ChatGPT Prompt Engineering for Developers

OVERVIEW
Building Strategic Influence in Matrix Organizations

The ChatGPT prompt engineering course aims to help developers leverage large language models to build powerful new applications and capabilities that can learn to innovate and create value in ways that were until now cost-prohibitive, highly technical, or impossible. This prompt engineering course for ChatGPT discusses how LLMs work, best practices for prompt engineering, and how LLM APIs can be used in applications for accomplishing different tasks. This comprehensive ChatGPT prompt engineering for developers course will guide participants through the principles of writing effective prompts, systematic prompt engineering, and building a custom chatbot. It will cover a wide array of topics, ensuring participants gain a robust understanding and hands-on experience in various facets of ChatGPT and prompt engineering. The ChatGPT prompt engineer course is enriched with detailed modules on Function Calling, Custom Instructions, Fine Tuning, API, OpenAI Playground, and Models, ensuring participants are abreast with the latest advancements and features.

WHAT YOU'LL LEARN
Why you shouldn't miss this course

By the end of this course, participants will have the leadership toolkit to shape and steer GenAI portfolios across their organization.

01Understand the workings of Large Language Models.
02Master the art of prompt engineering.
03Gain insights into summarizing, inferring, transforming, and expanding text using LLMs.
04Build a custom chatbot, OrderBot, understanding the chat format and customization.
05Explore and implement Function Calling and Custom Instructions in ChatGPT.
06Hands-on experience with Fine Tuning, API, and OpenAI Playground.
07Deep dive into various Models, understanding their architecture and functionalities.

PREREQUISITES
Recommended experience

CURRICULUM
Structured for
Strategic Application

In this module, participants will be introduced to the world of Large Language Models, laying the foundation for understanding their architecture and functionalities.

Lessons:

  • Overview of Large Language Models.
  • Introduction to the OpenAI API.
  • Understanding the Significance of Large Language Models in AI.

Lab:

  • Hands-on session: Exploring various Large Language Models.
  • Interactive exercises: Working with the OpenAI API.

After completing this module, students will be able to:

  • Understand the basic concepts of Large Language Models.
  • Gain insights into the architecture and functionalities of various models.

This module will delve into the world of prompting, offering participants a comprehensive understanding of their functionality and application.

Lessons:

  • Introduction to Guidelines for Prompting.
  • Exploring the Principles of Writing Clear and Specific Instructions.
  • Understanding Model Limitations: Hallucinations.

Lab:

  • Hands-on workshop: Working with effective prompting.
  • Interactive exercises: Identifying and mitigating model limitations.

After completing this module, students will be able to:

  • Understand the concept and application of effective prompting.
  • Gain hands-on experience with writing clear and specific instructions.

In this module, participants will learn the techniques for iterative prompt development and how to address various issues that may arise.

Lessons:

  • Introduction to Iterative Prompt Development.
  • Handling Issues: Text Length, Focus Details, and Table of Dimensions.

Lab:

  • Hands-on workshop: Developing and refining prompts iteratively.
  • Interactive exercises: Addressing issues in prompt development.

After completing this module, students will be able to:

  • Understand and apply iterative prompt development techniques.
  • Efficiently handle and resolve issues in prompt development.

This module will explore various summarizing techniques, focusing on different aspects such as shipping, delivery, price, and value.

Lessons:

  • Techniques for Effective Text Summarization.
  • Summarization with a Focus on Specific Aspects.

Lab:

  • Hands-on session: Practicing summarization techniques.
  • Interactive exercises: Focusing summarization on specific aspects.

After completing this module, students will be able to:

  • Master various text summarization techniques.
  • Effectively summarize text with a focus on specific aspects.

Participants will delve into the techniques for inferring topics and creating news alerts for certain topics in this module.

Lessons:

  • Introduction to Topic Inferring.
  • Creating News Alerts for Specific Topics.

Lab:

  • Hands-on workshop: Working with topic inferring.
  • Interactive exercises: Creating and customizing news alerts.

After completing this module, students will be able to:

  • Understand and apply topic inferring techniques.
  • Create customized news alerts for specific topics.

