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Agentic Knowledge Graphs
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 17m | Size: 233 MB​

AI agents often generate answers without true understanding or explainability.
This course will teach you how to design agent-driven knowledge graphs that enable structured reasoning, contextual understanding, and explainable decision-making.

What you’ll learn
Many AI agents can retrieve information but still fail to reason effectively or explain how they reach their conclusions.
In this course, Agentic Knowledge Graphs, you’ll learn to design and build agent-driven knowledge graphs that enhance reasoning and explainability in AI systems.
First, you’ll explore the foundations of knowledge graphs, including entities, relationships, and schemas that support agentic reasoning.
Next, you’ll discover how to construct and integrate knowledge graphs using agents that extract and connect data from structured and unstructured sources.
Finally, you’ll learn how to apply knowledge graphs in real-world agentic workflows using tools like Neo4j and LangChain to enable contextual querying and explainable decision-making.
When you’re finished with this course, you’ll have the skills and knowledge of agentic knowledge graphs needed to build intelligent, structured, and transparent AI agents that provide reasoning.

Free Download Agentic AI Mastery Multi-Agent Systems in Practice
Published 4/2026
Created by School of AI
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 18 Lectures ( 2h 35m ) | Size: 1.52 GB

Build production-ready multi-agent AI systems with orchestration, tools, memory, and deployment in 3 days
What you’ll learn
✓ Design and build multi-agent AI systems with specialized agent roles
✓ Implement agent orchestration workflows (Planner-Worker, Manager-Executor patterns)
✓ Integrate tools, APIs, and RAG-based memory into agent systems
✓ Develop production-ready architectures with FastAPI and simple UIs
✓ Apply guardrails, evaluation, and monitoring for reliable AI systems
✓ Optimize systems using parallel execution, caching, and cost control
Requirements
● Basic understanding of AI/LLMs (helpful but not required)
● Beginner-level Python knowledge (variables, functions, basic scripts)
● Familiarity with using tools like ChatGPT or Claude
● A computer capable of running Python (Mac, Windows, or Linux)
● Internet connection for accessing APIs and tools
● Willingness to build hands-on projects and experiment
Description
"This course contains the use of artificial intelligence"
The future of AI is no longer about single prompts-it’s about building multi-agent systems that can plan, execute, collaborate, and deliver real outcomes.
In Agentic AI Mastery: Multi-Agent Systems in Practice, you will learn how to move beyond basic LLM usage and start building production-ready AI systems that mirror how real companies are deploying AI today.
Most courses focus on prompt engineering. This course focuses on agentic AI architecture-how to design systems where multiple specialized agents work together to solve complex problems. You’ll learn how to structure Planner-Worker workflows, implement agent orchestration, and build systems that scale beyond simple tasks.
This is a highly hands-on program. You won’t just learn concepts-you will build real systems. Starting with a single agent, you’ll progress to multi-agent architectures with clearly defined roles, structured communication, and coordinated execution. You’ll implement tool usage, integrate APIs, and add memory layers using techniques like RAG (Retrieval-Augmented Generation) to enable context-aware reasoning.
You’ll also explore modern frameworks such as LangGraph, CrewAI, and AutoGen, while understanding when to use frameworks versus building your own orchestration layer. This ensures you gain both practical skills and architectural thinking.
Beyond building, you’ll learn what it takes to make systems production-ready. You’ll implement guardrails to control hallucinations and prevent prompt injection, design evaluation pipelines using metrics like task success and output quality, and add observability and monitoring to track system behavior, latency, and cost.
Deployment is a core part of this course. You will expose your system through a FastAPI backend, build a simple interface using Streamlit, and understand how to scale systems using async workflows, queue-based architectures, and caching strategies. You’ll also learn how to optimize performance and reduce costs using token management and efficient system design.
By the end of the program, you will build a production-style AI company system-a portfolio-ready project with multiple agents, orchestration, memory, monitoring, and API access. This is the kind of system that reflects how AI is actually being used in enterprise environments.
This course is designed for builders, engineers, product leaders, and anyone serious about mastering agentic AI systems. If you want to move from simple LLM usage to designing scalable AI architectures, this program will give you the skills to do it.
The shift is already happening-from prompts to systems, from tools to AI-powered teams.
This course helps you stay ahead of that shift.
Who this course is for
■ Developers and engineers who want to build real-world AI systems, not just prompts
■ Product managers and tech leaders exploring agentic AI and automation strategies
■ AI enthusiasts looking to move from theory to hands-on system building
■ Founders and builders creating AI-powered products or startups
■ Professionals aiming to future-proof their careers with multi-agent system skills
■ Anyone serious about going from LLMs → Agent Systems → Production AI
Homepage
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https://www.udemy.com/course/agentic-ai-mastery-multi-agent-systems-in-practice

