AI Workshop for career professionals
Master Gen AI & Build AI Agents in 4 Days
Learn cutting-edge Al skills through immersive weekend sessions designed for ambitious professionals aiming for high-paying jobs.
(Offer valid till Nov 14th)
Mentored by
Mr. Ashutosh
Senior Corporate Trainer – Makonis Software Solutions Pvt Ltd
AI/ML Consultant, Ex-Samsung, Philips
Who Should Attend
Perfect For
Software Developers & Engineers
Build autonomous agents, integrate tool-calling APIs, and create intelligent copilots with LangChain and Semantic Kernel.
Data Scientists & ML Engineers
Master RAG architecture, vector databases, embeddings, and deploy multi-agent systems for production environments.
Tech Leads & Product Managers
Understand agentic paradigms, orchestrate AI-powered products, and lead production-ready GenAI projects with confidence.
Career Professionals & Students
Learn cutting-edge AI frameworks and workflows to build a solid foundation in Agentic AI and Generative AI systems.
What You’ll Learn
5 power-packed modules across 2 weekends: From GenAI fundamentals to autonomous agents and production systems
Weekend 1 - Nov 15
Foundations – What are AI Agents and Agentic Workflows?
- Introduction to Autonomous Agents
- What is an AI agent? Agent vs. traditional program
- Where do agents fit in GenAI evolution?
- Real-world examples (AutoGPT, Copilot, personal assistants)
- Hands-on: Identify agent behaviors in consumer AI products
- Agent, Tool, Environment, Task, Observation, Action, Reward / Goal
- Types of agents: Reactive, Planning, Tool-using, Multi-agent
- The Agent Loop: Perceive, Decide, Act, Learn (high-level)
- Monolithic vs. Modular / Composable agents
- Toolformer, Function-calling, and Planning approaches
- Single-agent vs. Multi-agent system overviews
- Discussion: When is the agentic paradigm needed?
Weekend 1 - Nov 16
Building Blocks – LLMs, Prompts, Tools, and Orchestration
- What makes an LLM ‘agentic’?
- Prompt-based tools vs. function-calling APIs
- Examples: GPT-4/3.5, OpenAI Tools API, Azure OpenAI, Ollama
- Hands-on: Calling tools/functions via LLM prompts
- What is a “Tool” in agentic GenAI?
- Tool selection, tool calling, tool observation
- Safety, reliability, and error handling in tool use
- Hands-on: Connecting an LLM to a simple external API
- What is orchestration? What is a controller?
- Overview: Semantic Kernel, LangChain, Guidance, CrewAI
- Comparing approaches: code-first vs. prompt-first
- Hands-on: “Plan and Execute” agent with Semantic Kernel or LangChain
Weekend 2 - Nov 22
Advanced Agent Capabilities – Planning, Memory, Autonomy, and RAG
- Task planning: From user goal to actionable steps
- Role of LLMs in planning and subtasking (ReAct, MRKL, etc.)
- Agent workflows: single-shot vs. iterative vs. recursive
- Hands-on: Implementing a simple planner agent
- What is agent “memory”? Short-term, long-term, episodic
- Memory stores: Vector DB (Pgvector, Pinecone)
- Using RAG (Retrieval Augmented Generation) as agent “knowledge”
- Hands-on: Giving your agent a simple memory
- Looping and reflection (self-correction, retry, planning)
- Tool selection and dynamic workflows
Weekend 2 - Nov 23
Practical Development – Building, Evaluating, and Deploying Agentic Systems
- Define user goals
- Build: prompt, plan, tool-use, memory, feedback loop
- Hands-on: End-to-end agent with tool-use and memory
- Evaluation of agent behaviors (correctness, safety, hallucination)
- Prompt/Plan debugging, monitoring tool calls, logging
- Human-in-the-loop: review, escalation, fallback
- Running locally (Ollama), on cloud (Azure OpenAI), desktop apps
- Security, privacy, responsible agent behaviors
- Connecting to APIs, product DBs, and ops systems
- Agents with vision, speech, multi-modal capabilities
- Human/AI hybrid workflows, continuous learning
- Open research: self-improving agents, meta-agents
Your Career Path After This Workshop
AI Application Developer
LLM Application Developer
AI Solutions Engineer
Prompt Engineer
Senior AI/ML Engineer
AI Application Developer
LLM Application Developer
AI Solutions Engineer
Prompt Engineer
Senior AI/ML Engineer
Key Takeaways
By the end of this workshop, you'll build autonomous agents, RAG systems, and production-ready agentic applications using the hottest AI frameworks and tools.
You’ll Be Able To:
- Build autonomous AI agents with tool-calling and multi-agent orchestration
- Master LangChain, Semantic Kernel, and CrewAI frameworks
- Implement ReAct patterns, planning, and task decomposition
- Work with GPT-4, Azure OpenAI, Ollama, and open-source LLMs
- Build production RAG systems with Pgvector, Pinecone, Chroma
- Deploy intelligent copilots, research assistants, and code agents
- Evaluate and monitor agent behaviors for safety and accuracy
- Apply agentic paradigms to real-world business problems
Top Companies Hiring Generative AI and Agentic AI Engineers
Why This Workshop?
This workshop is conducted by AI/ML Practitioner Mr. Ashutosh, Ex-Samsung, Philips. Master the hottest AI technologies: autonomous agents, RAG architecture, and production-ready GenAI systems in just 2 weekends.
Agentic AI Mastery
Build autonomous agents with tool-calling, multi-agent orchestration, and self-improving systems using LangChain & Semantic Kernel.
Production-Ready Skills
Deploy RAG systems, vector databases, and intelligent agents for real-world applications like copilots and assistants.
Industry Expert Training
Learn from an industry expert with techniques used by leading AI companies and engineering teams.
Hands-on Projects
Build with trending tools: GPT-4, Azure OpenAI, Ollama, Pgvector, Pinecone, CrewAI, and open-source frameworks.
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