Leafclutch Technologies

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Agentic AI Training in Nepal

Design, build and deploy autonomous AI agents that plan, use tools and get work done.

  • 3 Months
  • Mode: Online & Hybrid Live Classes
  • Intermediate
  • 4.5 (2)

Learn directly from Rohan Aryal

Fee from

Rs. 6,400Rs. 8,000

20% OFF

Start with

Rs. 3,200

Updated on 25 Sept 2026 Created on 24 Sept 2026

Course overview

Agentic AI is the next step after chatbots: software that can reason about a goal, call tools and APIs, remember context and finish multi-step tasks on its own. This program takes you from Python and LLM fundamentals to production-grade agents built with LangGraph, CrewAI and the Model Context Protocol (MCP).

You will build retrieval-augmented assistants, tool-using agents, multi-agent teams and workflow automations, then learn how to evaluate, secure and deploy them. Every module ends with a working project, so you graduate with a portfolio that shows employers you can ship real AI systems.

Tools covered

Some of the major industry-relevant tools you will work with in this course:

  • Python
  • LangChain
  • LangGraph
  • CrewAI
  • OpenAI API
  • Claude API
  • MCP
  • ChromaDB
  • pgvector
  • FastAPI
  • n8n
  • Docker

Curriculum

The complete syllabus for Agentic AI: every lesson, section and topic you will cover. Download it as a PDF to read offline or share it.

8 lessons · 24 sections · 102 topics

Download PDF
    • Variables, data types and operators
    • Lists, dictionaries, sets and comprehensions
    • Functions, modules and packages
    • Classes, objects and dataclasses
    • Type hints and writing readable code
    • Installing Python and VS Code
    • Virtual environments with venv and uv
    • Managing dependencies and requirements files
    • Git and GitHub: commits, branches and pull requests
    • Storing secrets safely with environment variables
    • HTTP basics: requests, responses and status codes
    • Calling REST APIs with httpx and requests
    • async and await for concurrent API calls
    • Parsing and validating JSON with Pydantic
    • Handling timeouts, retries and rate limits
    • Tokens, context windows and sampling parameters
    • Pre-training, instruction tuning and RLHF in plain language
    • Strengths, limitations and hallucinations
    • Choosing models by quality, speed and cost
    • OpenAI, Anthropic Claude and Google Gemini SDKs
    • System, user and assistant messages
    • Streaming responses to the user interface
    • Tracking token usage and cost
    • Running open-source models locally with Ollama
    • Clear instructions, roles and constraints
    • Few-shot examples and output formats
    • Structured output with JSON schemas
    • Chain-of-thought and self-checking prompts
    • Prompt versioning and testing
    • What a tool is and when an agent needs one
    • Writing tool names, descriptions and input schemas
    • Returning useful results and errors to the model
    • Keeping tools small, safe and testable
    • The tool-calling loop step by step
    • Parallel and sequential tool calls
    • Stopping conditions and maximum steps
    • Handling tool failures and retries
    • Project: calculator, web search and database agent
    • Why MCP: one standard for tools and data
    • Building an MCP server in Python
    • Connecting MCP servers to clients and IDEs
    • Resources, prompts and tools in MCP
    • Securing MCP servers
    • What embeddings are and how similarity works
    • Creating embeddings with API and open-source models
    • Vector databases: ChromaDB and pgvector
    • Metadata filters and hybrid search
    • Loading PDFs, web pages and documents
    • Chunking strategies and chunk size trade-offs
    • Building a question-answering pipeline
    • Citations and grounding answers in sources
    • Re-ranking and query rewriting
    • Short-term conversation memory
    • Long-term memory stores
    • Summarising long conversations
    • Measuring retrieval quality with test sets
    • LangChain building blocks: models, prompts and tools
    • LangGraph nodes, edges and state
    • Conditional routing and loops
    • Checkpoints and resuming long-running agents
    • ReAct: reasoning and acting
    • Plan-and-execute agents
    • Reflection and self-correction
    • Router and supervisor patterns
    • Approval steps before risky actions
    • Editing agent state mid-run
    • Designing safe fallbacks
    • Project: customer support agent with approvals
    • When to split work across agents
    • Orchestrator and worker architecture
    • CrewAI roles, tasks and crews
    • Agent-to-agent communication and hand-offs
    • Automation with n8n: triggers, nodes and webhooks
    • Connecting Gmail, Sheets, Slack and databases
    • Scheduling and monitoring workflows
    • Combining deterministic workflows with agents
    • Browser automation with Playwright
    • Computer-use agents: capabilities and risks
    • Extracting data from websites responsibly
    • Project: autonomous research assistant
    • Tracing agent runs with LangSmith or Langfuse
    • Building evaluation datasets
    • LLM-as-judge and human review
    • Regression testing prompts and agents
    • Prompt injection and data exfiltration risks
    • Input and output validation
    • Permission scopes for tools
    • Handling personal and sensitive data
    • Serving agents with FastAPI
    • Background jobs and streaming responses
    • Containerising with Docker
    • Deploying to a cloud server
    • Monitoring cost, latency and failures
    • Choosing a real business problem
    • Writing requirements and success criteria
    • Architecture design review with your mentor
    • Implementing tools, memory and the agent loop
    • Adding evaluations and guardrails
    • Deploying the agent with a simple UI
    • Documentation and demo video
    • Demo day presentation
    • Internship readiness evaluation