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Free Download Agentic AI Masterclass 2026 Build Autonomous AI Agents
Published 4/2026
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 16m | Size: 193.38 MB
Learn Agentic AI, build autonomous AI agents, automation workflows, and real AI systems with practical projects.

What you’ll learn
Understand AI agents and automation systems and how they work in real-world applications across business, productivity, and digital workflows.
Build practical AI agents for tasks like research, email writing, content generation, and productivity automation using modern AI tools.
Use prompt engineering and AI workflows to automate repetitive tasks and improve efficiency using generative AI systems.
Create real AI tools and assistants step-by-step using no-code tools and optional Python integrations for advanced automation.
Requirements
No prior AI or coding experience required. Basic computer skills and internet access are enough. Python knowledge is optional but helpful.
Description
Artificial Intelligence is evolving rapidly, and Agentic AI is the next major breakthrough. Unlike traditional AI systems that simply respond to prompts, AI agents can plan, reason, and perform tasks autonomously.
In this course, you will learn how to build autonomous AI agents and intelligent automation systems step-by-step.
This course is designed to help you understand Agentic AI concepts, AI agent architecture, automation workflows, and practical AI applications. By the end of this course, you will be able to create real AI agents capable of performing tasks such as research, content generation, automation, and productivity assistance.
We will cover both fundamental concepts and practical projects, ensuring that you gain hands-on experience while learning the theory behind intelligent AI systems.
You will explore how modern AI tools, large language models, and automation frameworks work together to create powerful AI agents that can automate real-world tasks.
What makes this course unique
• Learn the fundamentals of Agentic AI and autonomous AI systems
• Understand how AI agents plan, reason, and execute tasks
• Build practical AI agents for automation and productivity
• Learn real-world AI automation workflows
• Explore the future of autonomous AI technology
Why learn Agentic AI?
Agentic AI is one of the fastest growing areas in artificial intelligence. Companies are increasingly adopting AI agents to automate workflows, improve productivity, and build intelligent digital assistants.
Understanding how to design and build AI agents will give you a valuable future-ready skill in the rapidly evolving AI industry.
By the end of this course you will be able to
• Understand the core principles of Agentic AI
• Build autonomous AI agents and intelligent workflows
• Use AI tools to automate tasks and improve productivity
• Design and implement practical AI automation systems
Start your journey into Agentic AI
If you want to understand the next generation of artificial intelligence and autonomous systems, this course will guide you step-by-step.
Join now and start learning how to build intelligent AI agents and automation systems.
Who this course is for
Beginners, professionals, entrepreneurs, and developers who want to learn AI automation and build AI agents to increase productivity or create AI tools.

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Agentic AI in Cybersecurity
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 1m 24s | Size: 183 MB​

AI-driven security systems are evolving quickly, but many organizations struggle to effectively integrate autonomous, decision-making agents into their cybersecurity workflows.

What you’ll learn
AI-driven security systems are evolving quickly, but many organizations struggle to effectively integrate autonomous, decision-making agents into their cybersecurity workflows. In this course, Agentic AI in Cybersecurity, you’ll gain the ability to implement agentic AI in your cybersecurity workflows. First, you’ll explore the basics of agentic AI and its design paradigms. Next, you’ll discover various security considerations when attempting to utilize agentic AI in your organization. Finally, you’ll learn about Ollama and how it can be used to implement agentic AI solutions in your organization.

