
Explore how ai-powered code generation and refactoring speed up development, with GitHub Copilot and Amazon Code Whisperer analyzing code context, suggesting lines and functions, and promoting cleaner, more efficient code.
Master crafting effective prompts for ai code generation by emphasizing clarity, specificity, and context, then iterate with feedback to produce high-quality, concise code solutions.
Learn how AI-powered debugging analyzes code, identifies issues, and suggests fixes to boost efficiency, reduce cognitive load, and improve code reliability through continuous improvement.
Create a login page with Client, follow installation steps, use the command palette to prompt 'creating a login page,' and launch a local server to preview the frontend.
Integrate ai-driven testing early, run automated tests through ci pipelines, and use ai in pull requests for automated checks and code reviews to detect security threats and anomalies.
Strengthen project success through concise, clear documentation that serves as a backbone, guiding new teammates and future changes with examples, use cases, and regular updates.
Develop accountability and transparency in AI development by documenting decision-making, clarifying what AI can and cannot do, auditing bias, and collaborating to ensure responsible, privacy-aware AI that benefits users.
In this intensive program, you will move beyond basic autocomplete. You will learn to orchestrate sophisticated AI agents like Cline and Copilot, mastering the art of "Vibe Coding"—a high-level, flow-state approach to rapid prototyping and system architecture. This course isn't just about writing code faster; it’s about rethinking the entire Software Development Lifecycle (SDLC) to be AI-first.
What You Will Master?
The curriculum is structured to take you from foundational prompting to executing complex, multi-file features with minimal manual intervention.
Foundations: The New Workflow & Prompting - Set up your agentic environment and master the linguistic precision required to "steer" LLMs.
Execution: Inline, Chat & Vibe Coding - Achieve fluid, in-IDE generation and learn to prototype at the speed of thought.
Optimization: Debugging, Security & QA - Use AI to diagnose "impossible" bugs and automate the generation of robust test suites.
Legacy & Ethics: Refactoring & Professionalism - Learn to clean up "spaghetti code" and navigate the ethical complexities of AI-generated intellectual property.
Course Goal:
To transform a traditional developer into a highly-efficient Agentic Developer by mastering advanced AI coding techniques, utilizing tools like copilot, Cline and dedicated coding environments, and applying sophisticated prompting strategies to manage the entire software development lifecycle.
Target Audience:
Developers and software engineers at various stages of their careers who want to leverage AI to drastically improve their efficiency and code quality.
Prerequisites:
Mandatory: Basic to intermediate proficiency in at least one modern programming language (e.g., Python, JavaScript, Java, C#) and familiarity with an IDE/code editor.
Recommended: Prior experience with version control (Git) and understanding of basic software development concepts.