This module will cover various text transformation techniques including translation, tone transformation, and format conversion.

Lessons:

  • Exploring Various Text Transformation Techniques.
  • Deep Dive into Translation, Tone Transformation, and Format Conversion.

Lab:

  • Hands-on session: Practicing text transformation techniques.
  • Interactive exercises: Working with translation, tone transformation, and format conversion.

After completing this module, students will be able to:

  • Master various text transformation techniques.
  • Efficiently translate, transform tone, and convert formats of texts.

In this module, participants will learn techniques for effectively expanding text and customizing automated replies to customer emails.

Lessons:

  • Techniques for Effective Text Expansion.
  • Customizing Automated Replies to Customer Emails.

Lab:

  • Hands-on session: Practicing text expansion techniques.
  • Interactive exercises: Customizing automated email replies.

After completing this module, students will be able to:

  • Master various text expansion techniques.
  • Customize automated replies effectively.

In this module, participants will delve into the world of OpenAI embeddings, understanding their significance and application in various tasks.

Lessons:

  • Introduction to OpenAI Embeddings.
  • Understanding the Applications and Use Cases of OpenAI Embeddings.

Lab:

  • Hands-on session: Working with OpenAI Embeddings.
  • Interactive exercises: Experimenting with various embedding techniques.

After completing this module, students will be able to:

  • Understand the concept and application of OpenAI Embeddings.
  • Gain hands-on experience with OpenAI Embeddings.

This module will introduce participants to function calling in ChatGPT, enhancing their understanding and skills.

Lessons:

  • Overview of Function Calling in ChatGPT.
  • Practical Applications of Function Calling.

Lab:

  • Hands-on session: Exploring function calling in ChatGPT.
  • Interactive exercises: Implementing function calling in tasks.

After completing this module, students will be able to:

  • Understand the concept of function calling in ChatGPT.
  • Apply function calling effectively in various tasks.

Participants will explore custom instructions in ChatGPT in this module, gaining insights into their utilization for enhanced task performance.

Lessons:

  • Introduction to Custom Instructions in ChatGPT.
  • Utilizing Custom Instructions for Task Enhancement.

Lab:

  • Hands-on workshop: Working with custom instructions in ChatGPT.
  • Interactive exercises: Enhancing tasks using custom instructions.

After completing this module, students will be able to:

  • Understand the use of custom instructions in ChatGPT.
  • Effectively utilize custom instructions for various tasks.

In this module, participants will delve into the world of fine-tuning in ChatGPT, enhancing their models for optimal performance.

Lessons:

  • Overview of Fine-Tuning in ChatGPT.
  • Techniques for Effective Fine-Tuning.

Lab:

  • Hands-on session: Practicing fine-tuning techniques in ChatGPT.
  • Interactive exercises: Enhancing model performance through fine-tuning.

After completing this module, students will be able to:

  • Understand the concept of fine-tuning in ChatGPT.
  • Apply effective fine-tuning techniques for optimal model performance.

In this module, participants will delve into the integration of ChatGPT using JavaScript. This module will enhance their skills in integrating ChatGPT into web projects and applications, ensuring seamless interaction and functionality.

Lessons:

Introduction to ChatGPT Integration in JavaScript.

  • Working with ChatGPT: Sending Requests and Handling Responses in JavaScript.
  • Best Practices for ChatGPT Integration in JavaScript.

Lab:

  • Hands-on session: Setting up and integrating ChatGPT in a JavaScript environment.
  • Interactive exercises: Crafting and sending requests to ChatGPT and handling the responses effectively in JavaScript.

After completing this module, students will be able to:

  • Successfully integrate ChatGPT into web projects using JavaScript.
  • Understand the intricacies of working with ChatGPT in a JavaScript environment.
  • Apply best practices for efficient and effective ChatGPT integration in JavaScript projects.

Participants will explore the OpenAI Playground in this module, understanding its features and benefits.

Lessons:

  • Overview of the OpenAI Playground.
  • Benefits and Features of Using the OpenAI Playground.

