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🦙 LangChain & Ollama
Master local LLM integration and agent workflows. Build self-correcting RAG systems, chatbots, and stateful multi-agent architectures using LangChain, LangGraph, and Ollama.
Skills You'll Master
Agentic RAG
Implement corrective, self-improving RAG systems with local models like DeepSeek R1 and Llama.
LangGraph Workflows
Design stateful multi-agent loops and state machine graphs for complex tasks.
Local LLMs & Ollama
Run open-source models locally without external API dependencies or costs.
Vector Databases
Integrate FAISS and ChromaDB vector stores for efficient semantic context retrieval.
Udemy CourseMCP Mastery: Build AI Apps with Claude, LangChain and Ollama
Build MCP servers & clients with Python, Streamlit, ChromaDB, LangChain, LangGraph agents, and Ollama integrations.
What you'll master:
- MCP Architecture: Client, server, and transport layers
- Claude Desktop Integration: Direct MCP server connections
- Real-World Applications: Data analysis servers for Excel, PowerPoint, SQLite
- RAG Implementation: Vector databases with LangChain integration
- Production Deployment: Testing, security, and cloud deployment
Udemy CourseAgentic AI - Private Agentic RAG with LangGraph and Ollama
Step-by-Step Guide to RAG with LangChain, LangGraph, and Ollama | DeepSeek R1, QWEN, LLAMA, FAISS.
What you'll master:
- Agentic RAG: Intelligent, adaptive systems that act like smart assistants
- Corrective RAG: Self-improving and error-correcting mechanisms
- Document Processing: Doclings integration for seamless document loading
- Production Ready: Streamlit apps and AWS EC2 deployment
Udemy CourseMaster Langchain v1 and Ollama - Chatbot, RAG and AI Agents
Master Langchain v1, Local LLM Projects, Ollama, DeepSeek, LLAMA 3.2, Complete Integration Guide.
What you'll master:
- Setup & Integration: Professional Ollama and Langchain configuration
- Custom Chatbots: Memory, history, and advanced features with Streamlit
- Prompt Engineering: Templates, chains (Sequential, Parallel, Router)
- Agent Development: Custom tools and step-by-step instruction execution
- AWS Deployment: Production-ready applications on AWS EC2
Udemy CourseMaster LangGraph v1 and Ollama - Build Gen AI Agents
Agentic RAG and Chatbot, AI Agent, DeepSeek, LLAMA 3.2 Agent, FAISS Vector Database.
What you'll master:
- Memory-Enabled Chatbots: Dynamic conversations with persistent memory
- Database Integration: Seamless MySQL query execution with LLMs
- State Management: LangGraph workflows with advanced state machines
- Private Data RAG: Custom embeddings and vector database integration
🤖 AI Agents & Advanced
Dive into production-ready agent engineering, multi-agent orchestrations, MCP servers, and LLM fine-tuning with Hugging Face for custom NLP tasks.
Skills You'll Master
Multi-Agent Systems
Design supervisor agents, specialist routing, and coordination structures using LangGraph.
Model Fine-Tuning
Adapt open-source models to proprietary datasets using Hugging Face and PyTorch.
Model Context Protocol (MCP)
Connect agents to files, SQLite databases, financial tools, and local utilities.
Production API & UIs
Build streaming APIs with FastAPI and responsive user interfaces with Chainlit and Streamlit.
Udemy CourseAgentic AI: Deploy LangChain v1 Agent Projects to Production
Build real AI agents using LangChain and Google Gemini — deploy with FastAPI and AWS EC2.
What you'll master:
- Agent Architecture: ReAct reasoning, tool calling, and structured decision making
- Memory Systems: Short-term and long-term memory using databases and embeddings
- Safety & Guardrails: Human-in-the-loop, middleware controls, and sandboxed code execution
- Production APIs: FastAPI REST endpoints with validation, CORS, and SSE streaming
- Full-Stack AI Apps: Streamlit UI connected to LangChain agents
- + 1 more modules
Udemy CourseDeep Agent - Multi Agent RAG with Gemini and Langchain
Build real-world AI agents and deep research systems using Google Gemini, LangChain v1, MCP, and modern RAG techniques.
What you'll master:
- Agent Foundations: ReAct patterns, tool calling, memory, and state management
- Gemini + LangChain Bootcamp: Streaming, multimodal inputs, function calling, and context caching
- MCP Finance Agent: Connect Yahoo Finance MCP server as LangChain tools for stock research
- Multimodal Deep RAG: Extract and process financial PDFs, tables, and images with Docling
- Qdrant Vector Database: Hybrid search, sparse+dense retrieval, metadata filtering, and de-duplication
- + 1 more modules
Udemy CourseFine Tuning LLM with Hugging Face Transformers for NLP
Learn transformer architecture fundamentals and fine-tune LLMs with custom datasets.
What you'll master:
- Transformer Deep Dive: Architecture fundamentals and mathematical foundations
- Custom Dataset Preparation: Data preprocessing and formatting techniques
- Fine-tuning Mastery: Advanced optimization and training strategies
- Model Optimization: Performance tuning and evaluation methodologies
Udemy CourseMaster OpenAI Agent Builder - Deploy Chatbot to Your Website
Build and deploy AI agents visually using OpenAI Agent Builder, ChatKit, RAG, Chatbot, AI Assistant with MCP, AWS, RDS MySQL.
