Master the technologies behind the next generation of AI applications. This comprehensive AI/ML and Generative AI program is designed to help learners develop practical skills in Machine Learning, Deep Learning, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI Agents, Multi-Agent Systems, MCP, APIs, databases, cloud deployment, and AI security.
Through hands-on learning and real-world projects, you will progress from Python and Machine Learning fundamentals to building intelligent AI agents and deploying production-ready AI applications.
The program covers leading AI technologies and frameworks including OpenAI, Gemini, Hugging Face, LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, FastAPI, FAISS, ChromaDB, Pinecone, PostgreSQL, MongoDB, Docker, Azure AI and AWS.
By the end of the program, you will have practical experience developing AI solutions such as AI resume screening agents, customer support agents, research assistants, RAG chatbots, SQL query agents, email automation agents, travel-planning multi-agent systems, AI data analyst agents, and autonomous business assistants.
Tools & Technologies
Python | Jupyter Notebook | VS Code | GitHub | OpenAI API | Gemini API | Hugging Face | LangChain | LangGraph | CrewAI | AutoGen | LlamaIndex | FastAPI | Streamlit | FAISS | ChromaDB | Pinecone | PostgreSQL | MongoDB | Docker | Azure AI | AWS
Sonal Gupta –
“I joined to build stronger skills and found the curriculum helpful. The practical examples made the learning more meaningful.”
B.Tech Computer Science Student
Vishal Sharma –
“A useful learning experience for anyone looking to build relevant skills. I liked the practical orientation and the range of topics covered.”
AI/ML Professional
Anushka Patil –
“The program helped me understand how the concepts can be applied in real projects. The hands-on work was a valuable part of the experience.”
B.E. Computer Science Student
Abhinav Singh –
“I liked the balance between concepts and hands-on learning. The examples made the topics easier to understand and apply.”
Data Scientist
Vivekanand Rao –
“I found the sessions clear and engaging. The structured learning path gave me more confidence in applying what I learned.”
AI Developer
Pallavi Desai –
“The curriculum was relevant and well organized. The project work was particularly useful for putting the learning into practice.”
Technology Consultant
Reshma Mathew –
“The program gave me a structured understanding of the subject. The practical exercises helped me connect the concepts with real-world applications.”
Software Engineer
Keerthana Nair –
“The practical approach was the best part for me. I was able to connect the concepts to situations I encounter in my studies or work.”
M.Tech Computer Science Student
Harini Suresh –
“A comprehensive learning experience with a good focus on practical implementation. The assignments added significant value.”
MCA Student
Mohit Agarwal –
“I appreciated the way the course moved from fundamentals to practical applications. It made the learning process much easier to follow.”
Full-Stack Developer
Akash Bansal –
“The instructors explained the topics in an accessible way. The course encouraged me to explore the subject further.”
Software Developer
Nikhil Reddy –
“The course covered several useful areas and gave me a stronger foundation. I especially appreciated the hands-on activities.”
ML Engineer
Rohit Kulkarni –
“The course covered several useful areas and gave me a stronger foundation. I especially appreciated the hands-on activities.”
Software Architect
Saurabh Mishra –
“I found the sessions clear and engaging. The structured learning path gave me more confidence in applying what I learned.”
BCA Graduate
Isha Malhotra –
“The practical approach was the best part for me. I was able to connect the concepts to situations I encounter in my studies or work.”
Software Engineer