Full Stack .NET Developer with AI & GenAI Integration

Duration: 80 Hours (20 Sessions × 4 Hours)

Introduction

This industry-oriented program is designed for fresh engineering graduates who want to become job-ready software developers. The focus is on a strong C# & .NET development foundation, basic understanding of AI/ML concepts, practical use of GenAI tools for coding productivity, and exposure to Agile and project workflows.

Learning Objectives

By the end of this program, learners will:

  • Write structured, clean C# code using OOP principles
  • Build basic web applications using .NET Core
  • Understand what AI/ML is at a developer awareness level
  • Integrate AI APIs into .NET applications
  • Use GenAI tools like Copilot responsibly
  • Work in Agile environments using JIRA

Module 1: C# & .NET Foundations

Sessions 1–7 | 28 Hours

  • Session 1 – Introduction to C# & Programming Basics: .NET ecosystem overview, C# syntax, data types, control statements, hands-on coding exercises
  • Session 2 – Object-Oriented Programming: Classes & objects, encapsulation, inheritance, polymorphism, real-world modeling exercise
  • Session 3 – Advanced C# Concepts: Exception handling, collections, generics, delegates (basic introduction), practice exercises
  • Session 4 – LINQ & File Handling: LINQ basics, querying collections, file I/O, data processing examples
  • Session 5 – Async Programming: async/await basics, tasks, handling concurrency, practical demo
  • Session 6 – ASP.NET Core Basics: Web application structure, controllers, routing, REST API basics, building a simple API
  • Session 7 – Mini Project (C# + Web App): CRUD application, basic validation, API testing, code review session

Module 2: AI & ML Awareness for Developers

Sessions 8–10 | 12 Hours

  • Session 8 – Introduction to AI & ML: What is AI? What is ML? Real-world applications, supervised vs unsupervised (concept only), AI in software products
  • Session 9 – ML Concepts (High-Level): What is regression? What is classification? What is model training? What is accuracy? Understanding APIs for ML services
  • Session 10 – AI Integration Demo: Using pre-built ML APIs, calling AI services from .NET, JSON response handling, basic AI feature integration demo

Module 3: Generative AI for Developers

Sessions 11–12 | 8 Hours

  • Session 11 – Introduction to Generative AI: What is Generative AI? GitHub Copilot overview, prompt engineering basics, code generation exercises
  • Session 12 – Productivity with GenAI: Debugging with AI, writing documentation, refactoring code, responsible AI usage

Module 4: Industry Tools & Agile Exposure

Sessions 13–15 | 12 Hours

  • Session 13 – Agile & JIRA Basics: Scrum concepts, epics/stories/tasks, sprint simulation, agile board hands-on
  • Session 14 – Time Tracking & Reporting: Logging time, understanding reports, resource basics, corporate expectations
  • Session 15 – Documentation & Modeling: UML basics, use case diagrams, class diagrams, team documentation practice

Module 5: Capstone & Integration

Sessions 16–20 | 20 Hours

  • Session 16 – Designing the Final Project: Requirement understanding, feature planning, JIRA setup, architecture discussion
  • Session 17 – Development Sprint 1: Core application build, API integration
  • Session 18 – Development Sprint 2: AI feature integration, testing & debugging
  • Session 19 – Finalization & Code Review: Optimization, peer review, documentation completion
  • Session 20 – Presentation & Assessment: Project presentation, technical Q&A, individual feedback