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Course Outline
Introduction to Vibe Coding
- Definition and historical context of vibe coding
- The philosophy of “prompt-to-code” collaboration
- Distinguishing AI coding from traditional development methods
Large Language Models in Coding
- Overview of LLMs for developers: GPT-4, DeepSeek, Qwen, Mistral
- Comparison of open-source versus proprietary AI coders
- Deploying LLMs locally or through APIs
Prompt Engineering for Developers
- Techniques for effective prompting in code generation and refactoring
- Managing context and handling conversation state
- Developing reusable prompt templates for coding tasks
Hands-on Vibe Coding Environments
- Utilizing Replit for collaborative AI coding
- Integrating GitHub Copilot and Qwen Coder into IDEs
- Tailoring workflows for enhanced team collaboration
Code Quality and Validation in AI Workflows
- Reviewing and testing code generated by LLMs
- Maintaining consistency, maintainability, and security
- Incorporating code validation tools into the workflow
Enterprise Integration and Governance
- Scaling vibe coding practices across teams
- AI governance, ethics, and compliance in code generation
- Establishing organizational frameworks for AI-assisted development
Advanced Topics: Extending Vibe Coding
- Combining multiple LLMs for hybrid AI workflows
- Merging vibe coding with CI/CD automation
- Future trends: multi-agent development ecosystems
Team Project and Collaboration
- Designing a real-world AI-assisted coding project
- Collaborating with both human and AI developers
- Presenting outcomes and assessing productivity improvements
Summary and Next Steps
Requirements
- A solid grasp of software development workflows
- Proficiency in Python, JavaScript, or other contemporary programming languages
- Knowledge of Git-based version control systems
Intended Audience
- Software engineers exploring AI-assisted development
- Engineering leads managing AI adoption in coding processes
- Enterprise development teams aiming to integrate LLMs into production pipelines
21 Hours
Testimonials (2)
The session was highly interactive and applicable to the business.
Jorge Boscan - Chevron Global Technology Services Company
Course - Advanced GitHub Copilot & AI for Projects and Infrastructure
Machine Translated
That i gained a knowledge regarding streamlit library from python and for sure i'll try to use it to improve applications in my team which are made in R shiny