Duration 3 days – 21 hrs

 

Overview

 

This course equips software engineers and technical professionals with the skills to integrate AI tools into their development workflows. Participants will learn how to utilize AI coding assistants (e.g., ChatGPT, GitHub Copilot, Azure OpenAI) for code generation, refactoring, testing, documentation, and debugging. The program emphasizes responsible adoption—ensuring security, accuracy, and coding best practices while boosting team productivity, innovation, and delivery speed.

 

Objectives

 

• Use AI tools within IDEs and CI/CD for development acceleration
• Write effective prompts to generate secure, optimized, and maintainable code
• Automate documentation, testing, and code reviews with AI
• Validate and secure AI-generated code outputs
• Apply AI-assisted techniques to solve real-world programming challenges
• Boost delivery velocity and code consistency across teams

 

Target Audience 

 

• Software Developers / Engineers
• DevOps & Platform Engineers
• QA Automation Engineers
• Solutions Architects & Tech Leads
• Students transitioning into professional development roles
• Anyone adopting AI for coding productivity

 

Prerequisites 

• Basic programming knowledge (any language e.g., JavaScript, Python, Java, C#)

• Familiarity with Git and software development lifecycle

• Laptop with VS Code or preferred IDE installed

 

Course Outline 

 

Day 1 – AI-Assisted Development Foundations

 

• Evolution of AI in Software Engineering
• How Large Language Models (LLMs) Work for Coding
• AI Coding Assistants: Capabilities vs. Limitations
• Natural Language to Code Conversion

 

Hands-On Labs:

 

• Generating functions and scripts
• Debugging with AI suggestions
• Inline code completion and real-time guidance in IDEs

 

Day 2 – Prompt Engineering for Developers

• Prompt Patterns for:

• CRUD operations
• API integration
• Unit tests generation
• Database queries & schema creation
• UI development scenarios

 

• Refactoring & Code Optimization with AI
• Multi-step Prompting for complex programming tasks
• Automating Documentation & Comments

 

Hands-On Labs:

 

• Transforming requirements into working code
• Prompting for multiple languages (Python, JavaScript, Java, C#)
• Performance and algorithm optimization using AI

 

Day 3 – Secure Integration & Workflow Automation

• Code Security & Validation of AI-Generated Code

• Vulnerability scans
• Dependency management
• Secure coding checklists

 

• AI-Enhanced CI/CD & DevOps Autonomy
• AI-Driven Code Review and Testing Automation
• Collaboration with AI for Architectural Design

 

Hands-On Capstone Project:

 

• Build feature → Generate tests → Deploy with automation
• Team exercise using AI for solution brainstorming and code quality checks