Agentic AI Training in Hyderabad

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Agentic AI Training in Hyderabad

Batch Details

Details Name Full Details
Trainers Name:
Vivek, Spoorthi
Trainers Experience:
10+ Years, 22+ Years
Next Batch Date:
15th of Every Month New Batch Starts
Training Modes:
Online and offline Training (Instructor-Led)
Course Duration:
3 months (offline & online)
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+91 90320 18369
Email Us at:
info@eazygurus.com
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Agentic AI Course Content

Module 1 : Introduction to Agentic AI
  • What is Agentic AI? 
  • Autonomous AI vs Traditional AI, Agent lifecycle and capabilities 
  • Types of autonomy in AI systems 
  • Real-world examples of agents (assistants, planners, scouts) 
  • Discuss maturity levels of AI autonomy 
  • Compare rule-based systems vs agents 
  • Interactive brainstorming: Where can agents be used in business? 
  • Live demo of a simple agent in action (e.g., task planner)
Module 2 : Foundations of AI Agents
  • Understanding what AI agents are 
  • Key features that make agents intelligent 
  • Different kinds of agent designs like reactive, deliberative, and hybrid 
  • How rational agents make decisions 
Module 3 : Multi-Agent Systems (MAS)
  • Understanding multi-agent systems 
  • How agents communicate and work together 
  • Solving problems across distributed systems 
  • Using game theory to understand how agents interact
Module 4 : Reinforcement Learning for Agentic AI
  • Basics of Reinforcement Learning (RL) 
  • Understanding Markov Decision Processes (MDPs) 
  • Learning policies and shaping rewards 
  • Deep RL methods like DQN, PPO, and A3C 
Module 5 : Large Language Models (LLMs) & Agentic AI
  • Role of LLMs and autonomous AI. 
  • AI agents like AutoGPT and BabyAGI use LLM technology. 
  • Designing prompts helps shape how agents act. 
  • Tuning and adjusting LLMs tailors them to specific agents. 
Module 6 : Tools & Frameworks for Building AI Agents
  • AI agent frameworks like LangChain, AutoGen, and CrewAI follow an open-source approach. 
  • Tools to manage workflows include LLM chaining and memory management techniques. 
  • Connecting AI agents to APIs and practical applications helps in real-world integration.
Module 7 : Agentic AI for Security & Cloud Automation
  • AI tools to secure systems 
  • Cloud automation using AI and DevSecOps practices 
  • Security agents and threat data powered by AI
Module 8 : Ethics & Risks of Agentic AI
  • Ethics in autonomous agents 
  • Bias fairness, and how we understand them 
  • Challenges in making AI safe and aligned 
  • Laws and rules to regulate AI agents
Module 9 : Hands-on Projects & Case Studies
  • Building a basic AI agent using OpenAI’s API 
  • Designing a simulation with multiple agents to solve a real-world problem 
  • Using AI agents in cloud systems and secure environments 
  • Exploring research and upcoming developments in agent-based AI
Module 10 : Tools & Frameworks for Building AI Agents
  • A look at well-known frameworks such as LangChain, Haystack, and Ray. 
  • Exploring libraries to plan tasks, store memory, and support reasoning. 
  • Connecting APIs and external tools with agent workflows. 
  • Practical activity: Create a basic agent with LangChain. 
  • Tips to design scalable and modular systems.
Module 11 : Ethical, Legal, and Safety Considerations
  • Understanding fairness, accountability, and transparency in AI. 
  • Regulatory landscape: AI Act, GDPR, and global guidelines. 
  • Bias detection and mitigation strategies. 
  • Building safe, value-aligned, and explainable agents. 
  • Case studies: Ethical dilemmas in autonomous AI systems.
Module 12 : Agentic AI in Enterprise Applications
  • Applications in finance, healthcare, manufacturing, and retail. 
  • Automates tasks in systems like CRM, ERP, and HR. 
  • Example: Automating customer support using agents. 
  • Building AI agents to improve business decisions. 
  • Team task: Build a prototype for an automated workflow agent.
Module 13 : Edge-to-Cloud Agentic AI
  • Using AI agents on edge devices to make decisions. 
  • Combining edge processing and cloud computing to enhance tasks. 
  • Lowering delays by processing AI on devices. 
  • Addressing security issues and privacy in decentralized agent setups. 
  • Presentation: A cloud-connected AI interacting with an IoT edge agent.
Module 14 : Multi-Step Planning & Problem Solving
  • Dividing big tasks into smaller achievable goals. 
  • Using planning methods such as STRIPS, A*, and Monte Carlo Tree Search. 
  • Adjusting plans when situations shift. 
  • Blending traditional planning techniques with learning-based approaches. 
  • Workshop: Create an agent to automate project management tasks. 
Module 15 : Capstone Project & Real-World Applications
  • Choose a project in a particular field like healthcare, finance, or logistics. 
  • Use what you know about multi-agents, autonomy, and reinforcement learning to work on it. 
  • Make sure to include measures to explain your project's steps and keep it ethical. 
  • Share your results and show how your prototype works. 
  • Prepare it for feedback, review, and get certified.

