Industrial AIoT Bootcamp

Cohort Six | AI Orchestration with LLMs, RAG & Agents.

A FREE Gateway to a Future in Technology!

Step into the future with the 6th edition of our live, online Bootcamp on AI Orchestration with LLMs, RAG & Agents — designed for professionals who want to understand and implement advanced AI workflows. In just 8 weeks of part-time learning, gain practical skills in building LLM-based systems, RAG pipelines, and intelligent agents, and learn how to apply orchestration techniques to real-world AI projects.

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Who can benefit from it?

Who Should Join?

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Engineers and Developers

Professionals with software
or AI experience who want to gain
practical skills in orchestrating
LLMs, RAG pipelines, and
AI agents for real-world
applications.

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AI & Data Enthusiasts

Learners and practitioners
eager to explore prompt
engineering, vector databases,
knowledge graphs, and
advanced AI workflows.

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Creators with Ideas

Entrepreneurs, innovators
and startup teams
aiming to build next-gen AI
products using orchestration
techniques.

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Product Managers and
Tech Leaders

Decision-makers who need
to understand the orchestration
layer of AI to define smarter
features, evaluate solutions,
and guide cross-functional
teams effectively.

Be a Trailblazer in AI Orchestration

Join the Industrial AIoT Bootcamp and unlock the power of next-generation AI systems. With us, you'll gain:

Networking Opportunities


Connect with peers, mentors, and innovators exploring LLMs, retrieval systems, and AI agents across industries.

Exclusive Access to Tools & Resources


Work with APIs, vector databases, knowledge graphs, and agent frameworks powering modern AI applications.

Hands-On Experience in AI Orchestration


Apply orchestration techniques by building real-world AI systems with LLMs, RAG pipelines, and agents for autonomous workflows, contextual Q&A, and multi-agent collaboration.

Access to Expertise


Learn from SenzMate’s AI and product experts, who bring real-world experience in designing, deploying, and scaling AI-driven solutions.
BootCamp Program

Program Highlights

Target Audience

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Professionals from software, AI/ML, product management, and technology innovation who want to understand and apply LLMs, RAG pipelines, and AI agents in real-world projects.

Curriculum Design

Network

Our curriculum is crafted to give a practical understanding of AI orchestration, covering prompt engineering, vector databases, knowledge graphs, and agent frameworks—all applied to real-world AI solutions.

Practical Learning

Innvate

Gain hands-on experience building AI systems that combine LLMs, RAG pipelines, and agents. Work on projects like autonomous workflows, contextual Q&A, and multi-agent collaboration, guided by SenzMate experts with real-world deployment experience.

About the Bootcamp

Industrial AIoT Bootcamp | Cohort 06: AI Orchestration with LLMs, RAG & Agents

This module provides a comprehensive introduction to AI orchestration, covering Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), knowledge graphs, and AI agents. Participants will gain a deep understanding of how these components work together to build real-world AI systems. Through hands-on projects, learners will design, implement, and orchestrate AI workflows—applying techniques like autonomous task execution, contextual Q&A, and multi-agent collaboration. By the end of the module, participants will be equipped to build and manage AI solutions that are practical, scalable, and aligned with industry needs.

Module Plans for Cohort 6

  • Introduction to LLMs

    • Evolution of Large Language Models (LLMs)
    • Core concepts: Transformers, attention, pre-training vs fine-tuning
    • Hands-on: Using a hosted LLM (e.g., GPT-4 / Llama 3) via API
    • Case studies of LLM applications in industry

    Cohort 06 | Week 01

  • Prompt Engineering

    • Principles of effective prompting
    • Zero-shot, few-shot, chain-of-thought prompting
    • Structured prompting (JSON, XML outputs, tools integration)
    • Hands-on: Building application with reusable prompt templates

    Cohort 06 | Week 02

  • Retrieval Augmented Generation (RAG) Fundamentals

    • Why RAG is needed: overcoming context limitations of LLMs
    • Workflow: document ingestion → chunking → embeddings → retrieval
    • Hands-on: Build a simple Q&A application over documents using vector search

    Cohort 06 | Week 03

  • Vector Databases & Search

    • Deep dive into vector embeddings & similarity search
    • Comparison of vector DBs: Pinecone, Weaviate, Chroma, FAISS
    • Hybrid search (keyword + semantic)
    • Hands-on: Connect LLMs with a vector DB for contextual Q&A

