Overview

Build a Solid Conceptual Foundation on Machine Learning, Large Language Models (LLMs) and Agentic AI along with MLOps

What you'll learn:

Learn What Machine Learning Really Is – Build a clear conceptual understanding of how machine learning works and how it differs from traditional programming.
Explore Key Types of Machine Learning – Get introduced to supervised, unsupervised, and reinforcement learning with simple, relatable explanations.
Understand the End-to-End ML Process – Learn the basic steps involved in building a machine learning model, from data preparation to evaluation.
Get Familiar with Popular ML Algorithms – Discover widely-used ML algorithms like linear regression, decision trees, and neural networks—without diving into hea
Introduction to Large Language Models (LLMs) – Understand how modern AI models like ChatGPT work, including concepts like tokens, transformers, and prompt engin
Discover the fundamentals of Agentic AI – including memory, planning, agent architectures, tools, and real-world use cases
Reflect on the ethical considerations of Agentic AI and how it ties into modern practices like DevOps and MLOps

Curious about Machine Learning and AI but not sure where to start?
This course is your perfect entry point.

"Machine Learning, LLMs & Agentic AI – A Beginner's Conceptual Guide" is designed to give you a clear, intuitive understanding of how modern AI works — without needing any coding or math background.

We start from the very basics, explaining what machine learning is, how it's different from traditional programming, and the types of learning like supervised, unsupervised, and reinforcement learning. You’ll also learn how models are built, evaluated, and improved, and get familiar with common algorithms like regression, decision trees, neural networks, and more — all explained in a way that’s easy to follow.

From there, we shift gears into the exciting world of Large Language Models (LLMs) like ChatGPT. You’ll learn how LLMs are trained, what tokens and parameters mean, and how techniques like prompt engineering and RAG (Retrieval-Augmented Generation) enhance performance.

Finally, we introduce you to the emerging field of Agentic AI — a major shift where AI systems can plan, reason, remember, and act autonomously. You’ll explore agent architecture, memory, planning, multi-agent collaboration, real-world tools, and the ethical challenges of deploying such systems.

Whether you're a student, a professional looking to upskill, or simply curious about the future of AI — this course will give you the conceptual clarity and confidence to take the next step in your learning journey.

By the end of this course, you will: