Course
AI-Assisted Coding for Developers
IntermediateSkill Level
Updated 08/2025TheoryArtificial Intelligence1 hr 30 min10 videos28 Exercises1,850 XP4,762Statement of Accomplishment
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Code Smarter with AI
AI is transforming the way developers write, debug, and maintain code. From generating functions to improving documentation and catching bugs, AI coding assistants can dramatically boost productivity—if you know how to prompt them effectively. This course teaches you the art and science of prompt engineering for coding, giving you the tools to harness AI responsibly and efficiently.Unlock the Power of AI in Development
You’ll begin by exploring how large language models (LLMs) support software development. Learn the fundamentals of prompt engineering, how context shapes AI outputs, and how to iteratively refine prompts for more accurate, reliable results.Apply Prompt Engineering to Real-World Coding Tasks
Next, you’ll practice advanced prompting strategies for debugging, documentation, and test generation. You’ll also discover how to guide models to improve security, ensuring your AI-assisted workflows avoid common vulnerabilities and support best practices in software development.Build Robust and Responsible Code
Finally, you’ll evaluate different models to choose the right tool for each task, balance speed, cost, and quality, and apply guardrails to ensure safe and ethical AI use. By the end, you’ll be able to leverage AI-powered coding assistants securely and tailor them to your needs.Prerequisites
Intermediate Python1
Unlocking the Power of AI in Code
Learn how AI models enhance coding through completion, debugging, and documentation. Master the basics of prompt engineering and discover how context makes AI responses smarter. This chapter sets the foundation for using AI as a practical coding assistant.
2
Prompt Engineering for Real-World Coding Tasks
Learn how to craft prompts that guide models through complex reasoning, document code effectively, and generate test-driven implementations. By the end of this chapter, you’ll be able to design prompts that improve both the quality of generated code and your overall development workflow.
3
Building Robust AI Coding Workflows
Go beyond prompt crafting in this chapter, and into the practical realities of running AI in production. Explore how to compare and select models based on performance, cost, and task fit; how to embed guardrails that keep outputs safe and compliant; and how to fine-tune workflows for efficiency without sacrificing quality.
AI-Assisted Coding for Developers
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FAQs
Is this course about a specific AI coding tool?
No. This is a theory course that teaches prompt engineering techniques applicable across AI coding assistants, rather than focusing on one specific tool.
What prior programming experience do I need?
You should know basic and intermediate Python. The course builds on your existing coding skills and teaches you to use AI to write, debug, and document code.
What practical coding tasks does this course address?
You will learn to use AI for writing cleaner code, debugging faster, generating documentation, creating test-driven implementations, and securing applications.
What will I learn about prompt engineering?
You will learn to craft precise prompts, use chain-of-thought reasoning, and design prompts that guide AI models through complex coding tasks effectively.
How long does this course take?
The course has 3 chapters and 28 exercises. Most learners complete it in about 1 to 1.5 hours.
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