Agentic AI
Build in-demand Agentic AI skills by learning to design, develop, deploy, and scale intelligent AI agents.
Duration
Approx 12 weeks3 hrs per week
Understand the foundations of Large Language Models and AI agents
As organisations increasingly adopt AI agents to automate workflows, enhance decision-making, and solve complex business challenges, the demand for Agentic AI skills continues to grow.
Understanding how to build AI systems that can reason, use tools, retain knowledge, and collaborate with other agents is becoming a key capability for modern AI engineers and developers.
This ExpertTrack will take you from the foundations of Large Language Models (LLMs) through to building, deploying, and managing production-ready agentic systems.
You’ll develop practical prompt engineering skills, explore LLM reasoning limitations, and learn how to guide models using structured outputs, function calling, and context engineering. With this knowledge, you’ll be able to build simple AI systems in Python that apply core agent design patterns such as ReAct, Reflection, and Plan-and-Execute.
Build production-ready AI agents with tools, memory, and multi-agent systems
To develop your skills, you’ll focus on creating more advanced AI agents that can interact with the real world. You’ll learn how to integrate tools and build agent memory and Retrieval Augmented Generation (RAG) pipelines so systems can retain and use knowledge effectively.
Create collaborative AI systems with memory, RAG, and agent communication
You’ll bring everything together by building advanced multi-agent systems that can remember, retrieve knowledge, and collaborate effectively. You’ll also apply the Agent-to-Agent (A2A) communication protocol to enable coordination between agents, resulting in fully functional, production-ready AI systems.
Deploy, evaluate, and scale AI agents in production
As you progress on the ExpertTrack, you’ll learn how to take AI agents from prototype to production. You’ll build skills in evaluation, monitoring, and observability using LLM-as-a-Judge techniques, regression testing, and tracing tools.
You’ll also learn how to deploy agents using Docker while implementing guardrails, security controls, and human oversight to ensure safe and reliable operation at scale.
Enhance your AI engineering skills with Edureka
Throughout the ExpertTrack, you’ll be guided by the specialists at Edureka, a global leader in technology education with extensive experience delivering enterprise AI training.
With their expertise, you’ll develop the practical skills to prepare you for the next generation of AI engineering roles.
Key skills you will learn
- Agentic AI
- AI
- AI Engineering
Experience required
No prior AI engineering experience is required, though basic familiarity with concepts like APIs and LLMs will be helpful. It is ideal for professionals exploring career transitions into AI engineering, team leads evaluating agentic AI for business applications, and curious learners who want to move beyond chatbots and understand autonomous AI systems.
Learners need a computer (Windows, macOS, or Linux) with at least 8 GB RAM and a stable internet connection. Python 3.10 or later should be installed, along with a code editor such as VS Code. No paid software or specialised hardware is required.
Getting started
This course is designed for technology enthusiasts, software developers, data professionals, product managers, and business leaders who want to understand agentic AI.
ExpertTrack course overview
Course 1
Agentic AI: Prompt Engineering and LLM Essentials
Build a foundation in how AI agents work by understanding the LLMs and prompting that power them as you build agentic systems.
3 tests
3 weeks
3 hours per week
Week 1
Build Your Prompt Engineering Foundation
- Navigating Your Prompt Engineering Journey
- Start with Generative AI and LLMs
- Learn the Basics of Prompt Engineering
- Set Up and Write Agentic System Prompts
Week 2
Engineer Context and Structure Better Reasoning
- Move Beyond Prompt Engineering
- Manage Context in Agentic Systems
- Use Structured Reasoning Prompts
Week 3
Design and Build Agentic AI Workflows
- Move into Agentic AI and Frameworks
- Explore Agentic Design Patterns
- Plan, Review and Execute Agent Workflows
Course 2
Agentic AI: Tool Integration, MCP, and Agent Frameworks
Gain practical AI engineering skills by building production-ready agents, mastering MCP, and comparing leading agent frameworks.
3 tests
3 weeks
3 hours per week
Week 1
Build Tool-Ready Agent Workflows
- Kickstart Your Tool Integration Journey
- Tools, Outputs, and Function Calling
- Custom Tools and Standard Connectors
Week 2
Connect Agents with MCP and Frameworks
- MCP Discovery and Tool Invocation
- From Scratch Workflows to LangGraph
- Compare Agent Framework Styles
Week 3
Secure and Strengthen Agent Tool Interactions
- Secure Agent Tool Access
- Resilient and Production-Ready Tool Workflows
Course 3
Agentic AI: Memory, RAG, and Multi-Agent Orchestration
Learn how to build more capable AI systems by giving agents memory, access to domain knowledge, and the ability to collaborate.
3 tests
3 weeks
3 hours per week
Week 1
Build Memory-Aware Agent Systems
- Start with Agent Memory Foundations
- Explore Agent Memory and Retrieval Routing
- Manage Context with Structured Memory
Week 2
Agentic RAG and Agent-to-Agent Communication
- Move from RAG to Agentic Retrieval
- Coordinate Specialist Agents
- Enable Agent-to-Agent Communication
Week 3
Add Human Oversight and Shared Multi-Agent Memory
- Design Safer Workflows with Human Oversight
- Resolve Agent Conflicts with Shared Memory
- Prepare Reliable Memory and Coordination Workflows
Course 4
Agentic AI: Evaluating, Deploying, and Scaling
Gain hands-on skills in taking AI agents from prototype to production, learning how to test, deploy, monitor, and improve systems.
3 tests
3 weeks
3 hours per week
Week 1
Assess Agent Quality, Safety and Reliability
- Step Into Agent Evaluation and Deployment
- Evaluate Agent Behaviour and Output Quality
- Test Agents for Behaviour Changes
Week 2
Deploy and Monitor Agentic AI Applications
- Move from Prototype to Production
- Containerise and Validate Agent Applications
- Monitor Agent Behaviour with LangSmith
Week 3
Scale Agents with Safety and Cost Controls
- Add Guardrails for Safer Agent Workflows
- Optimise Agents for Cost and Scale
- Prepare Production-Ready Agentic AI Systems
Prove you're job ready
Highlight the new, job-relevant skills you’ve gained and supplement existing qualifications with a hard-earned, industry-specific digital certificate – plus one for every course within your ExpertTrack.
- Learn the latest in your chosen industry or subject.
- Complete each course and pass assessments.
- Receive certificates validated by the educating organisation.
- Impress employers with learning outcomes you can add to your CV.
- Make your career dreams a reality.
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How ExpertTracks work
Join an ExpertTrack to master new skills in your chosen specialist area. Work through a series of topic-focused courses at your own pace, and pass the final assessment to earn a digital certificate award which proves your expertise.
Decide if the ExpertTrack is right for you with free access to the full suite of courses and assessments for a week.
Pay a monthly subscription fee of $39 for as long as it takes you to complete the ExpertTrack. You can learn at your own pace and cancel at any time.
Receive a certificate for every completed course and pass the final assessment to earn a digital certificate.
Use your specialist training to progress further in your career or build expertise in areas you’re passionate about.
World-class learning with Edureka
Edureka is a global online learning platform offering industry-focused training in emerging technologies such as Cloud, AI, GenAI, Data Science, DevOps, and Cybersecurity, helping professionals upskill and advance their careers.
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ExpertTracks are a series of online courses designed to help you master new skills in specialist areas. You pay a monthly subscription fee which includes access to all courses within the ExpertTrack, as well as assessments and the final digital certificate.
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