ai-for-developers – Aissistance

Ai for Developers

This course is designed for software developers, architects, and engineers, focusing on practical skills to integrate AI tools and techniques into the software development lifecycle, enhancing productivity and quality.

Session 1: Introduction to AI for Developers (9:00 AM – 10:30 AM)

Overview of AI and Generative AI relevant to software development.

Understanding how AI can enhance developer productivity (code generation, debugging, testing).

Introduction to key AI models and frameworks for developers (e.g., LLMs, Transformers, basic understanding of TensorFlow/PyTorch).

Ethical considerations and risks when using AI in development.

Session 2: Prompt Engineering for Code & Hands-on Tools (10:45 AM – 12:30 PM)

Fundamentals of prompt engineering for code generation (e.g., Python functions, SQL queries).

Using AI tools for code explanation, refactoring, and documentation.

Hands-on: Practical exercises with AI coding assistants (e.g., GitHub Copilot, Google Gemini Code Assist, or similar playground environments).

Lunch Break (12:30 PM – 1:30 PM)

Session 3: AI for Software Quality & Troubleshooting (1:30 PM – 3:00 PM)

Leveraging AI for automated testing and test case generation.

AI-driven debugging and troubleshooting: analyzing logs and identifying root causes.

Introduction to AI for security vulnerability detection.

Hands-on: Applying AI tools to analyze code snippets for potential issues or generate basic test cases.

Session 4: Integrating AI into Development Workflows & Future Trends (3:15 PM – 4:30 PM)

Best practices for integrating AI tools into existing CI/CD pipelines.

Overview of MLOps concepts and model deployment considerations for developers.

Discussion on emerging AI trends impacting software development (e.g., AI agents, low-code/no-code AI platforms).

Q&A and course wrap-up.