DotNet Development with AI

Why Learn Dot Net?

Microsoft Dot Net is one of the most sophisticated and reliable software development technologies that allows to develop several highly productive applications such as SAAS based Employee benefits solutions and Enterprise Resource Planning (ERP) via the window applications, window services, web applications, web services, business intelligence (via MS SQL Server) and SQL services. It has a unique neutral language infrastructure for the development and deployment of applications by supporting various programming languages. The cross-platform compatibility of the Dot Net solutions dissolved all the operating issues of older and new applications.

Course Structure

• book_2 Basic Programming Recap & Aptitude

  This module is designed to help students refresh their fundamental knowledge of C programming and assess their readiness for advanced programming concepts.

• book_2 Module 1: Introduction to DotNet Framework & AI

  topicOverview of DotNet in Web Development

  • ASP.NET work, CLR, CLS, CTS, ADO.NET, LINQ

  
  

  topicUnderstanding AI and Machine Learning

  • • What is Artificial Intelligence and Machine Learning?
  • • Types of AI: Supervised vs. Unsupervised Learning.

• book_2 Module 2: Database Insights, & AI Use

  • • Database Schema, Table creation.
  • • Create, Alter, Insert, Update, Delete, Select query, Joining Query.
  • • Stored Procedure, View, Concept of NOSQL.
  • • Database Automation using AI.

• book_2 Module 3: OOPs Concept with Console Application, use of AI

  • • Class, Object, Properties, Constructor, Inheritance, Interface, Method Overloading, Method Overriding, List, Loop, Switch Case.
  • • Code optimisation using AI Tools.

• book_2 Module 4: Coding with ASP.Net

  topicASP.NET CORE

  • Asp.net CORE overview and advantages, Web application folder structure, Middleware Pipeline, InProcess Hosting, OutProcess Hosting, Kestrel Server, Package Reference for asp.net core web app.

  
  

  topicASP.NET MVC 5

  • • Concept of MVC Framework, Working with controller, sending values from controller to view.
  • • Managing the default layout with AI.

• book_2 Module 5: Database Connectivity with ADO.NET (MVC)

  • • Concept of ADO.NET, Working with SqlConnection, SqlDataAdapter, SqlCommand Class, DataSet and DataTable, Basic CRUD operation with ADO.NET.
  • • Use of AI tools in CRUD operation.

• book_2 Module 6: Database Connectivity with LINQ using Entity Framework (MVC)

  • Model First approach or Database First approach CRUD Operation, CODE First approach CRUD Operation, Dynamic dropdown from database, File upload, Registration, Login with session.

• book_2 Module 7: AI-Powered Web Development with DotNet

  topicAI in .Net-Based Web Applications

  • • Integrating OpenAI API with .Net (ChatGPT, DALL·E for image generation).
  • • AI-based search and recommendation systems using Elasticsearch.
  • • AI-driven content moderation (text and image recognition).

  
  

  topicAI-Driven Chatbots & Automation

  • • AI as SEO expert to create SEO friendly website.
  • • Creating an AI-powered chatbot with Dialogflow and .Net.
  • • Automating customer interactions with AI chatbots in .Net websites.

  
  

  topicAI for Data Analysis & Predictions

  • • Using AI for predictive analytics in .Net applications.
  • • AI-based API Interference & data visualization tools (Google AI, Hugging Face APIs) .

• book_2 Module 8: Web API, and AI Integration
  • • JSON Format, HTTP Services (GET, PUT, POST, DELETE), Concept of POSTMAN operation & Swagger operation.
  • • USE of AI for creating API.
• book_2 Module 9: Automated Testing & Security with AI
  • • AI-powered testing tools for .Net applications (AI-driven Selenium).
  • • AI-based vulnerability scanning for .Net websites.
  • • AI-enhanced user authentication (face recognition, CAPTCHA alternatives).

AI-Enhanced Project Development & Deployment

Building upon their acquired DotNet expertise, students will engage in developing sophisticated, industry-relevant projects. This phase integrates AI tools to streamline development, focusing on:

• AI-Assisted Code Generation: Utilizing AI to accelerate the initial coding process.
• Intelligent Debugging & Optimization: Employing AI for identifying and resolving code inefficiencies.
• Automated Testing: Implementing AI-driven testing to ensure robust and reliable applications.

Students will follow a comprehensive Software Development Life Cycle (SDLC), gaining practical experience in each stage. Furthermore, they will be guided through the process of deploying their AI-enhanced projects on free hosting platforms, providing invaluable insight into live application deployment and the integration of AI in real-world scenarios.

Certification as Trainee Software Engineer

On successful completion of the course, students get certified as Trainee Dot Net Developer, jointly by Ejobindia and the development firm Sysalgo Technologies.