    Cohort 06 | Week 04

  • Knowledge Graphs & Graph Databases

    • Knowledge Graphs: nodes, edges, relationships
    • Use cases: reasoning, explainability, data integration
    • Tools: Neo4j, GraphQL, RDF/OWL basics
    • Hands-on: Build a small graph DB and query it with Cypher/SPARQL

    Cohort 06 | Week 05

  • Combining Graphs with LLMs

    • Knowledge-augmented LLMs (GraphRAG, Graph Neural Networks + LLMs)
    • How graphs improve accuracy and traceability
    • Hands-on: Application with querying graph DB with natural language using an LLM

    Cohort 06 | Week 06

  • Agents & Orchestration

    • What are AI Agents? Planning, reasoning, and tool usage
    • Agent frameworks: LangGraph, LangChain Agents, CrewAI
    • Multi-agent collaboration patterns
    • Hands-on: Build a simple LLM agent with tool calling

    Cohort 06 | Week 07

  • Advanced Agent Techniques

    • Memory in agents (short-term, long-term, episodic memory)
    • Multi-modal agents (text, vision, audio, code execution)
    • Hierarchical & recursive agents (agents managing sub-agents)
    • Safety, alignment, and guardrails in agent systems
    • Hands-on: Build an agent with persistent memory and multi-tool capabilities

    Cohort 06 | Week 08

Cohort 06 | Week 01

Introduction to LLMs

  • Evolution of Large Language Models (LLMs)
  • Core concepts: Transformers, attention, pre-training vs fine-tuning
  • Hands-on: Using a hosted LLM (e.g., GPT-4 / Llama 3) via API
  • Case studies of LLM applications in industry

Cohort 06 | Week 02

Prompt Engineering

  • Principles of effective prompting
  • Zero-shot, few-shot, chain-of-thought prompting
  • Structured prompting (JSON, XML outputs, tools integration)
  • Hands-on: Building application with reusable prompt templates

Cohort 06 | Week 03

Retrieval Augmented Generation (RAG) Fundamentals

  • Why RAG is needed: overcoming context limitations of LLMs
  • Workflow: document ingestion → chunking → embeddings → retrieval
  • Hands-on: Build a simple Q&A application over documents using vector search

Cohort 06 | Week 04

Vector Databases & Search

  • Deep dive into vector embeddings & similarity search
  • Comparison of vector DBs: Pinecone, Weaviate, Chroma, FAISS
  • Hybrid search (keyword + semantic)
  • Hands-on: Connect LLMs with a vector DB for contextual Q&A

Cohort 06 | Week 05

Knowledge Graphs & Graph Databases

  • Knowledge Graphs: nodes, edges, relationships
  • Use cases: reasoning, explainability, data integration
  • Tools: Neo4j, GraphQL, RDF/OWL basics
  • Hands-on: Build a small graph DB and query it with Cypher/SPARQL

Cohort 06 | Week 06

Combining Graphs with LLMs

  • Knowledge-augmented LLMs (GraphRAG, Graph Neural Networks + LLMs)
  • How graphs improve accuracy and traceability
  • Hands-on: Application with querying graph DB with natural language using an LLM

Cohort 06 | Week 07

Agents & Orchestration

  • What are AI Agents? Planning, reasoning, and tool usage
  • Agent frameworks: LangGraph, LangChain Agents, CrewAI
  • Multi-agent collaboration patterns
  • Hands-on: Build a simple LLM agent with tool calling

Cohort 06 | Week 08

Advanced Agent Techniques

  • Memory in agents (short-term, long-term, episodic memory)
  • Multi-modal agents (text, vision, audio, code execution)
  • Hierarchical & recursive agents (agents managing sub-agents)
  • Safety, alignment, and guardrails in agent systems
  • Hands-on: Build an agent with persistent memory and multi-tool capabilities

Expected Outcomes of Cohort 6

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Comprehensive understanding of AI orchestration concepts, including LLMs, RAG pipelines, knowledge graphs, and AI agents.

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Proficiency in building and managing AI workflows for real-world applications such as contextual Q&A, autonomous task execution, and multi-agent collaboration.

