Cursusaanbod
Introduction to Vibe Coding
- Definition and history of vibe coding
- Philosophy of “prompt-to-code” collaboration
- How AI coding differs from traditional development
Large Language Models in Coding
- Overview of LLMs for developers: GPT-4, DeepSeek, Qwen, Mistral
- Comparing open-source vs. proprietary AI coders
- Deploying LLMs locally or via APIs
Prompt Engineering for Developers
- Effective prompting for generating and refactoring code
- Context management and conversation state handling
- Creating reusable prompt templates for coding tasks
Hands-on Vibe Coding Environments
- Using Replit for collaborative AI coding
- Integrating GitHub Copilot and Qwen Coder into IDEs
- Customizing workflows for team collaboration
Code Quality and Validation in AI Workflows
- Reviewing and testing LLM-generated code
- Ensuring consistency, maintainability, and security
- Integrating code validation tools in the workflow
Enterprise Integration and Governance
- Scaling vibe coding across teams
- AI governance, ethics, and compliance in code generation
- Designing organizational frameworks for AI-assisted development
Advanced Topics: Extending Vibe Coding
- Combining multiple LLMs for hybrid AI workflows
- Integrating 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 human and AI developers
- Presenting results and measuring productivity gains
Summary and Next Steps
Vereisten
- An understanding of software development workflows
- Experience with Python, JavaScript, or another modern programming language
- Familiarity with Git-based version control systems
Audience
- Software engineers exploring AI-assisted development
- Engineering leads overseeing AI adoption in coding workflows
- Enterprise development teams seeking to integrate LLMs into production pipelines
Leveringsopties
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