Agentic AI Training In Hyderabad

Key Points

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01
Agentic AI works on its own without needing frequent human input. It decides, acts, and handles tasks, following the objectives it is assigned.
06
Agentic AI does not wait to be told what to do. It spots needs ahead of time, looks for chances to improve things, and takes action to make results better or avoid problems.
02
These systems adapt to what they learn from experiences and results. They tweak their approach to perform better over time even when conditions shift or become difficult to predict.
07
These systems notice what is happening around them. They consider what the user likes, limits of the situation, and outside factors to make smarter choices.
03
Agentic AI focuses on achieving a clear goal. Instead of carrying out instructions, it chooses and organizes tasks that help it move closer to reaching its target.
08
Agentic AI works within ethical and legal limits to make sure its independence and decisions stay true to human values and follow social rules.
04
Agentic AI can plan and carry out sequences of tasks that are complicated. It breaks big challenges into smaller pieces, makes choices as it goes, and changes its plan if something needs fixing.
09
A key feature is its skill in explaining how it thinks, decides, and acts in ways people understand. This helps build trust and clarity.
05
Agentic AI works with people or other AI by sharing details, organizing efforts, and helping out in group workflows or team settings.
10
Agentic AI deals with tasks of all sizes, from simple daily activities to big and complicated systems. It keeps things efficient, coordinated, and effective.

About Agentic AI Training

in Hyderabad

Agentic AI Training in Hyderabad helps professionals, students, and tech enthusiasts learn skills to excel in advanced artificial intelligence. Traditional AI sticks to predefined tasks, but Agentic AI emphasizes independence, flexibility, and achieving goals. It lets systems take charge, solve complex tasks step by step, and work well with both people and other AI agents. This program teaches key ideas in Agentic AI such as being proactive, understanding context, following ethical guidelines, being transparent, and expanding capabilities.  

Since Hyderabad has become a top tech hub, participants also explore how Agentic AI works in fields like finance, healthcare real estate, and business automation. Participants gain skills to create and use AI systems that handle tough workflows and bring new ideas through projects, expert sessions, and case studies. If you want to grow in your job, work on advanced research, or use AI in daily business, Agentic AI Training in Hyderabad offers a great way to keep up with the fast-changing world of smart tech.

 

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What is Agentic AI?

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Agentic AI describes a newer type of artificial intelligence that does more than follow fixed commands or automated tasks. Traditional AI usually functions based on set instructions that never change, but Agentic AI has autonomy and works with specific goals in mind. It can decide on its own, modify its approach using real-time feedback, and handle complex problems without needing constant help from people. These systems understand context, take initiative, and can work alongside humans or other AI tools to reach common goals. 

Agentic AI aligns with ethics and safety, making sure people use it in real situations. It combines its ability to act with being understandable and able to handle growth marking a significant shift in how machines assist with challenging jobs, improve results, and spark changes in fields like healthcare and finance.

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Why is Agentic AI Used?

Carrying Out Tasks

Agentic AI completes complicated tasks step by step from beginning to end. It does this without needing human help all the time. Tasks like analyzing information, processing payments, or returning products fall under its capabilities.

Boosting Output

Agentic AI takes over dull and repetitive work. This gives human workers more opportunities to focus on creative ideas, important strategies, or activities that add greater value. It helps teams work more overall.

Making Better Decisions

By processing huge amounts of data agentic AI spots important trends and possible risks. It helps industries make quicker and smarter decisions while staying well-informed at the same time.

Tailored Interactions

These AI systems track how users behave and change interactions to give tailored support and outputs that match specific needs.

Solving Problems

Agentic AI, unlike older AI models, can handle uncertainty, adjust to new surroundings, and plan actions on the go to hit targets instead of just sticking to pre-set instructions.

Boosting New Ideas

By handling simpler tasks and delivering valuable insights agentic AI gives people more time to try new things speeding up discoveries and fresh ideas.

