Foundations of AI

Core Concepts in Machine Learning, Deep Learning, Prompting, and RAG

What you’ll learn
Explain the core concepts of Artificial Intelligence, Machine Learning, Deep Learning, and Large Language Models and describe how they differ from traditional s
Analyze how Large Language Models generate text by understanding tokens, probability-based prediction, common limitations, and factors that contribute to halluc
Apply practical prompting techniques such as structured prompts, examples, and step-by-step reasoning to produce clearer and more reliable outputs from AI tools
Describe the components of Retrieval Augmented Generation including chunking, embeddings, and vector stores and evaluate when RAG systems are needed to provide

Requirements
There are no prerequisites for taking this course.

Description
Foundations of AI is a beginner-friendly and practical course that helps non-technical professionals understand how modern artificial intelligence works and how to use it confidently in real-world settings. The course is designed for people in roles such as product management, business analysis, project coordination, and other positions that work alongside technical teams. Each concept is explained clearly so that learners gain a strong understanding without needing a background in math or programming.You will begin by learning what artificial intelligence is and how it differs from traditional software. The course explains the basics of machine learning and deep learning in simple language and shows how these technologies power many tools used today. You will also learn how Large Language Models operate, how they generate text, and why they sometimes produce incorrect information. The course teaches practical prompting techniques that help you get more accurate and consistent results, including structured prompts, examples, and guided reasoning.Next, you will explore Retrieval Augmented Generation, a technique that allows AI systems to use real-time or organization-specific information. You will learn how chunking, embeddings, and vector stores work together to create reliable and grounded answers. The course also covers common limitations, responsible use, and ways to avoid misleading outputs.By the end of the course, you will understand the most important AI concepts, communicate more effectively with technical teams, and apply AI tools to improve productivity, research, decision making, and problem solving in your role.

Who this course is for
Professionals in product, business, or project roles who collaborate with technical teams
Non-technical professionals who want to understand how modern AI works
Beginners who use AI tools and want a clearer understanding of what happens behind the scenes
Career changers who want a simple and practical introduction to AI concepts
Anyone new to AI who wants a structured introduction to ML, LLMs, and RAG

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