Artificial Intelligence
Gen AI and Agentic AI
Deep dive into Generative AI and autonomous agents — master LLMs, LangChain, RAG, CrewAI, and build production-grade AI applications safely.
7+Learners
4.9Rating
75Days
181Lectures
Eswar
Last Updated: August 27, 2026
Description
Deep dive into Generative AI and autonomous AI agents. Learn transformer architecture, prompt engineering, fine-tuning LLMs, LangChain, RAG systems, and building multi-agent workflows with CrewAI and LangGraph. Deploy production-ready AI applications safely.
Course Requirements
- Intermediate Python programming skills
- Familiarity with APIs and basic ML concepts is helpful
- OpenAI API key (free tier is sufficient for most exercises)
- Curiosity about the future of AI-driven software
What You Will Learn
- Understand transformer architecture and how LLMs generate text
- Write effective prompts using few-shot, chain-of-thought, and ReAct patterns
- Fine-tune LLMs using LoRA and QLoRA techniques
- Build Retrieval-Augmented Generation (RAG) pipelines with LangChain
- Set up and query vector databases (Pinecone, FAISS, Chroma)
- Create autonomous AI agents with tool use and memory systems
- Orchestrate multi-agent workflows using CrewAI and LangGraph
- Deploy and monitor LLM applications safely in production
Video: AI & ML Fundamentals
10:00
Video: AI/ML Applications & Use Cases
10:00
Video: Machine Learning Algorithms
10:00
Video: Supervised & Unsupervised Learning
10:00
Video: Model Training, Testing & Validation
10:00
Video: Model Evaluation & Optimization
10:00
Video: Ensemble Methods
10:00
Video: Python Programming Fundamentals
10:00
Video: Variables, Data Types & Operators
10:00
Video: Conditional Statements & Loops
10:00
Video: Functions & Functional Programming
10:00
Video: Lists, Tuples & Dictionaries
10:00
Video: Modules & Packages
10:00
Video: File & Directory Handling
10:00
Video: Exception Handling
10:00
Video: Object-Oriented Programming
10:00
Video: Regular Expressions
10:00
Video: NumPy, Pandas & Scientific Computing
10:00
Video: Python for AI/ML Applications
10:00
Video: Descriptive & Basic Statistics
10:00
Video: Sampling & Sampling Statistics
10:00
Video: Inferential Statistics
10:00
Video: Hypothesis Testing
10:00
Video: Probability & Probability Distributions
10:00
Video: Calculus Fundamentals
10:00
Video: Derivatives & Optimization
10:00
Video: Linear Algebra
10:00
Video: Scalars, Vectors & Matrices
10:00
Video: Vector Operations
10:00
Video: Mathematical Foundations for ML
10:00
Video: Linear Regression
10:00
Video: Logistic Regression
10:00
Video: K-Means Clustering
10:00
Video: Hierarchical Clustering
10:00
Video: K-Nearest Neighbors
10:00
Video: Decision Trees
10:00
Video: Random Forest
10:00
Video: Bagging & Boosting
10:00
Video: Gradient Descent
10:00
Video: Train/Test/Validation
10:00
Video: Model Selection & Evaluation
10:00
Video: Neural Network Fundamentals
10:00
Video: Perceptron & Multilayer Perceptron
10:00
Video: Feedforward & Backpropagation
10:00
Video: Neural Network Architecture
10:00
Video: Activation Functions
10:00
Video: Loss Functions
10:00
Video: Gradient Descent
10:00
Video: Deep Learning Concepts
10:00
Video: Model Strengths & Limitations
10:00
Video: Hyperparameters & Model Training
10:00
Video: Train/Test/Validation Strategies
10:00
Video: Hyperparameters & Parameter Tuning
10:00
Video: Regularization
10:00
Video: Dropout
10:00
Video: Vanishing & Exploding Gradients
10:00
Video: Learning Rate Optimization
10:00
Video: RMSProp & Adam
10:00
Video: Ada / AdaBoost
10:00
Video: Softmax
10:00
Video: Bias Correction
10:00
Video: Computer Vision Fundamentals
10:00
Video: Image Preprocessing
10:00
Video: Image Transformation & Filtering
10:00
Video: Noise Removal & Edge Detection
10:00
Video: Non-Maximum Suppression
10:00
Video: Object Detection
10:00
Video: Bounding Boxes & Detection Models
10:00
Video: Landmark Detection
10:00
Video: R-CNN, Fast R-CNN & Faster R-CNN
10:00
Video: Mask R-CNN & YOLO
10:00
Video: Transfer Learning
10:00
Video: Image Segmentation
10:00
Video: Face Detection & Recognition
10:00
Video: Style Transfer
10:00
Video: Speech Processing Fundamentals
10:00
Video: Automated Speech Recognition — ASR
10:00
Video: Speech Synthesis
10:00
Video: Text-to-Speech — TTS
10:00
Video: Voice Assistant Applications
10:00
Video: Alexa Skill Development
10:00
Video: Autoencoders & Decoders
10:00
Video: Variational Autoencoders — VAE
10:00
Video: Generative AI Foundations
10:00
Video: Generative Adversarial Networks — GANs
10:00
Video: GAN Architecture & Training
10:00
