About this course
Learn to build AI-powered software with large language models (LLMs), AI APIs, embeddings, and Retrieval-Augmented Generation (RAG). Over this one-year program, develop practical skills for creating intelligent chatbots, document question-answering systems, and custom AI applications.
Build and refine projects using Git and GitHub, and learn deployment fundamentals to help prepare your applications for real-world use.
- Work with LLMs and AI APIs to create application features.
- Use embeddings and RAG to connect language models with relevant information.
- Develop chatbot and document question-answering projects.
- Practice version control and application deployment fundamentals.
Program duration: 1 year. Fee: ₹119,000.
Tools you will master
Hands-on practice on the same software that companies use every day.
Google GeminiAI
GitHub CopilotAI
VS CodeAI
GitHubAI
ClaudeAI
PerplexityAI
NotebookLMAI
What you will study, module by module
- AI Basics and Everyday Uses
- Generative AI: How It Works
- Prompt Engineering Foundations
- AI for Study and Workplace Tasks
- Fact-Checking and Reliable Research
- Privacy, Safety and Responsible Use
- Integrated Practice and Review
- AI Pair Programming Setup: VS Code and GitHub Copilot
- AI-Assisted Front-End Development
- Python Coding and AI Agents in the Editor and Terminal
- GitHub Team Workflow and AI Code Review
- Calling AI APIs from Your Own App
- AI-Assisted Testing, Debugging and Documentation
- AI-Assisted Deployment and Final Project
After this course you will be able to
- Explain core concepts behind generative AI and large language models.
- Integrate LLMs into software applications using AI APIs.
- Create embeddings and use them to retrieve relevant information.
- Design and implement Retrieval-Augmented Generation (RAG) workflows.
- Build intelligent chatbots and document question-answering systems.
- Develop custom AI application features and evaluate their behavior.
- Use Git and GitHub for version control and collaborative development.
- Apply deployment fundamentals to prepare AI applications for use.
Projects you will build
Build an AI-powered chatbot that responds to user questions using an LLM API.
Create a document question-answering application that retrieves relevant content with embeddings and RAG.
Develop a custom AI application that combines an LLM with a focused user workflow.
Publish project code to GitHub and prepare an application for deployment using the techniques covered in the course.
Jobs you can get after this course
Who hires for these skills
Earn on your own
- Depending on their skills and portfolio, learners may offer prompt writing, AI-assisted content support or simple no-code workflow setup. Freelance work requires client communication, quality checks and responsible handling of data.
Is this course for you?
Best for
- College students and graduates curious about AI careers.
- Working professionals who want to use AI in their current work.
- Job seekers exploring digital and technology roles.
- Business owners seeking to understand AI-enabled workflows.
- Creative workers and homemakers interested in practical AI tools.
Eligibility
Suitable for learners interested in software development and generative AI. Basic programming familiarity is helpful, but learners should check with the course provider for any formal prerequisites.
What next after this course
Questions students ask
The course duration is one year.
The listed course fee is ₹XXX,XXX. Confirm current pricing and payment options with the course provider.
You will work toward building intelligent chatbots, document question-answering systems, and other custom applications that use LLMs, APIs, embeddings, and RAG.
Basic programming familiarity is helpful for application development. Contact the course provider to confirm any formal entry requirements.
The course includes deployment fundamentals, along with Git and GitHub practices for managing application code.