Industry-Focused Learning : Master GenAI and Agentic AI 1:1 Mentorship with Generative AI experts Advanced Curriculum with 200+ Hours of Learning Master 26+ GenAI Tools and Libraries Hours of Immersive Learning Placement Assistance Hours of Live Workshops Quarterly 1:1 Expert-Led Mentorships Become a GenAI and Agentic AI Expert : Start Now How does the GenAI Pinnacle Plus Program Help You? 300+ Hours of Immersive Learning Full-spectrum GenAI and Agentic AI learning with 14 modules Master cutting-edge GenAI and Agentic AI frameworks and tools. 50+ Industry-Aligned Projects Acquire real-world experience through projects that connect theory with practice. Diverse projects designed to transform knowledge into expertise. 1:1 Expert Mentorship Get expert insights from seasoned professionals Accelerate your learning with a personalized roadmap to success 300+ Hours of Immersive Learning Full-spectrum GenAI and Agentic AI learning with 14 modules Master cutting-edge GenAI and Agentic AI frameworks and tools. 50+ Industry-Aligned Projects Acquire real-world experience through projects that connect theory with practice. Diverse projects designed to transform knowledge into expertise. 1:1 Expert Mentorship Get expert insights from seasoned professionals Accelerate your learning with a personalized roadmap to success Curriculum Statistics Hands-on learning with industry-relevant challenges. In-depth GenAI and Agentic AI learning to transform your career 40+ Tools & Libraries Develop expertise in 40+ essential industry tools, libraries and frameworks. 30+ Assignments To turn knowledge into action 75+ Mentorship Sessions 1:1 live mentorship session from GenAI and Agentic AI experts Personalized Roadmap Your ambition + our expertise = your custom path to mastery 1 Foundations for Generative AI 2 ML Foundations for Generative AI 3 DL Foundations for Generative AI 4 Build Applications using LLMs 5 Build RAG-Based Applications 6 Foundations for AI Agents 7 Getting Started with AI Agents using LangGraph, AutoGen & CrewAI 8 Build AI Agents using LangGraph, AutoGen & CrewAI 9 Real-World Projects on AI Agents 10 Finetune LLM-based applications 11 Deploy GenAI-Based Applications 12 Work with Diffusion Models 13 Decision-Making Essentials 14 Generative AI for Leaders 40+ cutting-edge courses to master GenAI and Agentic AI Exploring the Generative AI Universe Exploring the Generative AI Universe Introduction to Generative AI Introduction to Generative AI Essentials of Prompt Engineering Essentials of Prompt Engineering Fine-Tuning RAGs and Agents Fine-Tuning RAGs and Agents Responsible AI in the Generative AI Era Responsible AI in the Generative AI Era Introduction to Responsible AI in the Generative AI Era Introduction to Responsible AI in the Generative AI Era Coding Essentials for Agents Coding Essentials for Agents Introduction to Python Introduction to Python Working with Files and Databases Working with Files and Databases Working with APIs Working with APIs Working with LLMs Working with LLMs Build your First ML Model Build your First ML Model Build your first predictive model Build your first predictive model Preparing the dataset for Machine Learning Model Preparing the dataset for Machine Learning Model Introduction to KNN algorithm Introduction to KNN algorithm Building your first KNN Model Building your first KNN Model Evaluation Metrics Evaluation Metrics Foundational ML Algorithms Foundational ML Algorithms Introduction to Deep learning using PyTorch Introduction to Deep learning using PyTorch Introduction to Deep Learning Introduction to Deep Learning Understanding the working of Neural Networks Understanding the working of Neural Networks Improving Deep Neural Networks Improving Deep Neural Networks Natural Language Processing using PyTorch Natural Language Processing using PyTorch Introduction to NLP Introduction to NLP Building a basic classification model Building a basic classification model NLP: Recurrent Neural Network NLP: Recurrent Neural Network Attention Mechanism and transformers Attention Mechanism and transformers Preparing for LLMs Preparing for LLMs Computer Vision using PyTorch Computer Vision using PyTorch Introduction to Computer Vision Introduction to Computer Vision Building Blocks for Image Recognition Building Blocks for Image Recognition Getting Started with Large Language Models Getting Started with Large Language