Course outline

  • Introduction to Agentic AI – Understanding autonomy, adaptability, and goal-driven intelligence.

  • Core Concepts of Autonomy – How AI systems operate independently.

  • Learning and Adaptability – Building models that adjust to dynamic environments.

  • Goal-Oriented Design – Structuring AI to prioritize objectives effectively.

  • Collaboration Models – Enabling AI to work with humans and other agents.

  • Proactivity and Context Awareness – Anticipating needs and acting with situational awareness.

  • Ethics and Safety in Agentic AI – Ensuring responsible and aligned decision-making.

  • Explainability and Transparency – Designing AI systems that justify their actions.

  • Practical Applications & Projects – Hands-on training with real-world industry use cases.

Generative AI Training Modes

Check mark - Free shapes and symbols icons Basic to advance level

Check mark - Free shapes and symbols icons Daily recorded videos

Check mark - Free shapes and symbols icons Live project included

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Check mark - Free shapes and symbols icons 100% Placement assistance

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Check mark - Free shapes and symbols icons Lifetime Video Access

Check mark - Free shapes and symbols icons Basic to advance level

Check mark - Free shapes and symbols icons Doubt Clearing Session

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Check mark - Free shapes and symbols icons Certification Guidance

Check mark - Free shapes and symbols icons Interview Guidance

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Check mark - Free shapes and symbols icons Basic to advance level

Check mark - Free shapes and symbols icons Flexible Batch Timings

Check mark - Free shapes and symbols icons Live project included

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Check mark - Free shapes and symbols icons 100% Placement assistance

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Generative AI Course Job support program

Resume Building & Profile Improvement

The program offers step-by-step help to create resumes that work for AI and tech jobs. Coaches focus on showing off Agentic AI skills, projects, and certifications in a way that grabs attention in competitive fields. They also guide participants to upgrade their LinkedIn and job portal profiles to improve visibility to recruiters. 

Preparing for Interviews & Mock Practice

Participants get plenty of practice in mock interviews testing technical knowledge, problem-solving, and real-life scenarios related to AI. Skilled mentors give tips and advice on handling tricky interview situations with confidence. This helps candidates feel confident well-prepared, and ready to land jobs. 

Help With Real-World Projects

The program provides support to work on projects or tasks tied to Agentic AI. Mentors help participants use ideas like autonomy, adaptability, and solving problems with clear goals while handling real challenges. This hands-on help reduces the gap between learning and doing well at work. 

Career Advice and Planning

Learners get one-on-one sessions to choose the best path in the AI field. Experts help them decide to aim for research roles, development jobs, or industry-focused work. With this guidance, participants feel more focused and ready to work toward future goals. 

Placement Help and Industry Connections

The program brings participants together with recruiters hiring managers, and top professionals in the AI field. It offers guidance with job opportunities, recommendations, and chances to connect with others. This close link to the industry improves the odds of getting roles that match skill sets. 

Ongoing Mentorship After Training

Learners can get career advice and help with workplace issues even after finishing the course. This steady mentorship helps to grow over time. By staying connected, participants can keep learning and moving forward in their AI careers. 

Market Trend in Agentic AI

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01
Autonomous Decision-Making and Hyperautomation – Agentic AI is moving beyond helping humans. It now takes decisions on its own and manages complex tasks in different industries.
02
Multi-Agent Collaboration – AI systems built for specific tasks, are now teaming up. This boosts how well teams and departments work together.
03
Edge-to-Cloud Intelligence – AI tools handle data on devices for quicker reactions and connect to the cloud later to share larger insights.
04
AI-as-a-Service (AIaaS) – Businesses can now use AI through no-code setups and pre-built tools, no matter their size.
05
Ethical Governance and Transparency – With AI taking on more control, there’s a push to create clear, fair, and trust-building rules to guide its use.
06
Smooth Integration – Enterprises place AI agents within systems like CRM, ERP, and RPA to simplify main workflows.

