AI/ML Course

This course is designed to take you from core AI/ML foundations to building real-world Generative AI and Agentic AI systems.

Instead of focusing only on theory, the course emphasizes practical skills, system thinking, and production-ready development.

You will start with Natural Language Processing (NLP) fundamentals and gradually move towards advanced Generative AI concepts, including LLMs, RAG pipelines, and multi-agent architectures.

What you will learn:

• NLP Foundations

Understand text preprocessing, embeddings, feature extraction, and traditional NLP pipelines. Build a strong base for working with language data.

• Machine Learning & Deep Learning Basics

Learn key ML concepts, model building, evaluation, and how deep learning models work in real-world applications.

• Generative AI (LLMs)

Understand how large language models work, prompt engineering techniques, and how to build applications using LLM APIs.

• Retrieval-Augmented Generation (RAG)

Learn how to combine LLMs with vector databases (FAISS, Weaviate) to build context-aware systems.

• Agentic AI Systems

Design and implement multi-agent workflows using frameworks like LangChain and LangGraph. Learn how agents collaborate to solve complex tasks.

• Building Real AI Products

Move beyond notebooks and learn how to design scalable AI systems. Understand APIs, microservices (FastAPI), and real-world architecture.

• Deployment & Production Best Practices

Learn how to deploy AI systems using Docker, handle scalability, manage latency, and monitor performance.

• Generative AI Product Planning

Understand how to think like a product engineer — from idea validation to building MVPs and scaling AI solutions.

By the end of this course, you will not only understand AI concepts but also be able to design, build, and deploy production-ready AI systems.

This course is ideal for students, engineers, and professionals who want to transition into AI/ML or build real-world AI applications.