Free Download Agentic AI for Beginners Build Business AI Agents Bootcamp
Published 3/2026
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 5h 33m | Size: 2.06 GB
Learn to Create Intelligent AI Agents with Python, LangChain & LLMs for Real-World Business Automation

What you’ll learn
Understand the fundamentals of Agentic AI and how autonomous agents think, plan, and act
Build AI agents from scratch using Python, LLMs, and LangChain
Create real-world business use cases like AI customer support, resume analyzer, and research assistant
Implement RAG (Retrieval-Augmented Generation) to connect custom data with AI agents
Learn how to integrate local LLMs (like Ollama) for secure and offline AI solutions
Handle error management, retries, and performance monitoring in AI agents
Deploy AI agents using tools like Streamlit for real-time applications
Build AI solutions for freelancing, startups, and enterprise use cases
Gain hands-on experience through real-world projects and practical implementations
Requirements
No programming experience needed. You will learn everything you need to know
Basic understanding of computers and internet usage
Beginner-level knowledge of Python programming (variables, functions, basics) is helpful but not mandatory
No prior experience in AI, Machine Learning, or LangChain required – everything will be taught from scratch
Description
Step into the Future with Agentic AI and Build Real-World Business AI Agents from Scratch!
The course Agentic AI for Beginners: Build Business AI Agents Bootcamp is designed to help you master one of the most in-demand skills in today’s AI-driven world. Whether you are a beginner, developer, freelancer, or entrepreneur, this course will guide you step-by-step in building intelligent AI agents using Python, Large Language Models (LLMs), and LangChain-no prior experience required.
In this hands-on bootcamp, you will learn how Agentic AI systems think, plan, and act autonomously to solve real-world business problems. You will gain practical experience by building powerful AI agents and integrating them with real-world use cases such as customer support automation, resume analysis, research assistance, and personal productivity systems. The course also covers advanced concepts like RAG (Retrieval-Augmented Generation), connecting custom data to agents, and designing multi-agent systems for scalable automation.
This course is carefully structured for a Beginners, with clear explanations, real-world examples, and production-focused implementations. You will not just learn theory-you will build, test, and deploy AI agents that can be used in freelancing projects, start-ups, or enterprise environments.
By the end of this course, you will have the confidence and skills to create production-ready AI agents that automate tasks, improve efficiency, and unlock new career opportunities in artificial intelligence.
Don’t just learn AI-start building intelligent systems that work for you.
Enroll now and begin your journey into Agentic AI today!
Who this course is for
Beginners who want to start their journey in Agentic AI and AI development
Students and professionals looking to build skills in Python, LLMs, and LangChain
Developers who want to create real-world AI agents and automation systems
Freelancers aiming to offer AI-based services and solutions to clients
Entrepreneurs and startup founders interested in automating business workflows using AI
Tech enthusiasts who want to explore cutting-edge AI technologies and tools
Anyone curious about building intelligent systems that can think, plan, and act autonomously
Professionals looking to upgrade their skills and stay relevant in the AI-driven job market

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Free Download Agentic AI Engineering with Claude Code
Published 3/2026
Created by Data Science Academy
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 20 Lectures ( 5h 2m ) | Size: 2 GB

