This specialization offers a hands-on journey into applying Generative AI across the Software Development Lifecycle (SDLC). Learn to automate key phases from requirement gathering and project planning to design, coding, testing, and deployment using tools like GitHub Copilot, ChatGPT, and Hugging Face Transformers. Generate multilingual requirements, design architecture, refactor legacy code, and enhance testing and release cycles. Explore ethical AI practices to ensure responsible implementation.
By the end of this program, you will be able to:
- Build AI-Driven Workflows: Apply GenAI across SDLC phases using industry tools
- Automate Development Tasks: Use AI for planning, coding, testing, and deployment
- Process Unstructured Data: Generate documentation, extract insights, and support localization
- Ensure Ethical Compliance: Address AI bias, privacy, and fairness in software systems
Ideal for software developers, QA engineers, and tech professionals aiming to integrate Generative AI into real-world software projects.
Applied Learning Project
Project Overview: Automating AWS EC2 Deployment with GitHub Copilot, Terraform, and Kubernetes
Automate Node.js app deployment on AWS EC2 using GitHub Copilot, Terraform, and Kubernetes. Create IAM credentials, generate IaC scripts, and deploy via Kubernetes YAML. Build skills in IaC, cloud automation, and GenAI-powered DevOps.
Project Overview: Optimizing Infrastructure with Prometheus and GitHub Copilot
Deploy Prometheus for performance monitoring and use GitHub Copilot to analyze metrics and generate optimized Terraform scripts. Strengthen observability, infrastructure tuning, and AI-assisted automation for efficient cloud management.
Project Overview: AI-Driven Project Planning and Risk Management
Use ChatGPT to refine scope, assess risks, and define QA/QC parameters. Enhance project planning, automate workflows, and improve decision-making—ideal for future AI-driven project managers.
