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AI Wizardry: Mastering Development with Auto GPT

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    Understand how GPT and other LLMs process and respond to different types of prompts
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    Design effective prompts for a wide range of tasks including summarisation, translation, Q&A, and content creation
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    Apply few-shot and chain-of-thought prompting to improve model reasoning and output quality
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    Identify and mitigate common challenges such as hallucination and prompt sensitivity
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    Use prompt engineering tools and frameworks in a systematic way
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    Integrate LLM capabilities into workflows and applications through structured prompt design.

Overview

Off the shelf (OTS)

This course is designed for developers, analysts, content creators, and technical professionals who want to effectively leverage large language models like GPT in real-world scenarios. It is particularly valuable for those working with AI-powered applications, automation, or content generation who want to optimise model performance through prompt design.

Familiarity with basic programming concepts and a general understanding of natural language processing is helpful but not required.

The Mastering Prompt Engineering for GPT Training Course provides a practical deep dive into the techniques and principles behind prompt engineering for generative language models. Participants will explore how GPT models interpret prompts, the mechanics of few-shot and zero-shot learning, and how to guide outputs effectively for a range of use cases. The course includes hands-on labs, examples across industries, and structured frameworks for prompt design. Attendees will also learn about the limitations and risks of prompt-based AI systems, including bias, hallucination, and reliability.

Key Topics Covered:
• Introduction to large language models and prompt engineering fundamentals
• Zero-shot, one-shot, and few-shot prompting strategies
• Structuring prompts for reasoning, summarisation, transformation, and dialogue
• Prompt tuning, chaining, and integration into applications
• Addressing model limitations, hallucinations, and ethical considerations
• Tools and platforms for testing and deploying prompt-based solutions

The course is delivered over three days and includes guided hands-on exercises using real-world examples and use cases.

Delivery method
Virtual icon

Virtual

Course duration
Duration icon

21 hours

Competency level
Expert icon

Expert

Pink building representing strand 4 of the campus map
Delivery method
  • Virtual icon

    Virtual

Course duration
Duration icon

21 hours

Competency level
  • Expert icon

    Expert

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