Artificial Intelligence and ChatGPT Course

Lesson 1 • AI Applications Across Industries

Maps AI use cases in healthcare, finance, education, and creative fields. Grounds abstract concepts in tangible professional contexts learners will encounter.

Lesson 2 • Types of AI Systems

Categorises AI by capability—narrow, general, and superintelligent—and by function—generative, discriminative, and predictive. Helps learners place ChatGPT within the broader AI landscape.

Lesson 3 • Ethical Foundations of AI

Introduces bias, fairness, transparency, and accountability as core ethical pillars. Sets the responsible-use mindset required before learners begin working with AI tools.

Lesson 4 • Core AI Concepts and Terminology

Introduces machine learning, deep learning, and neural networks as nested concepts. Provides precise definitions that prevent misconceptions in later chapters.

Lesson 1 • Training, Fine-Tuning, and RLHF

Describes pre-training on large corpora, supervised fine-tuning, and reinforcement learning from human feedback. Explains why ChatGPT follows instructions and avoids harmful outputs.

Lesson 2 • Model Capabilities and Limitations

Identifies hallucination, knowledge cutoffs, and reasoning gaps as structural limitations. Prepares learners to verify outputs and design prompts that minimise errors.

Lesson 3 • Comparing Major Language Models

Benchmarks ChatGPT against other leading LLMs by capability, context length, and use-case fit. Enables informed model selection for professional tasks.

Lesson 4 • The Transformer Architecture

Covers attention mechanisms and the encoder-decoder structure that power modern LLMs without requiring mathematical depth. Builds intuition for why context window size matters.

Lesson 1 • Using Built-In Tools and Features

Introduces file uploads, image generation, browsing, and code interpreter as native capabilities. Expands learners' sense of what ChatGPT can accomplish beyond text chat.

Lesson 2 • Understanding Model Responses

Teaches learners to read, evaluate, and regenerate responses critically. Connects model behaviour knowledge from Chapter 2 to hands-on interaction.

Lesson 3 • Safety, Privacy, and Data Practices

Explains what data ChatGPT retains, how to disable training data sharing, and what not to submit. Establishes responsible usage habits before learners begin professional tasks.

Lesson 4 • Starting and Managing Conversations

Covers how to initiate chats, rename threads, and use conversation history effectively. Establishes organisational habits that scale as learners build larger prompt libraries.

Lesson 1 • Anatomy of an Effective Prompt

Breaks a prompt into role, context, task, format, and constraints components. Provides a reusable template that structures all subsequent prompting exercises.

Lesson 2 • Common Prompting Mistakes to Avoid

Catalogues vague instructions, conflicting constraints, and over-stuffed prompts as failure patterns. Prevents learners from repeating errors that waste time and tokens.

Lesson 3 • Core Prompting Techniques

Covers zero-shot, one-shot, and few-shot prompting with worked examples. Learners practise each technique and observe how examples shift output quality.

Lesson 4 • Controlling Tone, Style, and Length

Demonstrates how explicit style instructions shape formality, reading level, and word count. Directly applicable to professional writing tasks covered in Chapter 5.

Lesson 1 • Meta-Prompting and Self-Critique

Instructs learners to ask ChatGPT to evaluate and improve its own responses. Produces higher-quality outputs without requiring manual review of every draft.

Lesson 2 • Multi-Turn Conversation Design

Covers how to architect extended dialogues that maintain coherence across many turns. Prepares learners for complex research, tutoring, and workflow automation scenarios.

Lesson 3 • Structured and Formatted Outputs

Shows how to request JSON, Markdown tables, numbered lists, and custom schemas reliably. Enables direct integration of ChatGPT outputs into workflows and applications.

Lesson 4 • Chain-of-Thought Prompting

Teaches learners to instruct the model to reason step by step before answering. Significantly improves accuracy on analytical, mathematical, and logical tasks.

Lesson 1 • Building a Personal Prompt Library

Guides learners to catalogue, tag, and version their best prompts for reuse. Transforms individual productivity gains into a durable professional asset.

Lesson 2 • AI-Assisted Writing and Editing

Covers drafting emails, reports, proposals, and social posts with ChatGPT as a writing partner. Teaches review and editing prompts that preserve the author's voice.

Lesson 3 • Meeting and Project Support

Applies ChatGPT to agenda creation, meeting note summarisation, action item extraction, and project planning. Reduces administrative overhead for team leads and managers.

Lesson 4 • Research, Summarisation, and Synthesis

Demonstrates how to summarise long documents, extract key insights, and synthesise multiple sources. Builds critical evaluation skills to catch hallucinated citations.

Lesson 1 • Evaluating and Optimising Automations

Introduces metrics for measuring automation performance, reliability, and ROI. Closes the build-measure-improve loop for sustainable AI workflow management.

Lesson 2 • Custom GPTs and Assistants

Walks through creating, configuring, and publishing custom GPTs with specific knowledge and tools. Enables learners to deploy specialised AI assistants for teams or clients.

Lesson 3 • No-Code Automation with AI Tools

Demonstrates connecting ChatGPT to productivity apps using no-code automation platforms. Learners build functional automations without writing a single line of code.

Lesson 4 • Designing Multi-Step AI Workflows

Covers workflow mapping, conditional logic, and error handling for AI-driven pipelines. Prepares learners to design robust automations that handle edge cases gracefully.

Lesson 1 • Crafting Organisational AI Policies

Guides learners through drafting acceptable-use policies, approval workflows, and employee guidelines for AI tools. Produces a policy template learners can adapt for their organisations.

Lesson 2 • Regulatory and Compliance Considerations

Surveys global AI governance frameworks, data protection principles, and sector-specific compliance requirements. Prepares learners to align AI use with organisational legal obligations.

Lesson 3 • Leading AI Adoption and Change Management

Covers stakeholder communication, pilot programme design, and resistance management for AI rollouts. Transforms technically skilled learners into effective AI change agents.

Lesson 4 • Bias Detection and Fairness Auditing

Teaches practical methods for identifying and reducing bias in AI-generated content and decisions. Connects ethical foundations from Chapter 1 to actionable audit procedures.