
Trace the birth of AI and the rise of ChatGPT and LLMs, from 1980s rule-based programs to modern, thinking, writing tools that understand everyday language.
Discover how large language models power AI tools like ChatGPT and Copilot, learning language from massive text data and patterns to perform writing, summarizing, and analysis.
Understand how machine learning enables AI systems to learn from data, find patterns, and make predictions, while highlighting data quality, computing power needs, and its limits.
Explore how transformers enable context-aware language understanding, from early large language models like GPT-1 to ChatGPT, and learn how prompts and prompt engineering shape AI performance.
Explore deep learning as a multi-layer form of machine learning for complex, unstructured data. Learn how deep learning patterns emerge from raw data and excel at text, images, and audio.
Explore how neural networks use many simple neurons to learn, combine signals, and solve complex patterns in images and language, including transformers.
Embeddings convert text to numbers, mapping tokens to numerical representations that capture meaning and context. They include token position to preserve word order and handle variable lengths.
Fine tuning adapts a pre-trained language model for specific tasks, styles, or domains, improving consistency, tone, and domain-specific outputs for roles like project managers and business analysts.
Contrast traditional AI's analysis and prediction with generative AI's ability to create new content using deep learning, enabled by vast data, powerful computing, and natural language interaction.
Explore prompt engineering to steer large language models with clear instructions and core patterns like instruction, chain-of-thought, and persona, enabling high-quality, versatile outputs across tools like Canva and Copilot.
Master the instruction pattern to generate high-quality emails for marketing, sales, and business tasks, using a real-life e-commerce scenario to save hours of work.
Learn the iterative refinement pattern to improve ai outputs through step-by-step feedback, shaping emails, copy, and reports by creating, reviewing, and refining until you achieve your voice.
Master the template pattern to generate consistent, well-structured outputs for emails, reports, and content plans by defining a subject, preheader, and body structure.
Explore ethical, sustainable ai use in agile teams, balancing ai strengths in backlog refinement and sprint planning with human judgment, privacy, transparency, and collaborative leadership.
Learn how to choose between popular large language models and when to use each in real work, with practical guidance on ChatGPT, Google Gemini, Perplexity, Copilot, and Claude.
Explore how constraints shape ChatGPT outputs by specifying length, structure, and style to ensure consistency and reusability across tasks like product descriptions.
Discover how ChatGPT enables data analysis of spreadsheets and CSV files, allowing you to spot trends, patterns, and anomalies and turn numbers into insights.
Organize work with projects to group related chats, files, and context around a single goal, enabling seamless planning, research, images, product descriptions, and decisions without losing context.
Discover how to run repeating tasks in ChatGPT with scheduled tasks, enabling automatic weekly, daily, or monthly outputs in the background on a paid plan, using ChatGPT 5.2.
Learn to check images with ChatGPT's vision to spot branding inconsistencies, readability issues, and design elements before publishing.
This course contains the use of artificial intelligence.
Master AI today: Start by learning the fundamentals that make all AI tools work. Large Language Models (LLMs)!
Do you want to understand Large Language Models (LLMs) and how they power today’s most popular AI tools like ChatGPT, Gemini, Claude, and Copilot?
Are you ready to explore artificial intelligence in a clear, practical way—whether you’re new to AI or looking to build strong AI engineering fundamentals?
AI LLM Fundamentals is an AI for everyone course designed to help you confidently understand how modern generative AI works and how it’s used in real-world applications.
This course is your practical introduction to Large Language Models, the technology behind today’s best LLM platforms used across data science, software development, research, and business.
Why Learn Large Language Models and Generative AI?
Large Language Models are at the core of modern artificial intelligence. Tools like ChatGPT, Gemini, Claude, and Copilot are transforming how we write, research, code, and plan work.
Understanding LLMs helps you:
Communicate better with AI using prompt engineering
Choose the right LLM for the job
Work more efficiently with AI-powered tools
Build strong foundations for AI engineering and data science
Confidently participate in AI-driven projects at work
You don’t need to become an AI engineer to benefit—this course focuses on practical understanding, not heavy maths or theory.
Course Curriculum at a Glance
This course covers LLM fundamentals using real, widely-used AI tools:
Introduction to Large Language Models
What LLMs are, how they work, and why they matter in modern AI
AI Foundations
Artificial Intelligence, Machine Learning, Deep Learning, and Generative AI—explained simply
How LLMs Work
High-level neural networks, transformers, and natural language processing (NLP)
Prompt Engineering Basics
How to talk to AI effectively and get better results from LLMs
ChatGPT and GPT Models
What GPT means, how ChatGPT works, and where it shines
LLM Platforms Compared
ChatGPT, Gemini, Claude, Copilot, and Perplexity—strengths, weaknesses, and when to use each
Real-World LLM Use Cases
Writing, research, summarisation, documentation, code assistance, and AI workflows
Ethics and Responsible AI
Bias, accuracy, privacy, and why human judgment still matters
What You’ll Gain from This Course
By the end of this course, you will:
Understand how Large Language Models actually work
Know the difference between traditional AI and generative AI
Use prompt engineering to get better outputs from AI tools
Confidently choose the best LLM for different tasks
Apply LLMs responsibly in work and everyday scenarios
Build a strong foundation for future learning in AI engineering, gen AI, or data science
This course focuses on clarity, confidence, and real-world relevance—not hype.
Who This Course Is For
Beginners looking for AI for everyone, explained clearly
Professionals who use ChatGPT, Gemini, Claude, or Copilot at work
Developers and aspiring AI engineers who want strong fundamentals
Data scientists expanding into generative AI and NLP
Product managers, founders, and entrepreneurs working with AI tools
Students and tech enthusiasts exploring the complete generative AI landscape
No prior AI or machine learning experience is required.
Take the Next Step in Your AI Journey
If you want a clear, practical introduction to Large Language Models, generative AI, and today’s most important AI tools, this course is for you.
Enroll now and build the foundations you need to confidently work with AI—today and in the future.