GenAI Learning Week

Free 7-Day Learning Marathon!

  • Advanced Curriculum with 200+ Hours of Learning
  • Master 26+ GenAI Tools and Libraries
  • Insights from Top Generative AI Experts

200+ Hrs

Comprehensive Learning

10+

Real-world Projects

Claim Your Access to 7 Days of FREE GenAI Learning!

Personalized Roadmap

Navigate Your GenAI Journey with a Customized Learning Experience!

  • 1Introduction to Gen AI
  • 2Human decision making and its biases
  • 3Structured approach to problem solving
  • 4Applied ML, DL and NLP
  • 5Getting started with LLMs
  • 6LLM applications with prompt engineering
  • 7Introduction to LangChain
  • 8Building production ready RAG systems
  • 9Fine-tuning LLMs
  • 10Training LLMs from scratch
  • 11Mastering Stable Diffusion- beginner to advanced
  • 12Generative AI for business- strategies and Responsible AI
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Skill Up with Our Cutting-Edge Curriculum

19+ modules, crafted by experts, to rocket you from data whispers to LLM mastery. Conquer Stable Diffusion, dominate Reinforcement Learning and speak the language of AI.

10+ Projects
200+ Hours
26+ Tools
15+ Assignments

  1. Introduction to Generative AI

  2. Human decision- making and its biases

  3. Structured approach to problem solving

  1. Generative AI for NLP

  2. Building end-to-end LLM applications with Prompt Engineering

  3. Advanced Prompt Engineering

  4. Building RAG systems with LangChain and LlamaIndex

  5. Learn to use LLMs like ChatGPT, Gemini, Gemma, Phi

  6. Learn to use tools and platforms like LangChain, LlamaIndex, Streamlit, Chainlit and HuggingFace

  1. Fine-tuning LLMs with Parameter Efficient Fine-tuning Techniques

  2. Instruction fine-tuning of LLMs

  3. Reinforcement Learning with Human Feedback

  4. Training LLMs from Scratch

  1. Fundamentals of Diffusion Models

  2. Stable Diffusion in practice - popular techniques

  3. Methods, jobs, and tools of Stable Diffusion

  4. Advanced techniques - image variations, inpainting, outpainting and more

  1. Python for Data Science

  2. Data Exploration and Statistical Inference

  3. Basics of Machine Learning

  4. Fundamentals of Deep Learning

  5. Natural Language Processing

  6. Deep Learning for NLP - ANNs to Transformers

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10+ Generative AI Projects to Put Theory into Practice

Dive into real-world challenges, from harnessing ChatGPT to building conversational chatbots and RAG systems.

Learning Objective:

  • Train and evaluate LLMs from scratch
  • Learn LLM best practices and setup
  • Implement advanced computing strategies
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Training Large Language Models

Build Large Language Models (LLMs) like GPT-3.5 from scratch

Learning Objective:

  • Master building a ChatGPT-like LLM
  • Apply pretraining, finetuning, RLHF
  • Learn dialogue-optimized LLM practices
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ChatGPT Model Building

Develop a personalized ChatGPT model, starting from the basics up

Learning Objective:

  • Create a RAG-based QA Chatbot
  • Develop apps end-to-end with LangChain and Streamlit
  • Integrate app UI and backend seamlessly
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Building end-to-end RAG Apps

Craft RAG-based chatbots and Full-stack Applications with Integrated Frontend-backend synchronization

Learning Objective:

  • Construct Conversational Bots with LLMs including ChatGPT
  • Develop AI Instruments and Agents via LangChain
  • Establish and Manage LLM Applications using LangChain
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Build Conversational Apps and Agents

Create advanced conversational interfaces and intelligent Agents with LLMs and LangChain Technology

Learning Objective:

  • Enhance search accuracy in RAG systems through reranking
  • Apply RAG system techniques from cutting-edge studies
  • Construct RAG systems for diverse data types including tables, text, and images
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Advanced RAG System Development

Master precision in RAG systems across various data formats with State-of-the-art Techniques

Learning Objective:

  • Master prompt engineering techniques
  • Build chatbots using ChatGPT API
  • Implement LLMs on private data
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Prompt-Driven LLM Apps

Develop your own LLM Application using Prompt Engineering

Learning Objective:

  • Build RAG systems using LlamaIndex
  • Explore advanced LlamaIndex components
  • Fine-tune embeddings and retrieval
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RAG System Development

Create a production ready RAG systems on your private data

Learning Objective:

