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Agentic AI Masters 2026 LangChain, LangGraph & CrewAI
Published 6/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 58h 8m | Size: 33 GB
Master Python to Production-Grade AI Agents: NLP, LLMs, RAG, LangGraph, CrewAI, n8n & Multi-Agent Systems
What you'll learn
Build a solid foundation in Python programming to effectively implement AI concepts and applications.
Understand the complete pipeline of Natural Language Processing, from data preprocessing to model deployment.
Learn how transformer models revolutionize NLP tasks, and how to leverage them for various applications.
Explore the essentials of Large Language Models (LLMs) and their applications in generative tasks.
Gain hands-on experience with Retrieval-Augmented Generation (RAG) and Langchain for building advanced AI applications.
Develop skills in crafting effective prompts to optimize model performance and achieve desired outputs.
Learn how to utilize vector databases for efficient storage and retrieval of embeddings in AI projects.
Requirements
Basic knowledge on Machine Learning is beneficial but not mandatory
Description
TheAgentic AI Masters 2026 is a complete, end-to-end mastery program designed to take you from Python fundamentals all the way to building autonomous, production-ready AI agents.
This comprehensive course covers the entire modern AI stack. You will start with strong Python foundations and progress through classical NLP techniques (tokenization, stopwords, n-grams, Bag of Words, TF-IDF, POS tagging, NER), word embeddings (Word2Vec CBOW & SkipGram, GloVe, FastText), and deep learning architectures including ANNs, CNNs, RNNs, LSTMs, GRUs, and bi-directional models.
You will then master the revolutionaryTransformer architecture (encoder-only, decoder-only, and full encoder-decoder) and dive deep into Large Language Models — understanding tokens, context windows, prompt engineering, prompt tuning, and working with leading models from OpenAI, xAI, and local deployment using Ollama.
The course features extensive coverage ofRetrieval Augmented Generation (RAG), vector databases vs vector indexes, advanced RAG architectures, evaluation metrics, and RAG assessment frameworks. You will also learn model fine-tuning techniques and how to deploy generative AI applications in production.
In theAgentic AI specialization phase, you will master
- LangChain for building intelligent chains and agents
- LangGraph for creating reliable, stateful, controllable multi-agent workflows
- CrewAI for orchestrating role-based collaborative AI teams
- Low-code automation using n8n
- Implementation of guardrails for safe and reliable agents
- Advanced multi-agent systems design and orchestration
Throughout the program, you will work on multiple real-world projects that simulate industry use cases — from intelligent document Q&A systems and automated research agents to smart assistants, workflow automation, and complex multi-agent solutions.
By the end of this course, you will have the confidence and practical skills to design, develop, evaluate, and deploy sophisticated agentic AI systems that can reason, plan, use tools, and collaborate — making you job-ready for the rapidly growing demand in the agentic AI space.
Whether you are a developer, data scientist, AI engineer, or tech professional looking to future-proof your career,Agentic AI Masters 2026 delivers the deepest, most practical, and up-to-date education in building the next generation of AI agents.
Who this course is for
Individuals passionate about AI and ML who want to expand their knowledge and skills in generative AI applications.
Professionals looking to enhance their expertise in building and deploying generative AI models
Developers interested in integrating advanced AI capabilities into their applications and learning about the deployment and optimization of AI models.
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