Models The Evolution of NLP The Evolution of NLP What are Large Language Models? What are Large Language Models? The Current State of the Art in LLMs The Current State of the Art in LLMs Generative AI - Glossary Generative AI - Glossary Introduction to LangChain for Agentic AI Introduction to LangChain for Agentic AI Introduction to the LangChain Ecosystem Introduction to the LangChain Ecosystem Essentials of LangChain Expression Language (LCEL) Essentials of LangChain Expression Language (LCEL) Handling LLM Inputs and Outputs Handling LLM Inputs and Outputs Projects on Prompt Engineering and Advanced LLM Chains Projects on Prompt Engineering and Advanced LLM Chains Building LLM Chains and Conversational Applications Building LLM Chains and Conversational Applications Prompt Engineering Essentials Prompt Engineering Essentials Introduction to Prompt Engineering Introduction to Prompt Engineering Core and Advanced Prompt Engineering Patterns Core and Advanced Prompt Engineering Patterns Guidelines and Best Practices for Prompt Design Guidelines and Best Practices for Prompt Design Working with Commercial & Open-Source LLM APIs Working with Commercial & Open-Source LLM APIs Hands-on Projects with Prompt Engineering and LLMs Hands-on Projects with Prompt Engineering and LLMs RAG Systems Essentials RAG Systems Essentials Introduction to Retrieval-Augmented Generation (RAG) Systems Introduction to Retrieval-Augmented Generation (RAG) Systems Building Retrieval Systems: Data Loading, Splitting & Chunking Building Retrieval Systems: Data Loading, Splitting & Chunking Implementing Vector Databases and Retrievers Implementing Vector Databases and Retrievers Projects: Document Retrieval & Advanced RAG Systems Projects: Document Retrieval & Advanced RAG Systems Building and Evaluating Complete RAG Pipelines Building and Evaluating Complete RAG Pipelines Building RAG System using LLamaIndex Building RAG System using LLamaIndex Introduction to RAG Systems and LlamaIndex Introduction to RAG Systems and LlamaIndex Core Components and Setup of LlamaIndex Core Components and Setup of LlamaIndex Customization and Advanced Techniques in LlamaIndex Customization and Advanced Techniques in LlamaIndex Evaluating RAG System Performance Evaluating RAG System Performance Building Powerful, Production-Ready RAG Solutions Building Powerful, Production-Ready RAG Solutions Building End-to-End Generative AI Application Building End-to-End Generative AI Application Introduction to Generative AI applications Introduction to Generative AI applications No-code Generative AI app Development No-code Generative AI app Development Code-focused Generative AI App Development Code-focused Generative AI App Development From Prompt to Product: Vibe Coding with Windsurf From Prompt to Product: Vibe Coding with Windsurf Coding with Windsurf Coding with Windsurf Anyone can build AI Agents Anyone can build AI Agents Introduction to Agents Introduction to Agents Building Agents Building Agents Working with Complex Agents Working with Complex Agents Architecting Agentic AI Architecting Agentic AI Introduction to AI Agents and Agentic design Introduction to AI Agents and Agentic design Agentic AI Reflection Pattern Agentic AI Reflection Pattern Tool Use Pattern Tool Use Pattern Agentic AI Planning Pattern Agentic AI Planning Pattern Multi-Agent Pattern Multi-Agent Pattern Building AI Agents from scratch Building AI Agents from scratch Introduction to AI Agents and Their Capabilities Introduction to AI Agents and Their Capabilities Building Reflection, Tool-Using, and Planning Agents Building Reflection, Tool-Using, and Planning Agents Creating Multi-Agent Systems from Scratch Creating Multi-Agent Systems from Scratch Hands-on Project: Real-World AI Agent Development Hands-on Project: Real-World AI Agent Development End-to-End Agentic Workflow with Practical Implementation End-to-End Agentic Workflow with Practical Implementation Building AI Agents with LangChain Building AI Agents with LangChain Introduction to Tools and Tool Calling Introduction to Tools and Tool Calling Essentials of AI Agents with LangChain Essentials of AI Agents with LangChain Memory and Conversational Agents Memory and Conversational Agents Project: Build a Text2SQL AI Agent Project: Build a Text2SQL AI Agent Project: Build a Financial Analyst AI Agent Project: Build a Financial Analyst AI Agent Building