What you get

  • Live instructor-led classes
  • Recorded video of every session
  • Hands-on projects and assignments
  • 1:1 mentor support and doubt sessions
  • Internship pathway after evaluation
  • Verifiable completion certificate
  • Learner community on Discord
  • Career guidance and portfolio review
Bonus with your enrollment

Free Udemy courses with lifetime access

Enroll in Agentic AI and choose one of these Udemy courses at no extra cost. It stays yours for life, so you can keep learning long after the program ends.

Free · lifetime

Complete web development course

Only web development course that you will need. Covers HTML, CSS, Tailwind, Node, React, MongoDB, Prisma, Deployment etc

Hitesh Choudhary

  • 4.5
  • 22,644 ratings
  • 100 total hours
  • 331 lectures
  • All Levels

Free with your enrollment

Explore

Udemy is a separate platform. Course access is arranged by Leafclutch Academy after your enrollment is confirmed.

Fees & payment plan

3 Months program. Choose the class type that suits you. The curriculum, mentors, recordings and certificate are the same in every mode.

20% OFF

Online

Live, interactive classes over video, from anywhere in Nepal or abroad.

Rs. 6,400

Rs. 8,000Enroll online

Hybrid

Mix both: join the lab when you can and log in live when you cannot.

Rs. 12,000

Enroll hybrid
Payment planOnlineHybrid

First installment (50%)

Payable at enrollment

Rs. 3,200Rs. 6,000

Second installment (50%)

Payable when you are promoted to the internship

Rs. 3,200Rs. 6,000
TotalRs. 6,400Rs. 12,000

Upcoming batches

StartsModeScheduleStatus
8 Oct 2026HybridSun – Thu, 7:00 – 8:30 AMSeats openEnroll

Your mentor

Rohan Aryal

Rohan Aryal

Mentor

Rohan mentors Leafclutch Academy's AI and data programs, guiding learners from their first lines of Python to building agents, generative AI applications, machine learning models and analytics dashboards, with a strong focus on hands-on projects.

Agentic AIGenerative AIData ScienceData AnalyticsAI/ML

Who can join

  • Basic programming knowledge in any language
  • Comfort using a computer and the internet
  • A laptop with at least 8 GB RAM

Career opportunities

  • AI Agent Developer
  • AI Engineer
  • LLM Application Developer
  • Automation Engineer

What learners say about Agentic AI

Sample Learner
The mentors explained every concept with real business data. Within weeks I was building Power BI dashboards for my own office reports.

Sample Learner

Data Analytics learner · Agentic AI

Earn a high-value industry certificate

Complete Agentic AI and receive a certificate from Leafclutch Academy. Add it to your LinkedIn profile, resume or CV to stand out to recruiters. Every certificate carries a unique code that employers can check online.

Already earned a certificate? Verify it here

Sample Leafclutch Academy certificate

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Frequently asked questions

Is Agentic AI different from Generative AI?

Generative AI focuses on creating content such as text and images. Agentic AI builds on it: agents use LLMs to plan, call tools and complete multi-step tasks. If you are new to LLMs, either course works as a starting point.

Do I need to pay for AI APIs?

No. We use free tiers, open-source models through Ollama and shared practice credits wherever possible, so you can complete every project without extra cost.

What will I build?

A RAG assistant, a tool-using agent, an MCP server, a multi-agent research team, an automation workflow and a deployed capstone agent.

Start Agentic AI this month

Talk to our counsellors for free. We will help you choose the right course, mode and batch.