Prompt Engineering Masterclass - From Beginner to Advanced

Packt via Coursera Specialization

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Provider

Coursera Specialization
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 10 hours/week
Level

Intermediate

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This specialization features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress. You’ll master prompt engineering and work with large language models (LLMs). Starting with the basics, you will learn to build AI tools, design prompts, and understand LLM mechanisms using OpenAI and Anthropic models. The journey starts with setting up your environment and learning the OpenAI Python library. You’ll then build AI-powered tools like a Git commit message generator and an AI code reviewer, reinforcing concepts such as managing model responses, controlling output, and handling costs. This specialization is ideal for anyone interested in AI and machine learning. Basic Python knowledge is helpful. By the end, you’ll be able to craft effective prompts, design AI tools, and create real-world AI applications.

Syllabus

Course 1: Prompt Engineering Foundations
Course 2: Build with LLMs: Prompt Engineering & Real AI Projects
Course 3: Advanced Prompting & AI Tooling

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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this advanced course, you'll deepen your expertise in prompt engineering and learn how to craft highly effective prompts for sophisticated AI models. The course covers a range of advanced techniques, such as the "Flip the Script" pattern, self-consistency, function calling, and more. With practical labs, you’ll experiment with these techniques, refining AI-generated prompts, and building more dynamic, flexible, and high-performing AI systems. You'll also dive into function calling and applying it to real-world tasks, as well as improving response quality through decomposition and self-critique. The course also includes a comprehensive project where you will build an AI-powered code reviewer, allowing you to apply your prompt engineering skills in a practical setting. Throughout the project, you’ll enhance the tool with features like Git integration, code logic and syntax checking, self-critique, and the creation of expert personas. The project will culminate with the migration to structured output, improving the tool’s data management and its interaction with other systems. This course is ideal for learners who have a solid understanding of AI models and prompt engineering, and wish to take their skills to the next level by designing more powerful, efficient, and customized AI-driven tools. The course requires experience in programming and basic familiarity with AI principles. By the end of the course, you will be able to build sophisticated AI-powered tools, refine and optimize prompts for complex tasks, and integrate advanced techniques like function calling and self-consistency into your AI systems.
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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. This intermediate-level course dives deep into the essential techniques for working with large language models (LLMs), providing you with the practical tools and knowledge needed to build powerful AI applications. You will learn core concepts such as tokenization, log probabilities, and context windows, and gain hands-on experience through a series of engaging labs and projects. Additionally, you'll explore foundational prompt engineering patterns to improve response accuracy, control output formats, and develop advanced techniques such as few-shot prompting and chain-of-thought prompting. The course is structured to guide you from understanding the theoretical underpinnings of LLMs to applying those concepts in real-world scenarios. As you progress, you will work on an exciting project, building an AI-powered Git commit message generator. Through this project, you'll gain valuable experience in designing prompt templates, creating core logic for AI commits, and enhancing functionality with user reviews and model selection. Each section includes practical labs and exercises that ensure you're not just learning the theory, but also building real skills. The course is perfect for intermediate learners looking to enhance their AI development capabilities, particularly those interested in applying prompt engineering to optimize model behavior. A solid understanding of programming and LLMs is beneficial, but anyone with a technical background will find this course accessible. By the end of the course, you will be able to design structured prompts, implement advanced prompting techniques, generate AI-driven Git commit messages, and effectively manage API usage and costs.
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This course features Coursera Coach! A smarter way to learn with interactive, real-time conversations that help you test your knowledge, challenge assumptions, and deepen your understanding as you progress through the course. In this comprehensive course, you will gain a solid foundation in prompt engineering, learning how to work with large language models (LLMs) effectively. You'll explore the power of prompt engineering and how to build AI-powered tools by interacting with APIs such as OpenAI and Anthropic. Through real-world examples and hands-on projects, this course will help you master the art of developing prompts that maximize the capabilities of AI models. As you move through the course, you will be guided step by step through key concepts, including setting up development environments, making your first API calls, and managing API costs. You will also delve into advanced techniques for controlling output, managing authentication, and optimizing large language models for real-time applications. Each section is designed to build your skills progressively, ensuring that you gain the practical experience needed to excel. The course culminates in a project where you will apply what you’ve learned by creating your own AI-powered tools using the skills and knowledge gained throughout the course. By the end of the course, you will have built the foundation for an AI toolbox and will have the expertise to use prompt engineering in your own projects. This course is ideal for anyone interested in learning prompt engineering, whether you're an aspiring AI developer, a data scientist, or someone who wants to gain hands-on experience in using APIs for AI-driven applications. It requires a basic understanding of programming but is accessible to beginners with a technical background. By the end of the course, you will be able to set up your development environment, make API calls, use the OpenAI Python library, build command-line interfaces, and create AI-powered tools using best practices.