your First AI Agent with LangGraph Building your First AI Agent with LangGraph Introduction to LangGraph Introduction to LangGraph Build AI Agents with LangGraph Build AI Agents with LangGraph Building your First AI Agent with CrewAI Building your First AI Agent with CrewAI Introduction to CrewAI Introduction to CrewAI Core Components of CrewAI Core Components of CrewAI What sets CrewAI apart? What sets CrewAI apart? Building Advanced AI Agents with LangGraph Building Advanced AI Agents with LangGraph Introduction to Tools and Tool Calling Introduction to Tools and Tool Calling Essentials of AI Agents with LangChain Essentials of AI Agents with LangChain Memory and Conversational Agents Memory and Conversational Agents Project: Build a Text2SQL AI Agent Project: Build a Text2SQL AI Agent Project: Build a Financial Analyst AI Agent Project: Build a Financial Analyst AI Agent Building Advanced AI Agents with AutoGen Building Advanced AI Agents with AutoGen Introduction to AutoGen Introduction to AutoGen Conversation Agents - Part 1 Conversation Agents - Part 1 Conversation Agents - Part 2 Conversation Agents - Part 2 Additional Applications with AG2 Additional Applications with AG2 Introduction to AutoGen Studio and Its Interface Introduction to AutoGen Studio and Its Interface Building Advanced AI Agents with CrewAI Building Advanced AI Agents with CrewAI Course Introduction and Recap Course Introduction and Recap Advanced Components of crewAI Advanced Components of crewAI Building Advanced Agents Building Advanced Agents Assembling Complex Crew Assembling Complex Crew Optimizating Agents Optimizating Agents Building Agentic RAG Systems with LangGraph Building Agentic RAG Systems with LangGraph Introduction to Agentic RAG and LangGraph Introduction to Agentic RAG and LangGraph Popular Agentic RAG Architectures Popular Agentic RAG Architectures Project: Build a Router RAG System Project: Build a Router RAG System Project: Build an Agentic Corrective RAG System Project: Build an Agentic Corrective RAG System Project: Build an Adaptive RAG System Project: Build an Adaptive RAG System Building Agentic RAG using AutoGen for eCommerce Building Agentic RAG using AutoGen for eCommerce Introduction to Autogen and AI Agents Introduction to Autogen and AI Agents Setting up Chroma DB Setting up Chroma DB Setting up Autogen Agents Setting up Autogen Agents Adding Search to Agents Adding Search to Agents Multi-Agent AI system for Hotel Reservations Multi-Agent AI system for Hotel Reservations Introduction to AI Agents and Multi-Agent Systems Introduction to AI Agents and Multi-Agent Systems Agent-Based Hotel Reservation System Agent-Based Hotel Reservation System Advanced AI Agent Orchestration Advanced AI Agent Orchestration Deploying and Scaling AI Agents Deploying and Scaling AI Agents Finetuning LLMs Finetuning LLMs Introduction to the Course Introduction to the Course Introduction to Finetuning LLMs Introduction to Finetuning LLMs Instruction Finetuning in Practice Instruction Finetuning in Practice Parameter-Efficient Finetuning (PEFT) Parameter-Efficient Finetuning (PEFT) Prompt Learning PEFT Techniques Prompt Learning PEFT Techniques Training LLMs from Scratch Training LLMs from Scratch Introduction to Training Large Language Models (LLMs) from Scratch Introduction to Training Large Language Models (LLMs) from Scratch Key Concepts and Workflow for LLM Training Key Concepts and Workflow for LLM Training Step-by-Step Guide to Building Your Own LLM Step-by-Step Guide to Building Your Own LLM Aligning LLMs with Human Preferences Aligning LLMs with Human Preferences Next Steps and Real-World Applications Next Steps and Real-World Applications Mastering RL Foundations to Human Feedback Mastering RL Foundations to Human Feedback Introduction to Reinforcement Learning and Markov Decision Processes Introduction to Reinforcement Learning and Markov Decision Processes Core Methods: Dynamic Programming, Monte Carlo & Temporal Difference Core Methods: Dynamic Programming, Monte Carlo & Temporal Difference Deep RL Algorithms: PPO, DDPG, and Model-Free Control Deep RL Algorithms: PPO, DDPG, and Model-Free Control RLHF & DPO: Concepts, Techniques, and Algorithms RLHF & DPO: Concepts, Techniques, and Algorithms Hands-on Implementation and Practical Applications Hands-on Implementation and Practical Applications Mastering LLMOps: From Build to Deployment