Understand how AI thinks. Make it your sharpest tool!

What exactly is an LLM, and how does it work?

• This module strips away the technical jargon to show you what’s really happening inside ChatGPT and similar AI systems. 
• You’ll see why they’re better described as “pattern prediction engines” than databases, learn the three-step training process that shapes their behavior, and discover how words become mathematical objects the model can “reason” about. 
• We’ll also cover how the model actually generates an answer in real time, and why even the best AI can produce convincing nonsense, show bias, or miss recent developments. 
• By the end, you’ll understand the machine’s inner logic well enough to use it effectively — and to spot when it’s going off track.

What’s really under the hood of an LLM?

• This module takes you behind the scenes of the architecture that made ChatGPT possible. 
• You’ll grasp the core idea of the transformer and its “attention mechanism” in simple terms, see why the size of a model,  in parameters, computing power, and training data, can make or break its performance, and understand how OpenAI’s models have evolved from GPT-3.5 to GPT-5. 
• We will compare models built for lightning-fast business use with those pushing the limits of AI research, so you can match the right tool to the right task with confidence. 

Why does the AI sometimes feel brilliant and other times frustrating?

• This module shows you the levers that control the model’s personality, reliability, and scope. 
• You’ll learn how settings like temperature affect creativity and precision, why prompt size can make or break your results, and where the AI’s knowledge stops and educated guesses begin. 
• We’ll also reveal the two layers of instructions shaping every conversation, the hidden system prompt and your own words, so you can work with both to get exactly the output you need. 

If AI is so advanced, why can’t we trust it completely?

• This module dives into the hidden weaknesses of even the best language models. 
• You’ll see why hallucinations happen, how bias gets baked in, and what security vulnerabilities most casual users overlook. 
• We’ll then shift to a governance mindset, blending safeguards, oversight, and risk awareness, so you can use AI confidently without falling into the traps that catch less-informed practitioners. 

How do you turn AI theory into practical, repeatable results?

• In this module, you’ll bridge the gap between knowing how LLMs work and actually getting them to deliver exactly what you need. 
• We’ll explore proven prompting techniques — from giving the right amount of guidance (few-shot vs. zero-shot) to breaking down complex tasks (decomposition), having the AI review its own work (self-critique), and connecting it to trusted sources (retrieval-augmented generation). 
• You’ll also see why these skills will remain essential, even as AI systems evolve, so you’re prepared for the tools of today and tomorrow. 

A focused update on the new capabilities in GPT-5 that change how you work with AI.

• This mini-module shows you how to control GPT-5’s autonomy, make its reasoning visible, and keep prompts clear and compliant.
• You’ll learn how to set the right “eagerness” level for the task, design tool preambles for transparency, and use the new verbosity and reasoning effort settings for better results.
• These skills help you adapt fast to the latest AI behaviours while meeting oversight and governance needs.