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Build Intelligent Apps with Generative AI
The only Generative AI program that takes you from Python zero to deploying LLM-powered apps. Master LangChain, RAG, Hugging Face & Streamlit with real projects and expert mentorship.
Batch
starting
Batch
size
Mode
Online/Offline
Duration
4 months
Schedule
Weekdays 7-9 AM
Master Generative AI with Industry-Focused Training
Why Learn Generative AI?
Generative AI is transforming industries by enabling intelligent content generation, conversational systems, and context-aware AI applications. This course provides foundational to advanced knowledge required to build production-ready AI systems.
By enrolling in this course, you will learn to:
- Work with Python fundamentals including variables, control structures, functions, and modules
- Build machine learning models using Scikit-learn
- Understand neural networks and deep learning using PyTorch
- Apply NLP techniques including text preprocessing and vectorization
- Use Transformers like BERT and GPT-2
- Implement LangChain for building conversational systems
- Build Retrieval-Augmented Generation (RAG) applications
- Deploy and optimize LLM applications
Who Should Enroll?
- Students and graduates interested in AI careers
- Developers wanting to transition into Generative AI
- Professionals looking to build LLM-based applications
What Makes This Course Practical?
- Hands-on implementation in every module
- Model building and evaluation
- Capstone project using Streamlit, LangChain, and RAG
- Deployment using Streamlit Cloud and Hugging Face Spaces
Curriculum Highlights
What you will learn in the course
Generative AI Basics
Advanced Generative AI
SQL Basics
Advanced SQL
Course Curriculum
The only Generative AI program that takes you from Python zero to deploying LLM-powered apps. Master LangChain, RAG, Hugging Face & Streamlit with real projects and expert mentorship.
- Text: cleaning, stemming, lemmatization
- Vectorization using Bag of Words, TF-IDF, Word2Vec
- Sequence models: RNN, LSTM concepts
- NER, sentiment analysis hands-on
- Limitations of traditional NLP techniques
- Transformer architecture (self-attention, encoder-decoder)
- BERT, GPT-2 overview and use cases
- Using Hugging Face's transformers pipeline
- Downloading and using pre-trained models
- Hands-on: sentiment classifier, text summarizer
- LangChain architecture: Chains, Agents, Memory
- Building LLM chains using prompts and tools
- Creating a conversational bot with LangChain
- Integration with OpenAI API
- LangChain toolkits: calculator, Python REPL
- Understanding RAG and how it enhances LLMs
- Vector databases: FAISS, Pinecone basics
- Document loading and chunking for retrieval
- Creating context-aware Q&A systems
- Build a private chatbot using LangChain + RAG
- Prompt engineering patterns and anti-patterns
- Using Streamlit Cloud and Hugging Face Spaces for deployment
- Monitoring LLM behavior and optimization techniques
- Caching, truncation, rate limits and usage metrics
- Addressing hallucinations, bias, and safety in LLMs
- Plan and design a complete GenAI solution
- Possible projects: Resume screener, PDF-based chatbot, AI tutor
- Incorporate Streamlit + LangChain + RAG
- Model evaluation and improvement
- Presentation and deployment
What our Students Say
Real people. Real results.
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I recently completed the Generative AI course, and it was a great learning experience. The concepts were explained clearly with practical examples, which made it easy to understand how modern AI tools work. It really helped me gain confidence in using AI for real-world tasks. Highly recommended for anyone interested in AI!
Ankit singh
Student
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"I recently completed the Build Intelligent Apps with Generative AI course, and it was an excellent learning experience. The curriculum covered both AI fundamentals and modern tools like LLM integration and Prompt Engineering with practical projects. It really helped me improve my skills in building smart, automated applications and understanding how AI models interact with users. Highly recommended for anyone looking to build a future-ready career in software and AI."
Aryan Negi
Student
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"Joining this Generative AI program was the best decision for my technical growth as a developer. The course content is very deep, covering everything from basic API integration to building complex RAG (Retrieval-Augmented Generation) systems. What I liked most was the hands-on approach to real-world app development, which made complex AI concepts very easy to grasp. If you want to master building truly intelligent software, this is the perfect course for you."
Rahul Bisht
Student
Frequently Asked Questions
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