Mastering LLMOps: From Build to Deployment Setting Context for the Course Setting Context for the Course Kick-Start Your MLOps Journey Kick-Start Your MLOps Journey Overview of Level 1 MLOps Overview of Level 1 MLOps Overview of Level 2 MLOps Overview of Level 2 MLOps MLOps Applications and Best Practices MLOps Applications and Best Practices Agent Ops: Building & Deploying Agentic AI Systems Agent Ops: Building & Deploying Agentic AI Systems Introduction to AI Agent Operations Introduction to AI Agent Operations Building an Agentic AI System Building an Agentic AI System Build an API for your Agentic AI System Build an API for your Agentic AI System Deploying your AI Agent Deploying your AI Agent Testing and Monitoring your AI Agent Testing and Monitoring your AI Agent Getting started with stable diffusion Getting started with stable diffusion Introduction and Overview of the Stable Diffusion Process Introduction and Overview of the Stable Diffusion Process Core Components and Architecture of Stable Diffusion Core Components and Architecture of Stable Diffusion Understanding Variational Autoencoders (VAEs) Understanding Variational Autoencoders (VAEs) Deep Dive into Stable Diffusion Concepts and Workflows Deep Dive into Stable Diffusion Concepts and Workflows Hands-on Implementation: Building DDPM from Scratch Hands-on Implementation: Building DDPM from Scratch Mastering Methods and Tools of Stable diffusion Mastering Methods and Tools of Stable diffusion Understanding Dalle 2 Understanding Dalle 2 Steps involved in training stable diffusion Steps involved in training stable diffusion Mastering stability.ai and its tools Mastering stability.ai and its tools Prompt Engineering Concepts for Stable Diffusion Prompt Engineering Concepts for Stable Diffusion Advanced stable diffusion techniques Advanced stable diffusion techniques InstructPix2Pix Paper review and ControlNet InstructPix2Pix Paper review and ControlNet Human Decision Making and its Biases Human Decision Making and its Biases Why Decision Making is Hard Why Decision Making is Hard Data in Decision Making Data in Decision Making Group Decision Making - Perceptions, Prejudices and Biases Group Decision Making - Perceptions, Prejudices and Biases Group Decision Making - Role of Context, Hierarchy and Emotional Dynamics Group Decision Making - Role of Context, Hierarchy and Emotional Dynamics Structured approach to problem solving Structured approach to problem solving Introduction to Structured Thinking and Problem Definition Introduction to Structured Thinking and Problem Definition Developing Clear Problem Statements (Parts 1 & 2) Developing Clear Problem Statements (Parts 1 & 2) Problem-Solving Frameworks and Solution Finalization Problem-Solving Frameworks and Solution Finalization Pre-Solution Validation Checks Pre-Solution Validation Checks Applying Human-Centered Design Principles Applying Human-Centered Design Principles Design Thinking for Data Professionals Design Thinking for Data Professionals Understanding Human Centered Design and Role of Empathy Understanding Human Centered Design and Role of Empathy Discovery through Research Phase Discovery through Research Phase Insights through Synthesis Phase Insights through Synthesis Phase Generative AI for Consultants Generative AI for Consultants Why do Consultants need Generative AI? Why do Consultants need Generative AI? Generative AI in Practice Generative AI in Practice A Consultants' Guide to Generative AI Tools A Consultants' Guide to Generative AI Tools Generative AI for Business - A leader's handbook Generative AI for Business - A leader's handbook

Course Introduction Course Introduction Generative AI - The New Electricity Generative AI - The New Electricity Enterprising Generative AI Enterprising Generative AI Drive to succeed Drive to succeed All you need to know All you need to know Successful AI STrategies: A CEO's Perspective Successful AI STrategies: A CEO's Perspective Course Introduction and Defining AI Success Course Introduction and Defining AI Success Integrating AI with Engineering and Design Integrating AI with Engineering and Design Common Errors and Challenges in AI Common Errors and Challenges in AI Building Organizational Effectiveness for AI Initiatives Building Organizational Effectiveness for AI Initiatives Strategies for Successful AI Implementation Strategies for Successful AI