Prompt Engineering for ChatGPT training course

Learn how to design and fine-tune prompts to elicit desired responses from ChatGPT

JBI training course London UK

"I hadn't integrated Pandas with Python before joining my company. So it's very useful to consolidate my understanding of such skill via this course. The Jupyter notebooks provided will be a valuable resource for revising the materials and are really well laid out." 

JL, Data Analyst, Python for Data Science, March 2021

Public Courses

17/08/26 - 1 days
£1195 +VAT
28/09/26 - 1 days
£1195 +VAT
09/11/26 - 1 days
£1195 +VAT

Customised Courses

* Train a team
* Tailor content
* Flex dates
From £1200 / day
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JBI training course London UK

This course provides participants with a solid understanding of how to design and fine-tune prompts to elicit desired responses from ChatGPT. They will also be able to apply these techniques in a variety of real-world scenarios.

  • Basic usage and integration
  • Advanced usage and customization
  • Real-world applications and case studies
  • Best practices and considerations for deployment
  • Discussion and Q&A with industry experts
  • Next steps and opportunities for collaboration
Introduction to Prompt Engineering
• Understanding the power of prompts in ChatGPT
• Basic principles of good prompt design
• Case Study: Evaluating simple, basic prompts

Diving Deeper into Prompt Structures
• Understanding the effects of verbosity, temperature and max tokens
• Instruction Following and Knowledge Retrieval Prompts
• Understanding the System Message for Context
• The Role of Repetition and Patterns in

Prompt Design
Advanced Techniques in Prompt Engineering
• Conversational Depth: Using the User Message and Assistant Message in Prompts
• Designing prompts for complex tasks
• Effectively leveraging the persona and personality traits in your prompts

Skills and Workflow
• Introduction to skill chains and workflows in prompts

AI Training Mastering Prompt Engineering for ChatGPT 2
• Creating a coherent workflow for your prompts
• Defining clear tasks in your prompts
• Case Study: Designing a prompt with a complex skill chain and workflow

Testing and Refining Prompts
• Iterative Prompt Engineering: Test, Evaluate, Improve
• Best practices for testing prompts
• Evaluating and refining your prompts based on outcomes
• Managing and correcting common errors in prompt design
• Predicting the Response to a Given Prompt

Real-world Applications of Prompt Engineering
• Prompt Engineering in Business (e.g., Customer Support, Sales); Creative Applications
(e.g., Writing, Brainstorming); Education and Training
• Using Prompts for Sentiment Analysis and Opinion Generation
• Hands-on: Create a prompt for a specific task
• Peer review: Evaluate and provide feedback on fellow students' prompts

Conclusion and Further Learning
• Recap of key learnings from the course
• Further resources for learning and mastering prompt engineering
• A Look into the Future: Exploring the Potentials of Next-Gen Prompt Engineering
• Final Q&A and course wrap-up

Throughout the course, each module will include:
• Theory: Lectures and readings that discuss the principles of prompt engineering.
• Examples and Demonstrations: Real-world examples of prompts, as well as
demonstrations of how to craft them.
• Practice: Hands-on exercises where learners can create and experiment with their own
prompts.
• Feedback and Review: Opportunities to get feedback on your prompts and understand the
logic behind their successes and failures.
• Discussion: Forums and Q&A sessions where learners can interact, share experiences, and
ask questions.
JBI training course London UK

Software Developers looking to integrate ChatGPT with Python or Java

5 star

4.8 out of 5 average

"I hadn't integrated Pandas with Python before joining my company. So it's very useful to consolidate my understanding of such skill via this course. The Jupyter notebooks provided will be a valuable resource for revising the materials and are really well laid out." 

JL, Data Analyst, Python for Data Science, March 2021

“JBI  did a great job of customizing their syllabus to suit our business  needs and also bringing our team up to speed on the current best practices. Our teams varied widely in terms of experience and  the Instructor handled this particularly well - very impressive”

Brian F, Team Lead, RBS, Data Analysis Course, 20 April 2022

 

Watch client feedback from Python training course: 

JBI training course London UK

Certification


Every delegate will be entitled to a certificate of achievement on completion of the course.

If you are missing your certificate - please use the link below to apply - you can also use this link to sign up for the JBI Training newsletter to receive technology tips directly from our instructors - Analytics, AI, ML, DevOps, Web, Backend and Security.
 



