstone, your mentor signs off your work, and Ezibell Tech issues a certificate with a unique ID that anyone can verify at /certificates. It is a professional training certificate from an MSME and GST registered company, not a university degree or a government accreditation.
Are there weekend or evening batches for live Python classes online?
Yes. The Launchpad, Backend and REST API programmes run on weekday evenings or weekends, so you can learn around college or work. The Interview Bootcamp uses weekday evenings with weekend mock interviews. Exact timings are shared before each batch starts, and recordings cover any session you miss.
What projects will I build?
On the Launchpad you build a student-grades manager, a library-management system, an expense tracker with automated tests, a data report with MySQL and Matplotlib, a notes API with FastAPI, and a capstone AI study assistant that answers from your own notes with citations. Everything lives in your own GitHub account.
Will I learn data science or machine learning?
No. The academy does not teach data science or machine learning. You use NumPy, Pandas and Matplotlib for practical data handling and build Generative AI apps on existing language models, but there is no model training or statistics. If a data-science career is your goal, we will say so honestly on the counselling call.
Do you offer placement after the Python course?
We do not guarantee placement, and you should be careful of anyone who does. You get a reviewed GitHub portfolio, a deployed capstone, resume, LinkedIn and GitHub reviews and a mock interview on the Launchpad, or three recorded mock interviews on the Interview Bootcamp. We also share opportunities from our network.
Start your online Python course with a mentor
WhatsApp or call +91 82097 16316 with your background and goal. A senior developer will recommend a track, share the current fee and EMI options, and confirm the next batch.