Implementation Libraries & Frameworks Master 40+ GenAI and Agentic AI tools, libraries and frameworks for skill-building Build Your Portfolio with 50+ Industry-Relevant Projects Accelerate your industry readiness with projects designed to tackle real-world challenges. Learning Objective: Train and evaluate LLMs from scratch Learn LLM best practices and setup Implement advanced computing strategies 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 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 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 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 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 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 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 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 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 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 Diffusion Model Refinement Finetune Diffusion models using ControlNets and InstructPix2Pix models AI-Powered Mentorship, On Demand Access a 24/7 AI mentor that delivers personalized learning paths, assessments, and continuous career guidance at scale. Real Experience, Real Insights: Your Expert Mentors Tap into decades of combined industry experience Chi Wang, Senior Staff Research Scientist at Google DeepMind, specializes in AI, machine learning, and data mining. Formerly a Principal Researcher at Microsoft Research, he holds a Ph.D. from UIUC and has driven advancements in web entity disambiguation, social network analysis, and AI-driven optimization. Senior Staff Research Scientist Miguel Otero Pedrido, a leader in AI and Machine Learning, is the Founder of The Neural Maze and a Senior Machine Learning Engineer at Dressipi. With 9 years of expertise in AI systems, MLOps, and AI agents, he has driven AI innovations at BBVA, Telefónica Tech, and Enagás. Miguel Otero Pedrido Senior Machine Learning Engineer Eleni Verteouri, GenAI Tech Lead and Director - Conversational Banking at UBS, drives AI innovation and strategic partnerships. With 12 years of expertise in Generative AI, product management, and risk modeling, she has led AI transformations in finance. GenAI Tech Lead and Director - Conversational Banking 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 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 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 Applied Scientist II 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. Expert Senior Director 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. Head of Community and Principal AI Scientist Bhaskarjit is an award-winning data scientist with a diverse background in multiple domains such as Retail, Airlines, Media & Entertainment, BFSI Bhaskarjit Sarmah Head of AI Research 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. 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. 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. Senior Data Scientist 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 Associate Principal 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 Data & Applied Sciences 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 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. Senior Scientist 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 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 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 Qingyun Wu, founder of AG2 (formerly AutoGen) and Assistant Professor at Penn State University, brings over seven years of expertise in AI and machine learning. Her work spans AI agents, reinforcement learning, and algorithm optimization, with roles at Microsoft, Adobe, and Yahoo driving advancements in AI technologies. Creator and Founder Alessandro Romano, Senior Data Scientist at Kuehne+Nagel, has over six years of experience in AI and data science. With roles at FREE NOW and Cargonexx GmbH, he specializes in building AI-driven solutions and AI agents to automate workflows and enhance efficiency. A skilled public speaker, Alessandro effectively bridges technical concepts with diverse audiences. Alessandro Romano Senior Data Scientist Pio Scelina is an experienced AI Agent developer with over 6 years of expertise in creating advanced AI solutions. His strong research background keeps him at the leading edge of new tools and applications, constantly