Python (Gen AI /System Design / DSA/Frontend) with Dr. Ashutosh Kumar

What's Included

1. Python Programming

• Core Python, OOP, decorators and generators
• Lists, dictionaries, sets and strings
• Exception handling and context managers
• Asyncio, threading, multiprocessing and GIL
• Coding exercises with explanations

2. Data Structures & Algorithms (DSA)

• Arrays and strings
• Hash maps and sets
• Two pointers and sliding window
• Stack and queue
• Linked lists
• Binary search and sorting
• Recursion and backtracking
• Trees and binary search trees
• Heaps and priority queues
• Graphs, BFS and DFS
• Dynamic programming
• Time and space complexity
• Coding interview problems with step-by-step solutions

3. FastAPI & Flask

• REST API development
• Routing, middleware and dependency injection
• Authentication and authorization
• Async endpoints and error handling
• SQLAlchemy and database integration
• Testing and API performance

4. Frontend Development

• JavaScript fundamentals
• Asynchronous JavaScript, promises and closures
• React components, hooks and state management
• API integration and error handling
• Performance optimization and frontend architecture

5. RAG — Retrieval-Augmented Generation

• Document ingestion and chunking
• Embeddings and vector databases
• Semantic search and hybrid retrieval
• Reranking and retrieval optimization
• RAG evaluation and hallucination reduction
• Multi-tenant security and access control

6. Generative AI & Agentic AI

• LLM fundamentals and prompt engineering
• LangChain and LangGraph
• AI agents, tool calling and MCP
• Agent memory and workflow orchestration
• Guardrails, evaluation and observability
• Production deployment challenges

7. Software & Backend System Design

• REST APIs and database design
• SQL vs. NoSQL
• Caching, queues and asynchronous processing
• Microservices and distributed systems
• Scalability, reliability and fault tolerance
• Authentication, security and performance

8. GenAI System Design

• Design a production-ready RAG platform
• Design a multi-agent AI application
• Design an enterprise document assistant
• LLM serving, caching and cost optimization
• Evaluation pipelines and observability
• Data isolation, security and guardrails

Who Is This For?

• Freshers preparing for coding interviews
• Python and backend developers
• Full-stack engineers
• Experienced developers targeting senior positions
• Engineers transitioning into Generative AI

What You Get

• Topic-wise interview questions and answers
• DSA coding problems with solutions and explanations
• Python coding examples
• System design scenarios
• GenAI architecture and practical case studies
• A structured revision resource for interview preparation

Format: Downloadable digital study materials.