Student Testimonials Agentic AI Training

Before this course, I only had a basic understanding of AI. The mentors explained complex topics like reinforcement learning and multi-agent systems so clearly. I built my first AI workflow agent, and it gave me huge confidence to apply for AI roles.
Ananya Reddy
Student
The placement assistance was very helpful. The team guided me in preparing my resume and facing AI-specific interviews. I landed a role as an AI Engineer within two months of completing the training.
Rohit Sharma
AI Enthusiast
I loved the hands-on approach. Instead of just theory, we created working AI agents using LangChain and AutoGen. This practical exposure helped me during job interviews as I could talk about real projects.
Sneha Iyer
Data Scientist
The best part was the mentorship. Experienced professionals shared real-world use cases from healthcare and finance. It gave me clarity on how Agentic AI is being applied in industries today.
Arjun Menon
Content Creator
Coming from a non-coding background, I was nervous at first. But the trainers were very supportive. Now I can confidently design autonomous agents and even work with APIs to integrate them into business workflows.
Priya Nair
Entrepreneur
This training was a turning point for me. I not only learned advanced AI concepts but also got connected with recruiters. Today, I’m working on cloud automation projects powered by AI agents.
Karan Verma
AI Researcher
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Agentic AI Training In Hyderabad

Certification

  • Certification in Agentic AI validates expertise in autonomous agents and AI-driven automation.

  • Recognition of Mastery in multi-agent systems and reinforcement learning.

  • Industry-Relevant Skills applicable across cloud, cybersecurity, automation, and finance.

  • Career Advancement with certification boosting professional credibility.

  • Resume Enhancement that strengthens job applications in AI roles.

  • Opens Opportunities for positions like AI engineer, data scientist, and automation expert.

  • Global Recognition as a trusted credential in the evolving AI landscape.

  • Future-Ready Expertise to stay ahead in next-generation AI careers.

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Skills develop after the course

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01
Discover ways to build and launch AI systems that can think, plan, and complete tasks without constant human guidance.
02
Learn methods like Q-learning, Deep Q-Networks, and Proximal Policy Optimization to train AI in making smart choices in changing situations.
03
Explore how to develop and organize teams of AI agents that either work together or compete to tackle tough challenges.
04
Use AI to simplify work by automating tasks in fields such as cloud services, security, and business research.
05
Learn how to connect AI tools with cloud services like AWS, Azure, and GCP. Build AI-powered security systems to detect and stop threats as they happen.
06
Explore how to address ethical challenges in AI. Focus on reducing bias, making systems more transparent, and using autonomous tools.

Job opportunities after course

AI Engineer
Machine Learning Engineer
AI Automation Specialist
Data Scientist
Cloud AI Solutions Architect
AI Researcher

Placement program Agentic AI Training

In-Depth Learning

Courses include topics such as advanced agent systems, autonomous technology, reinforcement learning, and essential tools like LangChain and AutoGen.

Real-World Applications

Students tackle hands-on projects where they create intelligent agents and design multi-agent systems suited to various industries.

Guidance from Experts

Mentors experienced in the field and professionals from leading companies provide direct support to learners.

Career Support

Institutions assist with creating resumes, conducting practice interviews, and connecting students with potential employers.

Corporate Collaborations

Many programs work with industry networks to offer numerous opportunities for interviews and job placements.

Cutting-Edge Resources

Learners get access to the latest AI research papers, pre-trained models, and exclusive toolkits to stay ahead in the rapidly evolving agentic AI ecosystem.

Pre-requisites for Agentic AI Training

A solid grip on programming basics is essential. Knowing Python helps a lot in building AI models, automating tasks, and working with data. 

One must understand supervised, unsupervised, and reinforcement learning well. Applying these concepts in practical scenarios is crucial. 

It is important to know how data cleaning creates features for models, and how neural networks work. Working with TensorFlow or PyTorch is also valuable. 

Knowledge of linear algebra, probability, stats, and optimization plays a big role in creating and improving AI systems.

Learn how to use REST APIs and work with cloud services like AWS, Azure, or GCP to create scalable AI solutions. 

Use problem-solving skills to build effective AI workflows and handle tough situations with intelligent designs. 

Frequently Asked Questions - Agentic AI Training

1. Who can join the Agentic AI training program?

Anyone with basic knowledge of programming (preferably Python), machine learning, or data science concepts can join. Students, working professionals, and tech enthusiasts looking to grow in AI are welcome.

2. Do I need prior AI or ML experience to join?

Not mandatory. The program covers fundamentals before moving to advanced concepts. However, knowing Python and basic ML will help you learn faster.

 

3. What kind of projects will I work on?

Learners build real-world AI agents such as task planners, customer support bots, and multi-agent simulations for industries like healthcare, finance, and retail.

 

4. Is job placement guaranteed after the course?

The program provides 100% placement assistance through resume building, mock interviews, mentorship, and industry connections. While placement cannot be guaranteed, most learners secure relevant opportunities.

 

5. Will I receive a certificate after completing the course?

Yes. Upon successful completion of the program and capstone project, you will receive a globally recognized certification in Agentic AI, which adds strong value to your resume.

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