FeaturedUdemy
AI-Assisted Coding for Developers
4.8(1,061)7k studentsINTERMEDIATEEnglish
Korshub's take
The Korshub Take
This intermediate course focuses on the art and science of prompt engineering specifically tailored for software development. It demonstrates how to leverage Large Language Models (LLMs) to dramatically boost productivity across the coding lifecycle while maintaining secure and responsible practices.
Who It's For
Developers who want to effectively integrate AI coding assistants into their daily workflow to write, debug, and maintain code more efficiently.
Key Takeaways
- Prompt Engineering for Code: Understand how context shapes LLM outputs and learn to iteratively refine prompts for accurate, reliable coding results.
- Workflow Integration: Apply advanced prompting strategies for everyday tasks like debugging, generating tests, and improving documentation.
- Security Best Practices: Guide AI models to avoid common vulnerabilities and align generated code with established software development standards.
- Model Selection & Ethics: Evaluate different LLMs to balance speed, cost, and quality, while implementing guardrails for safe and responsible AI usage.
About this course
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.Advertisement