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Expertise in integrating LLMs with vector databases, knowledge graphs, and agent frameworks for scalable AI solutions.

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Hands-on experience with tools and frameworks used in AI orchestration, including LangChain, CrewAI, Pinecone, Neo4j, and other industry-standard platforms.

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Knowledge of best practices for designing, deploying, and maintaining practical AI solutions.

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Confidence in orchestrating AI-driven systems for product development, business solutions, and industry projects.

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Networking opportunities with peers, mentors, and industry professionals working in AI and related fields.

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Certificate of Completion to validate your skills and knowledge in AI orchestration and practical AI system design.

Prerequisites for Cohort 6

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Expected to dedicate 8–10 hours per week to complete the bootcamp over 8 weeks, including live online sessions.

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Participate in 2-hour hands-on sessions each week (attendance is recommended).

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Engage in optional 1-hour Q&A sessions to deepen understanding and clarify concepts.

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Basic understanding of AI or machine learning concepts is preferred, with familiarity in programming or working with AI tools.

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Interest in exploring LLMs, retrieval-augmented generation, knowledge graphs, and AI agent frameworks, with a passion for building real-world AI systems and workflows.

How to enroll

Apply and join BootCamp in 5 easy steps

Kickstart your journey by expressing your interest in joining the AIoT Bootcamp. Complete the application form to communicate your passion and career aspirations.
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After expressing your interest, our team will thoroughly review your application. Once selected, you'll receive a confirmation along with detailed information about the bootcamp.
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Participate in an orientation session where you'll get insights into the structure of the bootcamp, meet the instructors, and connect with fellow participants. This session sets the stage for a collaborative and engaging learning experience.
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Get hands-on with the basics! Our expert instructors will guide you through fundamental knowledge, ensuring you have a strong foundation before delving into more advanced topics and real world scenarios.
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Experience the practical side of big data and IoT! Engage in a collaborative project kickoff where you'll work on real-world applications. From concept to implementation, our team will support you every step of the way.
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SenzMate's Industrial AIoT Bootcamp | Cohort 06- Enrollment Form

Join SenzMate’s Industrial AIoT Bootcamp by filling out the form below. This 8-week program is designed for professionals eager to master the next generation of AI systems, combining Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent agents. Gain hands-on experience in orchestrating AI workflows, building contextual Q&A systems, and designing multi-agent solutions that mirror real-world applications. Take the next step in your AI journey by learning how to design, deploy, and scale orchestrated AI solutions in a collaborative, industry-focused environment.

Important Information:
  • Funding: This program is fully funded.
  • Selection Process: In the first round, we are selecting 30 candidates based on your profile for the 6th cohort.
  • Registration Deadline: Please complete your registration by 06/10/2025

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Frequently Asked Questions



What is the Bootcamp like? ▼

This cohort provides an immersive, hands-on learning experience designed to equip you with the skills to orchestrate AI systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent agents. Over 8 weeks, you will work on real-world projects, including building contextual Q&A systems, multi-agent workflows, and AI pipelines integrated with vector databases and knowledge graphs. The program is fully focused on practical AI applications, ensuring that your skills are directly relevant to real-world challenges in product development, business solutions, and industry projects. Courses are conducted on a dedicated Moodle LMS platform for an engaging, remote, part-time learning experience.

How long does it take to complete the Bootcamp? ▼

The program runs for 8 weeks with part-time learning, including live sessions, hands-on projects, and Q&A discussions. Whether you are a professional looking to upskill or an AI enthusiast exploring orchestration technologies, this cohort provides a structured and practical learning approach to help you thrive in the evolving AI landscape.

How much does the Bootcamp cost? ▼

The bootcamp has been developed and resourced by SenzMate AIoT Intelligence as part of our CSR initiative. As a result, the entire 8-week program is completely free free for selected participants.

What skills are needed for the Bootcamp? ▼

To succeed in this cohort, it’s helpful to have a basic understanding of AI or machine learning concepts. Familiarity with Python, APIs, or data handling is beneficial but not mandatory. Prior exposure to software systems, databases, or product workflows is a plus. Most importantly, enthusiasm for real-world AI applications, curiosity about LLMs and agent frameworks, and a willingness to experiment with tools like RAG pipelines will significantly contribute to your success.

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