This training course provides an introduction to the core concepts of the Python language, ultimately focusing on Big Data Analytics and Machine Learning applications.

The first three days of the course introduce you to Python tools for data science, including how best to manipulate and visualise your data with Python's excellent library support.

The last two days move one step forward, providing an overview of Artificial Intelligence and Machine Learning with the purpose of implementing predictive analytics applications.

Practical exercises and interactive walk-throughs are used throughout, so attendees have the opportunity to apply the proposed concepts on real data science applications, from exploratory data analysis to predictive analytics.

Generative AI training teaches individuals and teams how to use AI systems that generate text, code, images, and other content — including tools such as ChatGPT, Claude, Gemini, and Microsoft Copilot. JBI's Generative AI training courses are suitable for business professionals, developers, analysts, managers, and technical leaders who want to use AI more effectively in their work, improve productivity, or build AI-powered applications and workflows.
Prompt engineering is the practice of designing and structuring inputs to AI language models to obtain accurate, relevant, and consistent outputs. Effective prompt engineering helps users get better results from AI tools, reduce errors and hallucinations, and build reliable AI-assisted workflows. JBI offers dedicated prompt engineering courses for general LLM use, ChatGPT-specific use, and advanced GPT and LLM applications.
Yes. All JBI Generative AI and LLM training courses are available as live online instructor-led sessions, with the same hands-on exercises and expert instruction as classroom delivery. Online training is available to delegates across the UK and internationally.
A Large Language Model (LLM) is an AI system trained on large amounts of text data to understand and generate human language. LLMs such as GPT-4, Claude, Llama, and Gemini are the foundation of modern generative AI tools including ChatGPT and Microsoft Copilot. JBI's LLM training courses cover how LLMs work, their capabilities and limitations, how to use them effectively through prompt engineering, and how to build applications on top of LLM APIs.
Yes. All JBI Generative AI training courses can be delivered as bespoke closed-group programmes for corporate teams. Content is tailored to your team's role, existing AI experience, specific tools in use, and business objectives. JBI has delivered bespoke Generative AI and LLM training to teams in financial services, professional services, retail, media, the public sector, and technology organisations across the UK.
Retrieval-Augmented Generation (RAG) is a technique that enables AI language models to access and reason over external, up-to-date knowledge sources — such as internal documents, databases, or APIs — rather than relying solely on their training data. RAG is widely used to ground AI responses in factual, organisation-specific information. JBI covers RAG in several courses including Build Agentic AIs with Python, RAG and MCP and Build a Chatbot with Python, RAG and OpenAI.
Model Control Protocol (MCP) is an open standard for connecting AI models to tools, data sources, and external services in a structured and interoperable way. It provides a consistent interface for AI agents to access APIs, databases, file systems, and other resources. JBI offers a dedicated MCP training course covering server and client implementation, Claude API integration, and production deployment of MCP-enabled AI systems.
Yes. JBI Training offers a 3-day LangChain for AI Agents training course covering LLM workflow design, chain construction, agent development, memory systems, retrieval integration, and production deployment using the LangChain framework in Python. The course is designed for developers building LLM-powered applications and AI agent systems.
Prompt engineering focuses on crafting effective inputs to AI models to improve the quality and consistency of outputs — a skill relevant to any user of AI tools, technical or non-technical. Building AI applications with LLMs involves programming against model APIs, designing application architecture, managing context and memory, handling tool use and retrieval, and deploying AI-powered systems. JBI offers training for both — from introductory prompt engineering to advanced LLM application development.
Yes. JBI's Generative AI and LLM training range includes courses for complete beginners such as Harnessing Generative AI, Prompt Engineering for ChatGPT, and AI Prompt Engineering, which require no prior programming or AI experience. Developer-focused courses such as LangChain for AI Agents and Mastering LLMs require programming experience and prior familiarity with AI concepts. Each course page specifies the recommended experience level and prerequisites.
JBI Training regularly reviews and updates its Generative AI and LLM training content to keep pace with the rapid developments in this field. New model releases, updated prompt engineering best practices, emerging frameworks such as LangChain and MCP, and evolving governance requirements all feed into JBI's course refresh cycle. Whether you are learning about ChatGPT, Claude, Gemini, or open-source LLMs, JBI's training reflects how these tools are being used in practice today — not how they worked a year ago.

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