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AI agentic building Certification Training

One of the top providers of online IT training worldwide is VISWA Online Trainings. To assist beginners and working professionals in achieving their career objectives and taking advantage of our best services, We provide a wide range of courses and online training.

Reviews 4.9 (4.6k+)
Rated 4.7 out of 5

Learners : 1080

Duration :  25 Days

About Course

🌐 What Is AI Agentic Building?

AI Agentic Building (Generative AI)  focuses on developing intelligent, autonomous AI systems capable of reasoning, decision-making, and performing complex tasks with minimal human input. This training equips learners with the technical and conceptual understanding needed to design, build, and deploy AI agentic building that can plan, learn, and adapt — using cutting-edge AI models and frameworks.

Its core capabilities include:

  • Autonomous Decision-Making: Build agents that analyze environments and take context-aware actions.
  • Generative AI Integration: Leverage Large Language Models (LLMs) like GPT, Claude, or Gemini to generate content, automate workflows, and enhance interactions.
  • Tool & API Orchestration: Connect AI agents with tools, APIs, and external systems for dynamic task execution.
  • Workflow Automation: Create AI-driven workflows using frameworks like LangChain, LlamaIndex, or CrewAI.
  • Cognitive Reasoning: Implement logic chains for multi-step problem solving, planning, and reasoning.

📊 Course Features Typically Included

Most comprehensive online training platforms (such as Viswa Online Trainings, Udemy, Coursera, and DeepLearning.AI) include the following components:

  • Live expert-led sessions & recorded lectures
  • Hands-on labs building AI agents using Python, LangChain, and OpenAI APIs
  • Practical projects like chatbots, data assistants, and workflow agents
  • Access to model APIs (OpenAI, Anthropic, Google Vertex AI) for real implementation
  • Certification of Completion after project evaluation
  • Lifetime access to all sessions and materials

🎓 Key Learning Outcomes

After completing an AI Agentic Building (Generative AI) course, learners will be able to:

  • Understand the architecture and logic behind agent-based AI systems.
  • Design and implement AI agentic building that can plan, reason, and execute complex tasks.
  • Integrate LLMs with external data sources and APIs.
  • Use frameworks like LangChain, CrewAI, and LlamaIndex to build agent workflows.
  • Develop AI-driven automation and conversational systems.
  • Deploy and monitor AI agentic building in real-world business environments.

These skills are highly in demand for roles such as:

  • AI Engineer / AI agentic building Developer
  • Generative AI Consultant
  • Machine Learning Engineer
  • Automation / Workflow Architect
  • AI Product Developer or Research Engineer

📍 Bonus: Certification Tracks

Many learners also pursue certifications to validate their expertise, such as:

  • Certified Generative AI Developer (from Coursera / DeepLearning.AI)
  • LangChain Certified Developer Program
  • OpenAI API Advanced Developer Certification
  • Viswa Online Trainings – AI Agentic Building Developer Certification
  • Microsoft Certified: Azure AI Engineer Associate

AI agentic building Training Course Syllabus

Foundation of LLMs & LangChain
  • Introduction to Large Language Models (LLMs)
  • Architecture, capabilities, and use cases.
  • LangChain Overview
  • What is LangChain, and why it’s important for agentic workflows.
  • LangChain Chat and Embedding Models
  • Setup and API usage.
  • Understanding and implementing vector embeddings.
  • Lang Chain Prompts
  • Using Prompt Templates.
  • Implementing few-shot prompting.
  • Hugging Face + Lang Chain Integration
  • Using Hugging Face models via API within Lang Chain.
  • Memory in Lang Chain
  • Types of memory: Buffer Memory, Summary Memory.
  • Conversation memory and its use cases.
ore Lang Chain Constructs
  • Lang Chain Chains – LLM Chain, Sequential Chain
  • Creating simple pipelines using LLM Chain and Sequential Chain.
  • Lang Chain Structured Output
  • Using Pedantic Output Parser and schema definitions for structured outputs.
  • Lang Chain Output Parser
  • Parsing and validating LLM responses effectively.
  • Lang Chain Runnable
  • Introduction to Lang Chain Expression Language (LCEL).
  • Creating Custom Chains and Combining Runnable
  • Designing custom workflows and chaining multiple components.
  • Hands-on Lab
  • Build a modular chain with memory and structured outputs.
Agent-Based Workflows
  • Tools in Lang Chain
  • Tool abstraction and design.
  • Tool Calling in Lang Chain
  • Using tools with function-calling models.
  • Agent Overview + Weather API / Hardcoded Tool Demo
  • Introduction to agents with simple tool examples.
  • Lang Chain Agents – React Agent
  • Understanding reasoning and action flow with React architecture.
End-to-End Applications
  • Building RAG + Agentic Workflow using Lang Flow
  • Combining Retrieval-Augmented Generation with agents using Lang Flow interface.
  • Open AI Swarm
  • Exploring multi-agent orchestration patterns.
  • Overview and Implementation of Guardrails for AI Systems
  • Techniques and tools to ensure safe and predictable AI behavior.
  • ATS Application using Google Gemini Pro (Resume Screening)
  • Building an AI-powered applicant tracking system using Gemini Pro.
Domain & Cloud Deployments
  • Medical Chatbot using Lang Chain and External APIs
  • Building a healthcare-focused assistant using Lang Chain with real-time API integration.
  • Multi-query PDF QA Application with Google Gemini Pro
  • Handling complex queries over documents using Gemini Pro and Lang Chain.
  • Deploying GenAI Apps on Streamlit + Cloud
  • Step-by-step deployment on AWS or GCP for real-world usage.
  • Capstone Demo & Review Session
  • End-to-end walkthrough of a complete agentic application with feedback.
AI agentic building Course Key Features

Course completion certificate

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AI agentic building Online Training FAQ'S

What is AI Agentic Building?

AI Agentic Building is the process of creating autonomous agents that can analyze information, make decisions, and act independently using AI and LLMs.

 

What are the main components of an AI agentic building system.?

Key components of AI agentic building  include perception, reasoning, memory, action, and communication modules, enabling intelligent task execution.

 

What technologies are used for building AI agents?

Popular tools include LangChain, AutoGen, CrewAI, OpenAI APIs, and vector databases like Pinecone or Chroma for memory and context handling.

 

What are the key benefits of agentic AI systems?
  • They enable automation of complex workflows, adaptive decision-making, continuous learning, and scalable enterprise intelligence.
What are best practices for building agentic AI systems?

Use structured prompts, maintain contextual memory, integrate reliable APIs, ensure safety and ethical use, and test agent behavior in real-world environments.

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