  • Efficient LLM finetuning with PEFT
  • Apply LoRA, QLoRA, soft prompting
  • Build instruction-following LLMs
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LLM PEFT Finetuning

Finetuning LLMs using Soft Prompting, Adaptor techniques using PEFT

Learning Objective:

  • Fine-tune Stable Diffusion for datasets
  • Apply best practices in customization
  • Understand Stable Diffusion intricacies
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Customized Diffusion Model Tuning

Finetune your own Stable Diffusion Models on custom dataset

Learning Objective:

  • Build Text to Image models with DreamBooth
  • Implement DreamBooth on personal datasets
  • Create context-specific visual models
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DreamBooth Image Creation

Build your own personalized Text to Image models using DreamBooth

Learning Objective:

  • Fine-tune diffusion models with ControlNets
  • Optimize InstructPix2Pix in diffusion models
  • Tailor models for specific datasets
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Diffusion Model Refinement

Finetune Diffusion models using ControlNets and InstructPix2Pix models

Learn from Seasoned Pros

World-Class Instructors Sharing Industry Secrets & Best Practices!

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Mustafa Kadioglu is a prominent figure in the field of data science and artificial intelligence. He currently serves as a Lead Data Scientist and AI/ML Engineer at Cisco, where he has developed expertise in Python, data analysis, machine learning, and natural language processing (NLP)

Mustafa Kadioglu

Lead Data Scientist

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Srikanth Velamakanni is the Co-founder, Group Chief Executive and Vice Chairman of Fractal. Fractal is one of the most prominent providers of Artificial Intelligence to Fortune 500®companies.

Srikanth Velamakanni

Co-Founder, Group Chief Executive and Vice Chairman

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Sourab Mangrulkar, with a specialization in ML and Deep Learning from NIT Goa, has worked at Microsoft, Amazon, and Hugging Face, focusing on diverse AI challenges and contributing to open-source projects like Accelerate and PEFT.

Sourab Mangrulkar

ML Engineer & Applied Scientist

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Sandeep Singh, expert senior director at Bain & Company is a leader in AI and Computer Vision. He has pioneered advanced geospatial solutions in Silicon Valley, enhancing mapping, navigation, and sector-wide applications.

Sandeep Singh

Expert Senior Director

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Dipanjan has over 10+ years of hands-on and leadership industry experience as well as training, consulting and education initiatives in Data Science and Artificial Intelligence.

Dipanjan S.

Head of Community and Principal AI Scientist

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Bhaskarjit is an award-winning data scientist with a diverse background in multiple domains such as Retail, Airlines, Media & Entertainment, BFSI

Bhaskarjit Sarmah

Vice President

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Ravi is a Developer Advocate Enginneer at LlamaIndex. His involvement in the field of AI spans many years, marked by notable contributions in Natural Language Processing (NLP) and recommender systems.

Ravi Theja

Developer Advocate

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Kunal has 15+ years of experience in the field of Data Science and is the founder and CEO of Analytics Vidhya- world's 2nd largest Data Science coummunity.

Kunal Jain

Founder & CEO

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Aravind Pai, Senior Data Scientist at Analytics Vidhya, specializes in Generative AI, Deep Learning, Computer Vision, and NLP. He has developed impactful AI technologies across various sectors including sports and healthcare.

Aravind Pai

Senior Data Scientist

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Mani Kanteswara Rao Garlapati is an Associate Principal at Google, where he leads data science initiatives focused on fraud and spam detection across various Google products. With a strong background in machine learning and data science, he has previously held positions such as Lead Strategist at Google and Senior Data Scientist at Walmart Labs

Mani Garlapati

Associate Principal

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Sumit Jain is a seasoned professional in the fields of artificial intelligence and data science, currently working at Microsoft in the Data & Applied Sciences division. He specializes in real-time generative AI at scale and provides technical leadership and advisory services

Sumit Jain

Data & Applied Sciences

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Shahebaz Mohammad is a renowned Kaggle Grandmaster and LinkedIn Top ML Voice who currently works as a Lead Applied Machine Learning Engineer at Snorkel AI. He has established himself as an expert in the field of applied machine learning

Shahebaz Mohammad

Senior Applied ML Engineer

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Mayank Barnwal is a Senior Scientist at Tata Consultancy Services and an Adjunct Professor at IIT Bombay, specializing in control theory, machine learning, and optimization. With a Ph.D. from the University of Illinois at Urbana-Champaign, his research spans robust control algorithms, deep learning applications, and combinatorial optimization.

