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.

The Generative AI Course Group includes training across key areas such as: Generative AI Fundamentals – Understand the capabilities, applications, and impact of Generative AI Prompt Engineering – Learn how to create effective prompts and optimise AI model responses Large Language Models (LLMs) – Understand and develop applications using modern AI language models ChatGPT Development – Build AI-powered applications using ChatGPT and LLM APIs AI Application Development – Create practical solutions powered by Generative AI Retrieval-Augmented Generation (RAG) – Build AI systems that can search, retrieve, and use your own data AI Chatbots and Assistants – Develop intelligent conversational applications LLM Frameworks and Tools – Work with technologies used to build real-world GenAI solutions
During the courses, you will work with technologies and concepts including: Large Language Models (LLMs) OpenAI models and APIs ChatGPT Anthropic Claude Prompt Engineering Retrieval-Augmented Generation (RAG) Vector Databases Embeddings Python for AI Development AI Application Frameworks APIs and AI integrations Responsible AI practices
After completing the courses in this group, you will be able to build a range of Generative AI solutions, including: AI-powered chatbots and virtual assistants Applications using Large Language Models Knowledge assistants using RAG AI tools connected to business data and APIs Automated content and productivity solutions Intelligent applications that understand and generate text Custom AI solutions for business and enterprise use cases You will gain the practical skills needed to design, develop, and deploy modern Generative AI applications.
The Generative AI Course Group is a collection of multiple professional training courses focused on Generative AI technologies. It provides a structured learning pathway covering everything from GenAI fundamentals and prompt engineering to advanced LLM application development.
The group includes multiple Generative AI courses covering areas such as: Generative AI fundamentals Prompt engineering ChatGPT development Large Language Models (LLMs) AI application development Retrieval-Augmented Generation (RAG) AI chatbots and assistants
This is a course group containing multiple related Generative AI courses. Each course focuses on a specific technology or skill area, allowing you to build knowledge progressively across the GenAI ecosystem.
No. The course group includes beginner-friendly foundation courses as well as more advanced technical courses. Basic programming knowledge is recommended for development-focused courses.
Yes. Developers will learn how to build AI-powered applications using LLMs, APIs, RAG, and modern Generative AI development techniques.

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