Design, build, and scale autonomous AI systems with memory, tools, and multi-agent workflows
What you’ll learn
✓ Design and build autonomous AI agents that can plan, reason, and execute multi-step tasks independently
✓ Implement tool calling and integrations to connect AI agents with APIs, databases, and real-world systems
✓ Develop memory systems (short-term and long-term) to create context-aware and intelligent AI behavior
✓ Build and orchestrate multi-agent systems with supervisor-worker architectures and task delegation
✓ Apply planning and decision-making techniques to enable goal-driven and adaptive AI workflows
✓ Optimize and scale AI systems for performance, cost efficiency, and real-world deployment
Requirements
● Basic understanding of Python or any programming language (helpful but not mandatory)
● Familiarity with AI tools like ChatGPT or Claude is beneficial
● A laptop or computer with internet access
● Willingness to learn by building real projects and experimenting
● Basic understanding of APIs or workflows (optional, will be covered)
Description
"This course contains the use of artificial intelligence"
Are you ready to go beyond simple AI tools and start building autonomous AI systems that can think, plan, act, and improve on their own?
This course is your complete, hands-on guide to mastering Agentic AI systems using Claude Code, designed for developers, data professionals, and AI enthusiasts who want to build real-world, production-ready AI solutions.
Unlike traditional AI courses that focus only on prompts or isolated tools, this program is built around system design thinking. You will learn how to design and build intelligent agents that can reason, make decisions, use tools, manage memory, and execute multi-step workflows-just like real AI systems used in industry today.
Throughout the course, you’ll explore the full lifecycle of agentic AI, starting from foundational concepts and moving into advanced topics like planning systems, tool calling, memory architecture, and multi-agent orchestration. You will understand how to transform simple AI capabilities into powerful systems that can automate complex tasks with minimal human input.
This is a deeply practical course. You won’t just learn concepts-you will build real projects including an AI Content Agent, a Business Automation Agent, and a fully functional Multi-Agent System with supervisor and worker agents. These projects are designed to mirror real-world applications such as content pipelines, automated reporting systems, and intelligent decision-making workflows.
You will also learn how to design context-aware agents using short-term and long-term memory, implement retrieval strategies, and avoid common pitfalls like token overload and inefficient reasoning. As you progress, you’ll gain expertise in tool integration, connecting agents with APIs, databases, and external systems to enable real-time execution.
One of the most powerful parts of this course is the focus on multi-agent systems, where multiple AI agents collaborate, communicate, and coordinate tasks. You’ll learn advanced patterns like supervisor-worker architectures, task delegation, and agent communication strategies, enabling you to build scalable and modular AI systems.
In addition, the course covers autonomous feedback loops and self-improving systems, teaching you how to design agents that can observe, evaluate, and refine their own outputs over time. You’ll also explore debugging, safety, and guardrails, ensuring your AI systems are reliable, controllable, and production-ready.
Finally, you’ll learn how to scale agentic systems, optimize for performance and cost, and design your own AI Operating System-a unified system that combines agents, workflows, memory, and automation into a powerful personal or business tool.
By the end of this course, you won’t just understand AI-you’ll be able to design, build, and deploy intelligent AI systems that solve real-world problems.
Whether your goal is to become an AI Engineer, an AI Systems Architect, or build your own AI-powered products or SaaS, this course will give you the skills, mindset, and hands-on experience needed to succeed in the rapidly evolving world of AI.
Who this course is for
■ Developers and engineers who want to move beyond prompts and build real AI systems and agents
■ Data professionals and analysts looking to expand into AI engineering and automation
■ AI enthusiasts who want to understand how to build autonomous, decision-making systems
■ Product builders and founders interested in creating AI-powered tools, workflows, or SaaS products
■ Anyone curious about the future of AI and wants to learn how agentic systems actually work in practice
Homepage
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https://www.udemy.com/course/agentic-ai-engineering-with-claude-code

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Free Download Agentic AI Build Your First Agentic AI System
Released 3/2026
With Aishwarya Naresh Reganti
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Skill Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 1h 5m | Size: 158 MB

Learn how to build your first agentic AI system as you evaluate real-world opportunities, incorporate effective tools, and transform your theoretical AI knowledge into practical skills.
Course details
Dive into agentic AI and master the skills you need to build scalable, real-world systems within an enterprise environment. In this course, industry expert Aishwarya Naresh Reganti shows you how to identify suitable business problems for agentic AI solutions, break down systems, iterate designs from baseline to advanced setups, and evaluate design trade-offs. Learn how to apply a comprehensive CCCD (Continuous Calibration Continuous Development) framework to safely increase AI autonomy while maintaining user trust. Tackle complex AI challenges as you gain insights on guardrails, governance, and security. This course is suited for engineers, product managers, enterprise leaders, and anyone eager to move beyond AI basics and implementation hurdles. Whether you’re enhancing your existing skills or seeking to refine AI systems from concept to execution, this course delivers valuable knowledge for practical applications.
Skills covered
AI Agents, Generative AI, Artificial Intelligence (AI)
Homepage
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https://www.linkedin.com/learning/agentic-ai-build-your-first-agentic-ai-system

