Build a future-ready career at the frontier of technology with SkillShikshya's Generative AI and Agentic Systems Advanced Diploma Course in Nepal. Learn how the world's leading tech companies, AI startups, and enterprises are building intelligent systems using large language models, autonomous AI agents, RAG pipelines, multi-agent frameworks, and the AI automation stacks reshaping every industry in 2026. Whether you want to become an AI engineer, build your own LLM-powered products, automate business workflows with AI, or consult for companies in Nepal and internationally, this 2.5-month diploma gives you the technical depth, real-world projects, and career support to lead in the most in-demand field of the decade.

Hybrid Classes
Attend class physically or online from anywhere and learn practical, real-world skills with guidance from industry professionals.
Industry Practices
Learn essential strategies used by agencies, brands, and global marketing teams.
Flexible Schedule
Morning and evening batches designed for students and working professionals.
Beginner Friendly
No prior experience required to start learning and building your skills.
SkillShikshya's Generative AI & AI Agents Course is one of the most comprehensive and forward-thinking artificial intelligence training programs in Kathmandu — designed for students, working professionals, entrepreneurs, and tech enthusiasts who want to build a serious career in generative AI, large language models (LLMs), and autonomous AI agent development. Whether you're a complete beginner searching for a generative AI course for beginners in Nepal or a professional looking to upgrade to advanced agentic AI and automation skills, this course takes you from AI fundamentals to a job-ready AI specialist portfolio.
Generative AI is the fastest-growing technology sector in the world, and the demand for AI engineers, prompt engineers, and agentic AI developers is exploding both in Nepal and globally. Companies across every industry are urgently building teams to develop, deploy, and manage AI-powered applications, automation workflows, and autonomous agent systems. This is your moment to get ahead.
You'll master the complete generative AI and agentic AI workflow prompt engineering, working with large language models, building AI agents with LangChain and AutoGen, Retrieval-Augmented Generation (RAG), AI automation workflows with n8n and Make, vector databases, LLM fine-tuning, and deploying AI-powered applications using tools and frameworks that top tech companies, AI startups, and enterprises are actively hiring for.
Students and Graduates
Start your career with practical training and build job-ready, indusrty-relevant skills.
Entrepreneurs and Business Owners
Apply modern strategies to grow your business and reach more customers.
Aspiring Professionals
Build a strong foundation and transition into a professional career path.

Freelancers and Side Hustlers
Work independently, offer services globally, and build income-generating skills.
Generative AI Fundamentals
Understand generative AI, LLMs, and how businesses use AI to transform products and workflows.
Prompt Engineering for AI Models
Learn to craft effective prompts and instructions for accurate AI-generated outputs.
Building AI Agents with LangChain
Build AI agents that can reason, use tools, and perform multi-step tasks autonomously.
Retrieval-Augmented Generation (RAG)
Connect AI models with custom data to generate accurate, context-aware responses.
Agentic AI & Multi-Agent Systems
Develop multi-agent systems where AI agents collaborate to solve complex problems.
Large Language Models (LLMs) & APIs
Work with OpenAI, Claude, Gemini, and open-source LLM APIs to build AI apps.
AI Workflow Automation & Integration
Automate business processes using AI tools like Zapier, Make, and n8n.
Vector Databases & AI Memory Systems
Use vector databases to enable semantic search and long-term AI memory.
AI-Powered Application Development
Build and deploy real-world AI applications using generative AI technologies.
Fine-Tuning & Customizing AI Models
Customize AI models for specific industries and domain-focused use cases.
AI Ethics, Safety & Responsible AI
Understand AI ethics, bias, privacy, and safe AI development practices.
Generative AI Portfolio & Freelancing
Create a strong AI portfolio and start freelancing or consulting in AI.
Platforms & Tools You'll Master
You will learn industry-standard tools used by agencies and companies.



