AI Engineering with Python
Overview
AI is changing fast — and just learning Python or basic machine learning is no longer enough. The real demand today is for people who can build complete AI systems.
In this webinar, you will learn how modern AI applications are actually created — not just theory, but the real structure behind tools like chatbots, AI assistants, and smart automation systems.
We will break down AI Agents (how AI can take actions and make decisions), RAG (Retrieval-Augmented Generation) (how AI connects with real data instead of giving random answers), and how these ideas are used to build production-level AI systems.
What makes this session different:
- You will understand how real AI products are built
- Learn the exact concepts companies are using today
- See how to move from basic Python to real AI development
- Get a clear idea of how to start your AI Engineering journey
This is not a theory-heavy session. The goal is simple — to give you clarity, direction, and practical understanding so you can start building your own AI projects.
What you will learn
Introduction to AI Engineering
Understand the basics of AI engineering and its role in building real-world applications.
AI Agents
Learn how AI agents work and how to build autonomous systems that can make decisions.
RAG (Retrieval-Augmented Generation)
Explore how RAG connects AI with real data for smarter responses.
Production Systems
Understand how to deploy AI models into production for real-world use.
Hands-On Python Implementation
Apply concepts in Python to build practical AI solutions and projects.
More about the hosts
Adarsh Rai is an AI Research Engineer at Bootcoding and RTMNU graduate, building real-world AI solutions with a focus on agents, large language models, and practical system design.