Mayank Barnwal

Senior Scientist

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Kartik Nighania, an MLOps Engineer at Typewise, brings over seven years of AI experience across computer vision, NLP, and DevOps. Formerly Head of Engineering at Pibit.ai, he led AI-driven automation and infrastructure scaling. His expertise in CI/CD pipelines was honed at HSBC Technology, and his academic work includes AI publications and projects like ML-driven crop health detection

Kartik Nighania

MLOps Engineer

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Lucas Soares is an AI Engineer at Otovo, focusing on AI-driven solutions through large language models (LLMs) and computer vision. With 6+ years of experience across sectors like biometrics and retail, he excels in developing machine learning tools

Lucas Soares

AI Engineer

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Maarten Grootendorst is a Senior Clinical Data Scientist at IKNL (Netherlands Comprehensive Cancer Organization). He holds three master’s degrees in organizational psychology, clinical psychology, and data science, which he leverages to communicate complex machine-learning concepts to a wide audience

Maarten Grootendorst

Senior Clinical Data Scientist

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Instructor-Led Live Workshops

Live workshops, real-world problems, expert insights (For a limited period!)

Learning Objective:

  • Supervised & Unsupervised ML Algorithms, with use cases
  • Classification & Regression Metrics
  • Techniques of preventing models from overfitting
  • Model Selection and comparison
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Machine Learning for Generative AI

Learn Machine Learning for Generative AI

Learning Objective:

  • NLU Topics (POS Tagging, NER tags, noun chunking)
  • NLP Basics
  • End-to-end Sentiment Analysis project using ML algorithms and ANN
  • Advanced Sequence learning neural
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NLP using Deep Learning

Implement NLP using Deep Learning

Learning Objective:

  • Fundamentals of Transformer Architecture
  • Adanced Model Architectures
  • Techniques for reducing model size
  • Applications in translation, summarization, and content generation
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Advancing from Transformers to LLMs

Learn fundamentals of transformer architechture

Learning Objective:

  • Basics of Prompt Engineering & Understanding the role of prompts in AI interactions
  • Types of prompts, techniques for crafting effective prompts
  • Designing prompts for specific applications like translation, summarization, and content creation
  • Tailored prompts for tasks like question answering and data extraction
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Prompt Engineering

Learn prompt engineering

Learning Objective:

  • Intro to RAG
  • Different document loaders, tokenisations and chunking strategies in Langchain
  • Word embedding techniques & creating RAG-based LLM apps
  • Experimenting open-source and proprietary LLMs
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Advanced RAG using Langchain

Implement RAG using langchain

Learning Objective:

  • Basics of Fine-tuning
  • Data Preparation for Fine-tuning
  • Hyperparameter tuning for optimal performance, PEFT, other optimization tricks
  • Dealing with overfitting during the fine-tuning process
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Fine Tuning LLMs

Learn to finetune large language models

Certificates of completion

Get Certified in GenAI from Analytics Vidhya, Fractal, and Western State University, and share your achievement with the world

Our Advisors

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Prof. Tom Yeh leads the Imagine AI Lab at the University of Colorado Boulder, focusing on AI, HCI, Education, Ethics, and Neuroscience. He is the author of the popular AI by Hand series, has over 150 publications, and has received numerous university awards.

Dr. Tom Yeh

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Dr. Andrei Lopatenko, with over two decades of experience in the technology sector, has led pioneering research and development in artificial intelligence, machine learning, and natural language processing at prominent organizations including Google, Apple, Walmart, eBay, and Zillow, as well as at the startup Ozlo, which was subsequently acquired by Facebook. He earned his PhD in Computer Science from the University of Manchester.

Andrei Lopatenko

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Dr. Kirk Borne is a prominent data scientist with 40+ years of experience, founder of Data Leadership Group LLC, and an AI thought leader, career data professional, and research astrophysicist who has contributed to NASA's space science programs.

Dr. Kirk Borne

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AV Learners Spotlight

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All my expectations from the course and workshops have been fulfilled

I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons.

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I found future learning with Gen AI very interesting

I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons.

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The program has all the cutting edge technologies covered

I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons.

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I really value the personalised mentorship sessions which came with the program

I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons.

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Mentors of Analytics Vidhya have business experience and are practitioners themselves

I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons.

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The content Analytics Vidhya provided was far better than any other organisation

I've had the pleasure of witnessing the exceptional talent nurtured by Analytics Vidhya's hackathons.

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