Lab:

  • Hands-on session: Navigating the OpenAI Playground.
  • Interactive exercises: Working with features of the OpenAI Playground.

After completing this module, students will be able to:

  • Understand the OpenAI Playground and its functionalities.
  • Effectively use the OpenAI Playground for various tasks.

This module will focus on the critical aspect of data privacy in working with ChatGPT and other language models.

Lessons:

  • Overview of Data Privacy Concerns in Language Models.
  • Best Practices for Ensuring Data Privacy.

Lab:

  • Interactive session: Discussing real-world scenarios and solutions for data privacy.
  • Hands-on exercises: Implementing data privacy best practices.

After completing this module, students will be able to:

  • Understand the importance of data privacy.
  • Implement best practices for ensuring data privacy in their projects.

In this module, participants will explore the process of creating a chatbot, focusing on the ChatGPT platform.

Lessons:

  • Overview of Chatbot Creation.
  • Steps and Best Practices in Creating a Chatbot with ChatGPT.

Lab:

  • Hands-on session: Building a basic chatbot using ChatGPT.
  • Interactive exercises: Experimenting with chatbot features and functionalities.

After completing this module, students will be able to:

  • Understand the process of chatbot creation.
  • Build a basic chatbot using ChatGPT.

This module will delve deeper into the chatbot creation, focusing on creating a specific type of chatbot – OrderBot.

Lessons:

  • Understanding Advanced Features of Chatbots.
  • Detailed Steps in Creating OrderBot.

Lab:

  • Hands-on workshop: Creating OrderBot with advanced features.
  • Interactive exercises: Working with OrderBot and understanding its advanced functionalities.

After completing this module, students will be able to:

  • Understand advanced features of chatbots.
  • Create and work with an advanced OrderBot.

This concluding module will summarize the key learnings from the course and discuss potential future explorations in the field of ChatGPT and prompt engineering.

Lessons:

  • Summary of Key Learnings from the Course.
  • Discussion on Future Explorations in ChatGPT and Prompt Engineering.

Lab:

  • Interactive session: Review and reflection on the course learnings.
  • Group discussions: Sharing insights and future aspirations in the field.

After completing this module, students will be able to:

  • Summarize the key learnings from the course.
  • Discuss potential future explorations in ChatGPT and prompt engineering.

RECOMMENDED PARTICIPANT SETUP
This course follows Cognixia's AI-first,
hands-on learning model

Access to sanitized process maps, KPI definitions, candidate initiative lists, and basic cost baselines (time, cycle time, error or rework rates)

INTERESTED IN THIS COURSE?
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Speak with a Cognixia specialist about enrollment options, custom cohorts for your leadership team, or tailored delivery formats for your organization.

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Available in 5 delivery formats globally
Volume pricing for teams of 10+
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FAQs
Frequently
Asked Questions

Find details on duration, delivery formats, customization options, and post-program reinforcement.

Generative AI is a subset of AI that focuses on understanding patterns and structure in data and then using that to create more data like it.

Until now, machines couldn’t exhibit behavior that was indistinguishable from human responses. Generative AI has made that possible. In a world that operates on the principle of ‘Survival of the Fittest’, embracing Generative AI could be the edge you need to boost your productivity, improve operations, be more reliable and consistent, and do so much more.

Prompt engineering is a technique for refining large language models using specific prompts to get the desired outputs. Simply put, prompt engineering is the technique of writing specific effective prompts to get the desired outputs from Generative AI tools.

A prompt engineer is a person who uses prompt engineering techniques to get the desired outputs from Generative AI tools.

24 Hours

Yes, absolutely! The prompt engineering for ChatGPT online course is a virtual, instructor-led program so you can enroll and learn from anywhere.

This ChatGPT prompt engineering course is designed to be highly hands-on for all learners. Roughly 70% of this course would be hands-on practical training while 30% would be theoretical studies.

Yes! Every module will be pre- and post-assessed during this Prompt Engineering for ChatGPT online training course.

WHY COGNIXIA
Why Cognixia for This Course

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