For Business
.NET Developer Productivity with AI: Copilots, Automation, and Intelligent Workflows
Certificate of Completion by Code.Hub
This training equips .NET developers with the skills to leverage Generative AI tools and copilots to significantly enhance productivity across the software development lifecycle. Participants will explore how AI-assisted coding tools such as GitHub Copilot integrate with Visual Studio to accelerate development, improve code quality, and reduce repetitive tasks. The course covers intelligent code generation, refactoring, testing automation, and documentation using AI. It also introduces the design of AI-powered workflows within .NET applications, including integration with LLMs, APIs, and orchestration layers. Hands-on labs demonstrate how to build intelligent features such as natural language interfaces, automated decision services, and smart assistants within enterprise applications. Emphasis is placed on maintainability, security, and responsible AI usage in production environments. By the end of the training, participants will be able to augment their development processes and applications with AI-driven capabilities.
By the end of this module, participants will be able to:
- Use AI copilots to accelerate coding, debugging, and refactoring in .NET environments
- Automate testing, documentation, and code generation workflows using AI tools
- Integrate LLM capabilities into .NET applications via APIs and SDKs
- Design intelligent application features such as assistants and decision-support components
- Apply best practices for secure, maintainable, and production-ready AI-augmented systems
AI-Augmented Development
Foundations of AI in Development
- Overview of AI in software engineering, productivity impact, introduction to GitHub Copilot
AI Practice: AI-assisted Git/Copilot setup
Code Generation Techniques
- Writing effective prompts/comments, generating methods, APIs, refactoring patterns using AI
AI Practice: AI-assisted Development of boiler plate code
AI-Assisted Coding
Hands-on ASP.NET Core Development
- Building Web API endpoints, improving code structure and speed
AI Practice: Design and evaluation using Gen AI tools
Code Understanding & Bug Detection
- Explaining code, identifying issues, root cause analysis using AI tools
AI Practice: Using to evaluate code, provide suggestions, Critique Design
Documentation Automation
AI-Generated Documentation
- Creating API documentation, summarizing codebases, generating technical explanations
AI Practice: Using AI to create documentation and explanations
Testing with AI
Automated Test Generation
- Generating unit and integration tests, identifying edge cases, improving coverage
AI Practice: Using AI to create tests from code and code from tests
Developer Copilots
Automated Test Generation
- Generating unit and integration tests, identifying edge cases, improving coverage
AI Practice: Using AI to create tests from code and code from tests
Security in AI Development
Responsible AI Usage
- Risks (code leakage, prompt injection), secure usage patterns and guidelines
AI Practice: Best practices in AI secure usage
Optimization & Best Practices
Efficient AI Usage
- AI optimization, when to use AI vs manual coding, reducing noise and cost
AI Practice: Estimation and management of AI costs
Roles:
- .NET Developer
- Software Engineer
- Technical Lead
Seniority:
- Mid to Senior Level
- Solid experience with C# and the .NET ecosystem including Visual Studio and basic application architecture
- Familiarity with REST APIs and general software development lifecycle practices
Sessions can be delivered via the following formats:
- Live Online – Interactive virtual sessions via video conferencing
- On-Site – At your organization’s premises
- In-Person – At Code.Hub’s training center
- Hybrid – A combination of online and in-person sessions

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