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Free Download Agentic AI Bootcamp Build Autonomous AI Systems in 3 Days
Published 4/2026
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 55m | Size: 2.26 GB
Design, build, and deploy production-ready multi-agent AI systems with tools, memory, and real workflows

What you’ll learn
Understand how Agentic AI systems work (agents, reasoning, tools, memory)
Build single-agent systems with tool usage and retrieval-based memory
Design and implement multi-agent architectures for complex workflows
Use frameworks like LangGraph, CrewAI, and AutoGen for orchestration
Integrate RAG (Retrieval-Augmented Generation) for grounded, accurate responses
Connect agents to real-world systems via APIs and automation tools (Zapier, n8n)
Implement evaluation pipelines (LLM-as-a-Judge, test cases, regression testing)
Add guardrails and safety mechanisms to prevent failures and misuse
Monitor systems with logging, observability, and performance tracking
Design scalable, production-ready AI architectures for enterprise use cases
Requirements
Basic understanding of AI concepts (helpful but not required)
Familiarity with Python is useful, but not mandatory
Comfortable using web apps and APIs (beginner level is enough)
Laptop with internet connection (Mac/Windows/Linux)
Ability to install tools like: Python and VS Code (or any IDE)
Willingness to learn hands-on by building real systems
No prior experience with agents or LLM frameworks required
Curiosity about AI, automation, and real-world applications
Description
"This course contains the use of artificial intelligence"
Master Agentic AI: From Foundations to Production-Ready Systems
This intensive 3-day course is designed to take you from understanding the basics of Agentic AI to building production-ready multi-agent systems that can operate in real-world business environments. You will go beyond simple prompting and learn how to design intelligent systems that can reason, act, use tools, and collaborate to complete complex tasks.
On Day 1, you will build a strong foundation in how AI agents actually work. You will learn the difference between chatbots, workflows, and agents, and understand core concepts like the ReAct loop (Think → Act → Observe). You will then dive into the anatomy of an AI agent, including system prompts, memory, tools, and output structures. By the end of the day, you will build your first working agent with tool integration and retrieval-based memory.
Day 2 focuses on scaling from single agents to multi-agent systems. You will explore powerful design patterns such as Planner-Executor, Researcher-Writer, and Critic-Improver, and understand why single agents fail in real-world scenarios. You will learn how to use modern orchestration frameworks like LangGraph, CrewAI, and AutoGen to design structured workflows. Through hands-on implementation, you will build a multi-agent system that collaborates across roles to solve end-to-end tasks.
On Day 3, you will transition from prototypes to production-ready AI systems. You will learn how to implement evaluation pipelines, including LLM-as-a-Judge, test cases, and regression testing. You will design guardrails and safety systems to prevent prompt injection, unsafe outputs, and tool misuse. You will also explore observability and monitoring, tracking inputs, outputs, latency, and failures. Finally, you will learn how to scale agent systems using cost optimization, parallelization, and caching, and design enterprise-grade architectures with API layers, orchestration layers, and governance.
Throughout the course, you will also dive into advanced topics like Agent + RAG (Retrieval-Augmented Generation) for knowledge grounding, Agent + automation (Zapier, n8n) for workflow execution, Agent + enterprise APIs for real-world integration, and Agent + UI (Streamlit) for building interactive applications.
The course culminates in a capstone project, where you will build a production-ready multi-agent system with tools, memory, evaluation, and guardrails-complete with a working demo and business use case.
By the end, you will not just understand Agentic AI-you will be able to design, build, and deploy scalable, reliable, and enterprise-ready AI systems that deliver real impact.
Who this course is for
Professionals looking to build real-world AI systems, not just use prompts
Software engineers who want to learn agentic AI and multi-agent architectures
Product managers aiming to design AI-powered products and workflows
Data scientists transitioning into LLM-based and agent-based systems
Entrepreneurs and builders creating AI startups or automation tools
Automation and no-code users wanting to upgrade to intelligent AI systems
Technical leaders exploring enterprise AI architecture and strategy
Anyone interested in moving from AI experimentation → production-ready systems

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