Description

Introduction
This training provides a comprehensive understanding of how Generative AI can enhance the Software Development Life Cycle (SDLC) by improving requirements gathering, accelerating development, optimizing QA, and automating documentation. Participants will learn how to integrate Gen AI tools into every SDLC phase to increase productivity, reduce errors, and deliver high-quality software faster.

Prerequisites
Basic understanding of SDLC concepts
Familiarity with software development or QA processes
General awareness of AI/Gen AI tools (preferred but not mandatory)

Table of Contents
1. Understanding Gen AI in SDLC
 1.1 What is Generative AI and Its Capabilities
 1.2 Traditional SDLC vs AI-Enhanced SDLC
 1.3 Use Cases of Gen AI Across Each SDLC Phase
 1.4 Benefits and Challenges of Using Gen AI in Software Projects
2. Gen AI for Requirements Engineering
 2.1 AI-Driven Requirements Gathering Techniques
 2.2 Converting Business Needs into User Stories Using AI
 2.3 Automated Requirement Validation and Gap Analysis
 2.4 Generating Functional & Non-Functional Requirements with Gen AI
3. Gen AI in System Design & Architecture
 3.1 AI-Assisted Architectural Diagrams & System Blueprints
 3.2 Intelligent Design Pattern Recommendations
 3.3 Generating Data Models, ER Diagrams & API Specs
 3.4 Validating Architecture for Scalability & Performance with AI
4. Accelerating Development with Generative AI
 4.1 AI-Based Code Generation & Refactoring Techniques
 4.2 Using AI for Debugging, Optimization & Code Reviews
 4.3 Creating Stubs, Mocks & Reusable Components Automatically
 4.4 Applying Gen AI for Secure Coding Practices
5. Gen AI for Testing & QA Optimization
 5.1 Test Scenario, Test Case & Test Data Generation Using AI
 5.2 Automated Bug Detection & Resolution Recommendations
 5.3 AI-Driven Regression, Performance & Security Testing Support
 5.4 Building Intelligent QA Dashboards & Defect Predictions
6. Gen AI for DevOps & Release Automation
 6.1 AI-Enhanced CI/CD Pipelines
 6.2 Proactive Risk Identification During Deployments
 6.3 Intelligent Configuration & Release Notes Generation
 6.4 Monitoring, Alerts & Incident Prediction Using AI
7. Gen AI for Documentation & Knowledge Management
 7.1 Auto-Generating Technical Documentation & User Manuals
 7.2 AI-Supported API Documentation & Change Tracking
 7.3 Streamlining Knowledge Base & SOP Creation
 7.4 Documenting Code, Architecture & QA Assets with AI
8. Governance, Ethics & Best Practices for Gen AI in SDLC
 8.1 Data Privacy, Security & Compliance Considerations
 8.2 Responsible Use of Gen AI in Development Teams
 8.3 Accuracy, Verification & Human-in-the-Loop Principles
 8.4 Choosing the Right Gen AI Tools & Adoption Framework
9. Hands-On Exercises & Real-World Applications
 9.1 Prompt Engineering for SDLC Use Cases
 9.2 Live Demo: Generating Code, Requirements & Test Cases
 9.3 Implementing AI-Driven Workflows in Agile & DevOps
 9.4 Case Studies from Modern Software Teams

This training equips participants to harness Gen AI across all SDLC phases, enabling faster delivery, improved accuracy and superior software quality. By adopting AI-driven practices, teams can significantly boost productivity and build future-ready development capabilities.