Packt

Advanced Prompting & AI Tooling

Packt

Advanced Prompting & AI Tooling

Included with Coursera Plus

Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Master advanced techniques in prompt engineering, including "Flip the Script" and self-consistency.

  • Develop AI-powered tools like code reviewers using Git and advanced error handling techniques.

  • Implement function calling and self-critique workflows to refine AI output.

  • Design structured outputs and manage data effectively for complex AI applications.

Details to know

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Recently updated!

March 2026

Assessments

5 assignments

Taught in English

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Build your subject-matter expertise

This course is part of the Prompt Engineering Masterclass - From Beginner to Advanced Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 3 modules in this course

In this module, we will explore advanced prompt engineering techniques designed to optimize model behavior. You'll learn how to apply dynamic patterns like "Flip the Script," use function calling within prompts, and enhance responses using self-consistency. Practical labs will allow you to apply these concepts in real-time to refine your skills.

What's included

11 videos2 readings1 assignment

In this module, we will work on building an AI-powered code reviewer. You’ll learn how to use the GitPython library for code interaction, develop expert personas for deeper analysis, and refine your tool’s logic with self-consistency techniques. This module provides a comprehensive approach to creating a tool that can review code effectively.

What's included

20 videos1 assignment

In this final module, we will guide you through the process of structuring the output of your AI-powered code reviewer, ensuring better data management. You'll refactor your tool for maintainability, fix any remaining bugs, and complete the project by adding final touches, such as building a JSON output parser and documenting the tool for future users.

What's included

13 videos1 reading3 assignments

Earn a career certificate

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Instructor

Packt - Course Instructors
Packt
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