Packt

Prompt Engineering Masterclass - From Beginner to Advanced Specialization

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Packt

Prompt Engineering Masterclass - From Beginner to Advanced Specialization

Master Prompt Engineering for AI Solutions.

Design AI tools, control model behavior, and optimize outputs for real-world applications.

Included with Coursera Plus

Get in-depth knowledge of a subject
Intermediate level

Recommended experience

4 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Get in-depth knowledge of a subject
Intermediate level

Recommended experience

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

What you'll learn

  • Master the essential techniques for effective prompt engineering with LLMs.

  • Build and deploy functional AI tools using OpenAI and Anthropic models.

  • Gain hands-on experience with real-world AI applications and projects.

  • Understand and control the key parameters that drive AI behavior and responses.

Details to know

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Taught in English
Recently updated!

March 2026

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Specialization - 3 course series

Prompt Engineering Foundations

Prompt Engineering Foundations

Course 1 5 hours

What you'll learn

  • Gain hands-on experience in prompt engineering and its applications in AI.

  • Set up local Python environments and API keys for interacting with AI models.

  • Learn how to make API calls and manage outputs effectively for real-time responses.

  • Build AI-powered tools and command-line interfaces using modern libraries and frameworks.

What you'll learn

  • Master the core concepts of large language models and their applications.

  • Build structured prompts and leverage advanced techniques like few-shot and chain-of-thought prompting.

  • Develop AI-powered tools for real-world scenarios, such as Git commit message generation.

  • Optimize API usage and manage costs efficiently in large-scale AI applications.

Advanced Prompting & AI Tooling

Advanced Prompting & AI Tooling

Course 3 10 hours

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.

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Instructor

Packt - Course Instructors
Packt
1,566 Courses 441,543 learners

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Packt

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