Large Language Models & Agentic AI: From Fundamentals to AI

This self-paced course introduces the foundations of AI, Natural Language Processing, LLMs and Agentic AI. Learn how language models process information, how AI agents use tools to complete tasks, and how reasoning approaches such as ReAct, Plan-and-Execute and Tree of Thoughts support multi-step problem-solving.

Study at your own pace and develop the conceptual knowledge needed to explore modern AI application development.

Understand the Foundations of Modern AI

Artificial Intelligence is moving beyond traditional prediction and text generation towards systems that can plan tasks, interact with external tools and work towards defined objectives.

Understanding these developments requires knowledge of Machine Learning, Natural Language Processing, Large Language Models and AI agent architectures.

The LSET Large Language Models & Agentic AI course provides a structured introduction to these technologies. You will begin with core AI concepts before exploring how LLMs process language, generate responses and use contextual information.

The course then introduces Agentic AI, including autonomous agents, tool-assisted workflows and reasoning strategies. Through a series of focused video lessons, you will build a conceptual understanding of how these components fit together in modern AI systems.

Whether you are a student, software developer or technology professional, this course provides a foundation for further learning in AI engineering and AI-powered application development.

Who Is This Course For?

This course is suitable for:

• Aspiring AI Engineers: Build a conceptual foundation in LLMs, AI agents and modern AI system architectures.
• Software Developers: Understand how language models, tools and agent workflows can support AI-powered software applications.
• Students and Recent Graduates: Explore key AI concepts and prepare for more advanced learning in Generative AI and AI engineering.
• Technology Professionals: Develop an understanding of current AI technologies and how agent-based systems can support business and software workflows.
• AI Enthusiasts: Learn how modern language models and AI agents work, without needing to begin with advanced mathematical theory.

How Self-Paced Learning Works

• Learn at Your Own Pace: The course is designed for flexible online learning. You can study the available video lessons according to your schedule and revisit topics whenever you need to reinforce your understanding.
• Watch the Lessons: Access the course videos through your LSET student account.
• Follow the Learning Path: Progress through the modules in sequence, starting with AI foundations and moving towards LLMs and Agentic AI.
• Revisit Key Concepts: Return to lessons to review important concepts such as Transformer architecture, context windows, AI agent workflows and reasoning strategies.
• Continue Your Learning Journey: Use the knowledge gained from this course as a foundation for further study in Generative AI, AI application development and agent frameworks.

Skills and Knowledge Areas

Throughout the course, you will explore the following areas:

• Artificial Intelligence fundamentals
• Machine Learning and Deep Learning
• Natural Language Processing
• Large Language Models
• Transformer architecture and attention
• Tokens and context windows
• Model parameters, training and inference
• Agentic AI concepts
• Autonomous and tool-assisted agents
• AI reasoning and planning strategies
• Tool integration concepts
• AI workflow safety and human oversight

Frequently Asked Questions

Do I need previous AI experience?
No advanced AI experience is required. The course begins with foundational concepts and gradually introduces LLMs and Agentic AI.

Do I need programming experience?
Programming knowledge is helpful if you plan to continue into practical AI application development, but it is not essential for understanding the core concepts taught in these lessons.

Can I study at my own pace?
Yes. The course is intended for self-paced learning, allowing you to study around your existing commitments.

What topics does the course cover?
The curriculum covers AI foundations, Machine Learning, Deep Learning, NLP, LLMs, Transformer architecture, AI agents, tool-assisted workflows and reasoning strategies.

Will I learn about autonomous AI agents?
Yes. Dedicated lessons introduce autonomous agents, tool-assisted agents, ReAct, Plan-and-Execute and Tree of Thoughts.

Does this course include practical coding projects?
This course focuses on conceptual foundations and the operation of AI systems. Practical coding projects or assessments should only be advertised if they are included in the published course materials.

What can I study after completing this course?
You can continue with more specialised learning in Generative AI application development, AI agent frameworks, tool integrations, Model Context Protocol (MCP) and multi-agent systems.

Begin Your Journey into LLMs and Agentic AI

Develop your understanding of the technologies shaping modern Artificial Intelligence. Explore how Large Language Models process language, how AI agents use tools, and how reasoning strategies support more structured AI workflows.

Start learning with LSET and build a foundation for your next step in AI engineering.

Start learning at your own pace with LSET's self-paced online courses.