driving innovation. Known for his passion for exploring emerging technologies and enhancing AI-driven experiences, Pio has established a reputation as a trailblazer in AI-powered transformation. AI Agent Developer Kamil Ruczynski is a seasoned AI Agent developer with over 7 years of experience in cutting-edge AI organisations. His deep expertise in research and development enables him to stay ahead of emerging trends and technologies, driving continuous innovation. Renowned for his dedication to pushing the boundaries of AI-driven applications, Kamil has earned recognition as a pioneer in creating transformative AI experiences Kamil Ruczynski AI Agent Developer Prashant Sahu, an IIT Bombay alumnus and seasoned Corporate Trainer in AI & ML, has over 17 years of diverse experience in areas like research, automation, and cryptography. His expertise extends to developing comprehensive Data Science training materials, including curriculum, case studies, and projects. Manager - Data Science - Instructor Apoorv Vishnoi, a seasoned professional with over 13 years of experience, including more than 10 years in Machine Learning and AI. He holds an MBA from the prestigious Indian School of Business and several certifications in Data Science and Deep Learning. His ability to simplify complex concepts in Data Science and Machine Learning has established him as a respected and influential instructor. Head - Training Initiative Pinnacle Plus Mastery Offer Use code PINNACLE20 and get flat 20% off GenAI Pinnacle Plus Program. Use code GENAI20 and get $180 off on GenAI Pinnacle Program. Enrollment closes in Instructor-Led Live Workshops Live GenAI and Agentic AI workshops : Solve real-world problems with expert insights Learning Objective: Differentiate RAG from prompt engineering and fine-tuning. Learn when to use RAG versus other approaches. Understand Retrieval-Augmented Fine-Tuning (RAFT). Build, tune, and evaluate a RAG pipeline. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering RAG Systems I Learning Objective: Learn LangChain fundamentals for building AI Agents. Explore prompts, chat models, tools, and function calling. Develop tool-use Agents with hands-on exercises. Integrate memory to create adaptive conversational Agents. Upcoming 7:00 PM - 10:00 PM (IST) IST Introduction to LangGraph for Building AI Agents Learning Objective: Understand ML algorithms, Data Preparation, and Model Building. Master Linear & Logistic Regression with error minimization and key metrics. Learn data handling techniques like missing value treatment & encoding. Apply regularization and interpret confusion matrices for classification. Upcoming 7:00 PM - 10:00 PM (IST) IST Machine Learning Basics Learning Objective: Explore Decision Trees, SVM, and KNN for classification and regression. Learn to handle overfitting, multicollinearity, and unbalanced data. Master model selection, cross-validation, and hyperparameter tuning. Enhance model performance with ensemble methods like bagging and boosting. Upcoming 7:00 PM - 10:00 PM (IST) IST Machine Learning Advanced Learning Objective: Understand Neural Networks, activation functions, and optimization techniques. Build Artificial Neural Networks (ANNs) for structured data. Learn backpropagation, gradient descent, and overfitting prevention. Explore the basics of CNNs and RNNs for Deep Learning applications. Upcoming 7:00 PM - 10:00 PM (IST) IST Deep Learning Using Pytorch Learning Objective: Learn vector space models like Bag of Words and TF-IDF. Explore word embeddings with Word2Vec, GloVe, and FastText. Understand embeddings at word, sentence, and document levels. Build sequential models (RNN, LSTM, GRU) and apply them to NLP tasks. Upcoming 7:00 PM - 10:00 PM (IST) IST NLP using Deep Learning Learning Objective: Understand the importance of prompt engineering. Learn to craft clear, specific, and contextual prompts. Apply few-shot prompting techniques for better AI responses. Refine generated content through iterative improvements. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering Prompt Engineering I Learning Objective: Manage multi-turn conversations effectively. Apply advanced prompting techniques for complex tasks. Design chatbot scenarios and analytical reports. Understand AI limitations and ethical considerations. