Fundamentals of Large Language Models
Understand how large language models (LLMs) and generative AI create content, solve problems, and power modern applications across text, images, and more.
Course Information
Certificate Track
About this Course
Step inside the systems behind today’s most pervasive AI tools. This course helps you build a clear understanding of how LLMs work, from how they process text to how they generate responses, reason through problems, and support real-world tasks. You’ll develop the intuition to use these tools effectively and responsibly across different contexts.
You’ll explore how generative AI creates text, images, and other content, and how multimodal systems combine different types of data for richer outputs. Along the way, you’ll learn practical prompting techniques, understand how models are trained and used, and examine their strengths, limits, and ethical challenges. By the end of the course, you’ll be able to think critically about how these systems shape work, creativity, and decision-making.
Fundamentals of Large Language Models is one of the five courses in Universal AI, a self-paced program designed to help you go from beginner to AI authority—no coding or technical skills required.
What you'll learn
- Understand how large language models work, including transformers, attention, and text generation
- Use prompting techniques like zero-shot, few-shot, and step-by-step reasoning
- Learn how generative AI creates content like text and images
- Understand how embeddings help connect and combine text, images, audio, and other data
- Evaluate the strengths, limits, and ethical risks of generative AI systems
- Explore how generative AI is changing creativity, work, and decision-making across industries
Modules
This course has 3 modules
Meet your instructors
Dimitris Bertsimas
Vice Provost for Open Learning, MIT Open Learning
Dimitris Bertsimas is the Vice Provost for Open Learning at MIT, the Associate Dean of Business Analytics, the Boeing Leaders for Global Operations Professor of Management, and a Professor of Operations Research at MIT Sloan School of Management. At MIT Open Learning, he oversees Open Learning’s product offerings, new initiatives, infrastructure, finances, and operations.
