Python

Master advanced Python 3, asynchronous programming, backend frameworks, and automated data pipelines.

Python 3.12FastAPISQLAlchemy 2.0PostgreSQLPolars & DuckDB

View Curriculum ↓Enroll Now ↗📊 Beginner to Advanced

Program Highlights

Key Benefits

Expert-led live sessions

Learn directly from experienced data scientists and AI engineers through interactive, live sessions.

Hands-on project labs

Apply your knowledge to real-world problems using industry-standard ML tools and frameworks.

Industry certification

Earn a recognized certification upon completion to showcase your AI & Machine Learning expertise.

Small batch sizes

Enjoy personalized attention and mentorship with our strictly limited batch sizes.

Career placement support

Get job-ready with resume building, interview prep, and dedicated placement assistance.

Lifetime access to recordings

Never lose your materials. Get lifetime access to all session recordings and course updates.

Course Curriculum

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Unit 1: Core Python & Object-Oriented Software Architecture20 Hours

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Unit 2: Advanced Python, Concurrency & AsyncIO20 Hours

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✓Custom decorators, generator pipelines with `yield`, and context managers (`__enter__`, `__exit__`)

✓Concurrency models: threading vs. multiprocessing vs. AsyncIO event loops

✓Handling high-throughput I/O bound network requests with `aiohttp` and `asyncio.gather`

✓Hands-on Lab: Building an asynchronous real-time web crawler with rate limiting

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Unit 3: Backend Web Services with FastAPI & PostgreSQL20 Hours

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✓FastAPI architecture: Dependency injection, middleware, and Pydantic v2 data validation

✓Async database queries with SQLAlchemy 2.0, Alembic migrations, and PostgreSQL pooling

✓JWT token authentication, password hashing with bcrypt, and role-based permissions

✓Hands-on Lab: Commercial microservice API with full OpenAPI documentation and auth

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Unit 4: Data Engineering & Analytics with Polars & DuckDB20 Hours

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✓Vectorized computations with Polars: lazy evaluation, Apache Arrow memory format

✓Embedded SQL analytics with DuckDB on large Parquet datasets without memory overflow

✓Automated data extraction, validation pipelines, and CSV/JSON/API synchronization

✓Hands-on Lab: High-speed analytics processing pipeline for 10M+ records

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Unit 5: Automated Testing, Packaging & Production Deployment20 Hours

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Hands-On Practice

4. Hands-on Production Capstone Projects

Enterprise Multi-Tenant Asynchronous Microservice Platform

Production-ready backend API featuring async PostgreSQL transactions, Redis caching, role permissions, and Swagger docs.

Automated Big Data ETL Pipeline with Polars & Parquet

High-throughput data transformation pipeline capable of ingesting and aggregating millions of events with sub-second execution.

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