Generative AI Bootcamp

This AI Literacy series gives you the tools to unlock real value from Generative AI, moving from basic prompt crafting to full-scale automation. In this session, which covers Levels 1 & 2, you’ll learn how to shape clear, effective prompts that get better results from AI, setting the stage for more advanced use cases. Then, you’ll create reusable prompts and automate everyday workflows to save time and boost team efficiency. Level 3 and above are not covered in this session.

This course empowers you to streamline tasks, enhance productivity, and make Generative AI a part of your daily operations.

Levels 1 & 2

Generative AI (GenAI) Foundations and Basic Prompting

Content:

• Introduction to GenAI: Overview of how GenAI works, with a focus on next-token prediction, scaling trends, and some of its emergent capabilities.
• Few-shot Prompting: Learn the essentials of prompt formulation, including how to provide templates to the AI

Learning Outcomes:

• Understand how GenAI uses next-word-prediction to build complex conversations.
• Understand why models keep getting bigger and what this means for training data.
• Write a few-shot prompt and know how to improve it.

Getting Better at Prompting

Content:

• Prompt refinement: The first attempt is never great – we’ll look at how to make your first prompt better.

• Multi-modal prompting: How to combine your prompts with images, screenshots and documents.
• Meta-prompting: Even more outsourcing, this time getting the AI to write its own prompts.
• Other Prompting Techniques: Chain of thought prompting (step-by-step reasoning) and ensemble prompting (multiple models).

Learning Outcome:

• Try out advanced prompting techniques for different kinds of problems.

Common Use Cases and Practical Applications

Content:

• Tutor and Peer Review: Prompts to learn new ideas and get feedback.
• Identifying misinformation: Classify the four ways that GenAI output can be wrong and know how to spot them.
• Text and Tone Modification: Experiment with prompts to adjust style, tone, and level of formality in text.
• Document Query and Summarization: Practice using models like NotebookLM for querying long documents and generating summaries.

Learning Outcomes:

• Build a workflow prompt that can replicate complex organisational tasks.
• Use GenAI to augment your own learning in information-rich environments.
• Understand and engage in text modification while checking underlying messages haven’t been changed.
• Effectively look for mistakes in GenAI output.

Developing Simple GPTs

Content:

• Introduction to GPT Customization: Explore the basics of developing tailored GPTs for specific tasks or workflows.
• Hands-on GPT Creation: Build simple, task-oriented GPTs with custom instructions, using provided templates or starting from scratch.
• Crossing the line: We’ll explore some clearly unethical use cases and discuss the ethical challenges that can arise.

Learning Outcomes:

• Build a simple GenAI computer program to automate simple tasks for you.
• How to start thinking about GenAI and organisational responsibility.