An AI engineer in 2024 spent most of their time on plumbing: writing boilerplate LangChain code, debugging API call failures, manually chunking documents for RAG, and configuring vector database schemas from scratch. In 2026, that workflow has fundamentally changed. Modern AI development stacks, LangGraph with checkpointing, n8n with MCP integration, CrewAI with role-based crews have abstracted the plumbing so engineers can focus on what actually matters: designing agent architectures, evaluating model outputs, writing the business logic that makes an AI system genuinely useful rather than just technically functional. This course teaches you both layers: the technical foundation and the engineering judgment that AI tools cannot replace.
| Task in the AI Engineering Workflow | Tool Used | What Was Done Before (2024) | What You Do Now (2026) |
|---|---|---|---|
| Building LLM-powered applications | LangChain + OpenAI / Claude API | Write raw API calls from scratch, manage prompt templates manually, handle conversation history by hand, debug token overflow errors individually | LangChain abstracts the boilerplate — chains, memory, and tool routing handled in minutes. You focus on what the application does, not how to wire the API. What took a day now takes an afternoon. |
| Building stateful AI agents | LangGraph | Agents had no reliable state — they forgot context between steps, could not branch conditionally, and had no rollback on failure. Production agent systems required bespoke engineering for every workflow | LangGraph models agents as explicit state machines — graphs with nodes, edges, and checkpoints. Define the workflow explicitly. The agent retains state, branches conditionally, retries on failure, and supports human-in-the-loop approval before critical actions. |
| Multi-agent systems where agents collaborate | CrewAI | Building multi-agent systems from scratch meant writing custom orchestration, message passing, and failure recovery logic — weeks of work | CrewAI: assign each agent a role (researcher, writer, reviewer), give them tools and a goal. The crew coordinates, delegates, and produces outputs. Working multi-agent demos in an afternoon. Used by 1,500+ companies executing 10M+ agents per month. |
| Connecting agents to external tools & data | MCP (Model Context Protocol) | Every new tool integration required a custom connector — weeks of engineering per tool, and different LLMs needed different connector formats | MCP is the universal standard: build one MCP server per tool and every MCP-compatible agent (Claude, GPT, Gemini, n8n) can use it. Over 500 public MCP servers now exist — GitHub, Slack, Stripe, PostgreSQL, Figma, Docker. Your agent can use any of them. |
| Building RAG pipelines (AI + your own documents) | LangChain + ChromaDB / Pinecone | Manually write document loaders, chunking logic, embedding calls, and vector search from scratch — error-prone, slow, and different for every data source | LangChain RAG pipeline: load documents, chunk, embed, store in ChromaDB or Pinecone, retrieve at query time — in a structured workflow you build once and reuse. What previously required senior ML engineering knowledge is now a module-level skill. |
| Running LLMs locally without API costs | Ollama + Llama 3 / Mistral / DeepSeek R1 | Local LLM deployment required deep ML infrastructure knowledge — CUDA setup, model quantisation, serving layer engineering | Ollama: one command to pull and run Llama 3, Mistral, or DeepSeek R1 locally. No API costs, no data leaving your machine, no internet required. Switch between local and cloud models based on task and cost requirements. |
| AI workflow automation for business processes | n8n + MCP | Connecting AI reasoning to business systems (CRMs, email, databases) required custom code for every integration. n8n workflows and AI agents were separate, incompatible systems | n8n now supports MCP — your AI agent can discover and call n8n workflows as tools. An agent that researches a company can trigger an n8n workflow to send a personalised email, log the result in a CRM, and notify a Slack channel — all decided by the agent, not hardcoded by you. |
| Monitoring and debugging production AI systems | LangSmith / Langfuse | Production AI failures were invisible — you knew something was wrong when users complained. There was no equivalent to server logs for LLM applications | LangSmith and Langfuse give you full observability: trace every agent step, see every prompt and response, detect latency spikes and prompt drift, evaluate model outputs programmatically. The most common reason agent projects fail after demo is skipping this layer. |
SkillShikshya's Generative AI & Agentic AI Course in Nepal is structured to take you from zero AI knowledge to a confident, job-ready generative AI specialist and AI agent developer. Every module includes practical AI building labs, real-world automation projects, and hands-on LLM experiments designed to build a strong, employer-ready AI specialist portfolio.
The curriculum covers the complete generative AI and agentic AI engineering workflow: prompt engineering, LangChain agent development, RAG systems, multi-agent architectures, LLM API integration, vector databases, AI automation with n8n and Make, fine-tuning, AI application deployment, AI ethics, and portfolio development, the full stack of skills that AI companies and tech employers are urgently hiring for globally.
After completing the program, you will receive a certification from At Skill shikshya, the best online learning institute in Nepal. This certification helps demonstrate your professional skills when applying for jobs or freelance opportunities.

Thinking of enrolling? Here's what makes our courses different.
Beginner Friendly
Start from the basics and gradually progress to advanced concepts.
Expert Led Training
Learn from professionals with real-world industry experience.
Hands-On Projects
Work on practical projects and build a strong, portfolio-ready skillset.
Lifetime Learning Resources
Access learning materials, updates, and resources even after completing the program.
Career Support
Get guidance for job applications, internships, and career growth opportunities.
Industry Certification
Earn a recognized certification that validates your skills and knowledge.
Batch Repeating Options
Repeat sessions if needed to strengthen your understanding.
Free Workshops
Access additional workshops covering tools, trends, and evolving practices.
HR & CV Sessions
Resume building, interview preparation, and career counseling support.

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