What you'll master:
- Visual AI Development: Build AI agents without complex coding using OpenAI Agent Builder
- Real-World Integration: Connect AI workflows with MySQL, AWS, and MCP connectors
- Production Deployment: Deploy AI agents with ChatKit and Guardrails for safety
- Complete Projects: Weather Agent, RAG Document Q&A Chatbot, E-Commerce AI Assistant
- Database Integration: AWS RDS MySQL connection and management
- + 1 more modules
Udemy CourseAdvanced RAG: Build & Deploy Production GenAI Apps
Build RAGWire — a production-grade RAG toolkit with LangChain, Qdrant, and LangGraph — from hybrid search to multi-cloud deployment.
What you'll master:
- Hybrid RAG Pipeline: BM25 sparse + dense retrieval with Reciprocal Rank Fusion (RRF)
- Multi-LLM Support: OpenAI GPT, Groq, Google Gemini, Ollama, and HuggingFace embeddings
- Agentic RAG: Self-correcting agents that grade retrieval quality and rewrite queries
- Multi-Agent Systems: Supervisor agents with CrewAI, Microsoft AutoGen, and LangGraph routing
- Production UI & API: Chainlit chat UI with auth + FastAPI OpenAI-compatible endpoints with SSE
- + 1 more modules
📊 Machine Learning and Data Science
Establish a bulletproof foundation in mathematical and statistical analysis, regression modeling, exploratory data analysis (EDA), and core machine learning models.
Skills You'll Master
Data Preprocessing
Master NumPy and Pandas to clean, structure, and manipulate raw dataset files.
ML Algorithms
Implement supervised and unsupervised models including linear regression and decision trees.
Deep Learning Basics
Build Artificial Neural Networks (ANN) and sequence models (LSTM) using TensorFlow.
Feature Engineering
Extract numeric values from messy text, handle missing data, and normalize input features.
Udemy CourseDeep Learning for Beginners with Python
Neural Networks, TensorFlow, ANN, CNN, RNN, LSTM, Transfer Learning and Much More.
What you'll master:
- Artificial Neural Networks (ANN): Build from mathematical foundations
- Convolutional Neural Networks (CNN): Image processing and computer vision
- Recurrent Neural Networks (RNN): Sequential data and time series analysis
- LSTM Networks: Advanced sequence modeling and memory networks
- Transfer Learning: Leverage pre-trained models for custom applications
Udemy CoursePython for Linear Regression in Machine Learning
Master statistical foundations and practical implementation of regression analysis.
What you'll master:
- Regression Theory: Mathematical foundations and statistical principles
- Hypothesis Testing: Statistical validation and significance testing
- Feature Engineering: Variable selection and transformation techniques
- Model Evaluation: R-squared, RMSE, and comprehensive diagnostics
- Business Applications: Real-world predictive modeling scenarios
Udemy CourseMachine Learning & Data Science for Beginners in Python
Complete foundation in ML and DL using Python, Scikit-Learn, Keras, and TensorFlow.
What you'll master:
- Python for Data Science: From basics to advanced data manipulation
- Data Analysis Mastery: Pandas, NumPy, and exploratory data analysis
- Machine Learning: Supervised and unsupervised learning algorithms
- Deep Learning Introduction: Neural networks with Keras and TensorFlow
- Data Visualization: Professional charts and insights presentation
Udemy CourseNatural Language Processing in Python for Beginners
Build NLP models using Python with Spacy, NLTK, and modern NLP techniques.
What you'll master:
- Text Processing: Spacy and NLTK for production-ready NLP
- Sentiment Analysis: Emotion detection and opinion mining
- Named Entity Recognition: Extract people, places, organizations
- Text Classification: Document categorization and content analysis
- Feature Engineering: TF-IDF, word embeddings, and advanced features
🚀 Production and Deployment
Bridge the gap between experimental notebooks and production code. Learn how to wrap models in FastAPI microservices, containerize with Docker, and deploy to AWS at scale.
Skills You'll Master
FastAPI Microservices
Expose trained model predictions through high-performance REST APIs.
Docker Containers
Package applications into lightweight, self-contained units for reliable cross-platform execution.
AWS Cloud Hosting
Deploy secure, production-ready instances on EC2, Lambda, and API Gateway.
DevOps & Monitoring
Configure NGINX, uWSGI, uvicorn, and implement automated prediction logging and health checks.
Udemy CourseDeploy ML Model in Production with FastAPI and Docker
Professional deployment strategies using FastAPI, Docker, and modern DevOps practices.
What you'll master:
- FastAPI Development: High-performance API creation for ML models
- Docker Containerization: Scalable and portable deployment solutions
- Cloud Deployment: AWS, GCP, and Azure deployment strategies
- Security & Monitoring: Authentication, logging, and performance monitoring
- DevOps Integration: CI/CD pipelines and automated deployment