Video: GAN Evaluation
10:00
Video: Conditional & Advanced GANs
10:00
Video: Image Translation & CycleGAN
10:00
Video: Generative AI Applications
10:00
Video: Reinforcement Learning Fundamentals
10:00
Video: Q-Learning
10:00
Video: Exploration & Exploitation
10:00
Video: Deep Reinforcement Learning
10:00
Video: OpenAI Gym
10:00
Video: Policy Gradient Methods
10:00
Video: Actor-Critic Methods
10:00
Video: Proximal Policy Optimization — PPO
10:00
Video: Reinforcement Learning Applications
10:00
Video: Time-Series Forecasting
10:00
Video: ARIMA
10:00
Video: RNN-Based Forecasting
10:00
Video: LSTM-Based Forecasting
10:00
Video: Transformer-Based Forecasting
10:00
Video: NLP Fundamentals
10:00
Video: Text Mining
10:00
Video: Vector Space Models
10:00
Video: Word Embeddings
10:00
Video: RNN, GRU & LSTM for NLP
10:00
Video: Named Entity Recognition
10:00
Video: Document Similarity
10:00
Video: Word Clouds
10:00
Video: Sentiment / Emotion Mining
10:00
Video: Machine Translation
10:00
Video: Web Scraping
10:00
Video: Naive Bayes Text Classification
10:00
Video: Bayesian Concepts
10:00
Video: Apriori & Posterior Distributions
10:00
Video: Transformer Architecture
10:00
Video: Attention Mechanisms
10:00
Video: Single-Head & Multi-Head Attention
10:00
Video: Encoder Models
10:00
Video: BERT, RoBERTa & DistilBERT
10:00
Video: Decoder Models
10:00
Video: GPT & GPT-2
10:00
Video: Sequence-to-Sequence Models
10:00
Video: BART & T5
10:00
Video: Pre-trained Transformer Models
10:00
Video: OpenAI API Integration
10:00
Video: LLM Applications & Playgrounds
10:00
Video: ChatGPT Fundamentals
10:00
Video: AI & ChatGPT Evolution
10:00
Video: ChatGPT Architecture
10:00
Video: ChatGPT Capabilities & Applications
10:00
Video: Professional Content Generation
10:00
Video: Research & Information Gathering
10:00
Video: Resume & Communication Assistance
10:00
Video: Brainstorming & Problem Solving
10:00
Video: AI Limitations & Ethical Considerations
10:00
Video: ChatGPT Best Practices
10:00
Video: Generative AI Foundations
10:00
Video: Descriptive vs Generative AI
10:00
Video: NLP & LLM Fundamentals
10:00
Video: GPT & ChatGPT
10:00
Video: Prompt Engineering Fundamentals
10:00
Video: Prompt-Based Content Generation
10:00
Video: Tokens & Parameters
10:00
Video: Zero-Shot, One-Shot & Few-Shot Prompting
10:00
Video: Advanced Prompt Optimization
10:00
Video: Fine-Tuning Parameters
10:00
Video: Hallucination & Bias
10:00
Video: Prompt Evaluation & Testing
10:00
Video: Prompt Quality Metrics
10:00
Video: Human Evaluation
10:00
Video: Multi-Model Prompt Testing
10:00
Video: LLM Fundamentals & Use Cases
10:00
Video: Text Generation & Chatbot Development
10:00
Video: Generative Model Foundations
10:00
Video: Transformers & Attention
10:00
Video: GANs & Autoencoders
10:00
Video: Reinforcement Learning & RLHF
10:00
Video: Real-World LLM Applications
10:00
Video: Instruction Fine-Tuning
10:00
Video: Single-Task & Multi-Task Fine-Tuning
10:00
Video: LLM Evaluation & Benchmarks
10:00
Video: Parameter-Efficient Fine-Tuning — PEFT
10:00
Video: LoRA & Soft Prompting
10:00
Video: ROUGE, BLEU, METEOR & CIDEr
10:00
Video: MLOps Fundamentals
10:00
Video: ML Project Lifecycle
10:00
Video: MLOps Stages & Roles
10:00
Video: ML Workflow Design & Development
10:00
Video: Pipelines & Pipeline Steps
10:00
Video: Artifacts & Materializers
10:00
Video: Parameters & Configuration
10:00
Video: ML Execution & Components
10:00
Video: Orchestration
10:00
Video: Artifact Stores
10:00
Video: ML Server Infrastructure
10:00
Video: Metadata Tracking
10:00
Video: Collaboration & Dashboards
10:00
Eswar
4
Courses
7 Enrolled
Senior Full Stack Developer with 10+ years of experience in Python, Django, and cloud infrastructure. Has trained 5,000+ students at top tech bootcamps across India. Previously at Infosys and Flipkart.
Reviews (5)
Preethi Krishnan
1 week from nowExcellent content and well-structured curriculum. I landed a job within 2 months of completing this course. Worth every rupee!
Vivek Chaudhary
3 weeks agoThe hands-on projects are really practical and relevant to real-world scenarios. The instructor is very responsive to questions.
Rashmi Pandey
2 months agoBest course I have taken online. The depth of content is incredible and the examples are very easy to follow.
Aditya Rao
3 months agoThis course completely transformed my understanding. The instructor breaks down complex concepts into digestible lessons. Highly recommend!
Meghna Das
3 months agoGood course overall. The video quality is great and the explanations are clear. Would love more practice exercises.
