Agentic AI Course in Hyderabad – Practical AI Training 
                     A G E N T I C  A I  T R A I N I N G
Generative AI vs. Agentic AI:
Which Skill Will Dominate the Future?
Understand the shift from AI that creates content to AI that can plan, decide, and act.
GENERATIVE AI AGENTIC AI
Creates Plans + Acts
→
Text · Images · Code · Audio Goals · Reasoning · Tools · Memory
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Why Should Learners Understand
Generative AI and Agentic AI?
Agentic AI Training helps learners understand a new stage of artificial intelligence where AI systems can work toward goals and complete multi-step 
tasks. Generative AI focuses mainly on creating text, images, code, and other content from prompts. Agentic AI goes further by adding planning, 
reasoning, tool use, memory, and actions. Both technologies are important and often work together. This presentation compares how they work, 
where they are used, the tools behind them, and the practical skills learners can build for modern AI projects.
T H E  E V O L U T I O N  P AT H
Prompt → Generate → Reason → Plan → Use Tools → Act
The takeaway:  generative AI stops at content creation; agentic AI carries that content into a plan of action.
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C O R E  D I S T I N C T I O N
What Is the Difference Between
Generative AI and Agentic AI?
Direct Answer:  Generative AI creates new content from user instructions. Agentic AI uses AI models with goals, reasoning, memory, tools, and workflows to 
decide what steps to take and complete more complex tasks.
GENERATIVE AI AGENTIC AI
• Produces text, code, images, audio, or summaries. • Plans and performs a sequence of actions.
• LLMs provide the reasoning and language layer. • AI agents connect models with tools, APIs, data, and memory.
Prompt → Model → Content Goal → Plan → Tools → Actions → Result
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S I G N I F I C A N C E
Why Does the Shift Toward Agentic AI Matter?
Generate → Reason → Plan → Act → Evaluate
1 From answers to actions:  AI can move beyond generating responses and participate in workflows.
2 Multi-step tasks:  Agents can break a larger goal into smaller steps.
3 Tool integration:  AI systems can interact with APIs, databases, search systems, and software tools.
4 Context and memory:  Agents can use stored information to support later steps.
5 Human oversight:  Reliable systems still need permissions, checks, evaluation, and clear limits.
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Which Core Concepts Should Learners Understand?
Large Language Models: Understand and generate language, code, and 
structured responses.
LLM
Reasoning and Planning: Agents determine which steps can help achieve a 
defined goal.
Memory: Stores useful context that may support later decisions or tasks.
Planning Memory
AI Tool Use: Allows an agent to work with APIs, databases, search, and applications.
Agent
RAG: Retrieval-Augmented Generation gives an AI system relevant external 
knowledge.
Tools RAG
An Agentic AI Course Online connects these concepts through practical workflows.
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Which Tools and Technologies Power Agentic AI?
Python → LLM → RAG → Agent Framework → Tools / APIs
1 Python:  Used to build AI applications, integrations, logic, and automation.
2 LLMs:  Provide language understanding, generation, and reasoning capabilities.
3 LangChain:  Helps developers connect models, data, tools, and application workflows.
4 LangGraph:  Supports stateful and multi-step agent workflows.
5 Vector Databases:  Store embeddings so AI applications can retrieve relevant information for RAG.
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How Does an Agentic AI Workflow Work?
1 2 3
Receive a Goal → Understand Context → Create a Plan
The system reviews instructions and available 
The user gives the AI system a task or objective. The agent identifies useful steps toward the goal.
information.
↓
4 5 6
Select Tools → Perform and Evaluate → Return the Result
It chooses approved tools, APIs, retrieval systems, or The system executes steps and checks intermediate The agent provides an answer or completed 
data sources. results. workflow for review.
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Where Can Generative and Agentic AI Be Used?
1 2 3
Knowledge Assistants Customer Support Software Development
Retrieve information and create clear answers from Summarize requests, find relevant information, and Explain code, generate drafts, test components, and 
approved sources. support defined workflows. support development.
4 5
Business Operations Data Workflows
Assist with document processing, research, reporting, Retrieve data, analyze information, and prepare 
and workflows. outputs for human review.
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S K I L L  B U I L D I N G
Which Agentic AI Skills Should Beginners Build?
1 2 3 4 5 6
Python Fundamentals Prompt Design LLM Fundamentals RAG Development Agent Workflows Evaluation & Safety
Python  →  Reliable Agentic Applications
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What Is a Beginner-Friendly Agentic AI Learning Roadmap?
Fundamentals Practical Skills Advanced Concepts
Learn Python, AI basics, prompts, Practice RAG, tool calling, memory, Study multi-agent systems, 
and LLM concepts. and structured outputs. orchestration, and safety.
1 2 3 4 5 6
Real-World 
Core Tools Projects
Applications
Explore LLM APIs, LangChain, Build assistants, knowledge Combine agents, data, APIs, and 
LangGraph, and vector databases. systems, and simple AI agents. human review to solve tasks.
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Generative AI or Agentic AI: Which Skill Matters More?
AI Basics → GenAI → RAG → Agents → Agentic Systems
Generative AI remains a core foundation for creating and understanding AI-generated content.
Agentic AI extends those capabilities through planning, tools, memory, and multi-step workflows.
The two technologies are complementary rather than simple replacements for one another.
Learners benefit from understanding LLMs and generative AI before building advanced agents.
A strong learning path moves from AI fundamentals to reliable, real-world agentic systems.
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Learn Agentic AI with Visualpath
Visualpath provides Agentic AI Training designed to help learners understand modern AI concepts through structured online learning.
✓ Practical online training ✓ ✓ Learning paths for beginners and professionals
✓ Instructor-led learning ✓ Online access for global learners
✓ Real-world exercises and AI workflows ✓ Corporate training for teams
Explore Python, LLMs, RAG, AI agents, tools, and modern agentic workflows through practical learning.
Start building practical Agentic AI skills with
Start building practical Agentic AI skills with Visualpath.
Visualpath.
Enroll Today
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