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering Prompt Engineering II Learning Objective: Compare GraphRAG with traditional RAG systems. Build and store knowledge graphs in graph databases. Create and evaluate GraphRAG pipelines. Understand the architecture and key components of a RAG system. Upcoming 7:00 PM - 10:00 PM (IST) IST Mastering RAG Systems II Learning Objective: Learn LangChain fundamentals for building AI Agents. Explore prompts, chat models, tools, and function calling. Develop tool-use Agents with hands-on exercises. Integrate memory to create adaptive conversational Agents. Upcoming 7:00 PM - 10:00 PM (IST) IST Building AI Agents with LangChain Learning Objective: Learn memory management and snapshots for AI Agents. Build conversational Agents with persistent memory. Develop a financial analyst Agentic system. Create adaptive Agents that retain context and improve over time. Upcoming 7:00 PM - 10:00 PM (IST) IST Building Advanced AI Agents with LangGraph - I (Conversational Agents) AV Assisted Placements Our alumni universe: 1200+ professionals making their mark Assistant Manager - Analytics Ashiwn Deendayalan Assistant Manager - Analytics Assistant Manager - Analytics Associate Consultant Industry-Recognized Certification Get certified in GenAI and Agentic AI from Analytics Vidhya, Fractal and Western State University, and share your achievement with the world Our advisors ensure our programs are innovative, impactful, and industry-aligned. 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. 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 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. AV Learners Spotlight 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. Sr. Level Strategic Planning Executive 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. Arunima R Pillai ML Engineering Analyst 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. Staff Data Scientist 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. 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. Application Developer 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. Parikshit Rathode Senior AI & ML Developer Money Back Guarantee! GenAI Pinnacle Plus Program comes with 7 days no questions asked Money Back Guarantee. If the Program is bought in pre-launch offer or on discounted price, then the fee paid is non-refundable. For more T&C, Click here Choose the Right AI Program for You Unlock your AI potential with the GenAI program designed for your growth journey. GenAI Pinnacle Program 12 Months of Power Learning 50+ Deep-Dive Mentorship Sessions 100+ Hours of Hands-On Workshops 50+ Industry-Grade Projects 300+ Hours of Structured Curriculum 30+ Industry-Aligned Assignments AV Certificate | Fractal Certificate | WSU Certificate GenAI Pinnacle Plus Program 18 Months of Continuous Access 75+ Deep-Dive Mentorship Sessions 200+ Hours of Hands-On Workshops 50+ Industry-Grade Projects 300+ Hours of Structured Curriculum 30+ Industry-Aligned Assignments AV Certificate | Fractal Certificate | WSU Certificate Contact Us Today Take the first step towards a future of innovation & excellence with Analytics Vidhya Upskill, Reskill, Thrive Get Expert Guidance Need support? We've got your back anytime! +91-9354711240 10AM - 7PM (IST) Mon-Sun [email protected] You'll hear back from us in 24 hours. [email protected] Frequently Asked Questions Looking for answers to other questions? What makes the GenAI Pinnacle Plus Program different from other AI courses? The GenAI Pinnacle Plus Program sets itself apart by offering a unique combination of 1:1 mentorship, over 300 hours of advanced Generative AI and Agentic AI learning, and real-world project experience. This GenAI certification program focuses on hands-on learning using more than 40 Generative AI tools and frameworks, ensuring you stay ahead in the evolving AI industry. How is the GenAI Pinnacle Plus Program different from the Pinnacle Program? The GenAI Pinnacle Plus Program provides a more comprehensive learning experience than the GenAI Pinnacle Program, with 18 months of access compared to 12 months, 75+ mentorship sessions instead of 50, and 200 hours of workshops versus 100 hours. Overall, GenAI Pinnacle Plus is designed for learners who want extended access, increased mentorship, and significantly more live workshop hours for deeper skill development. Who is the ideal candidate for this program? 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