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Agentic AI bootcamp

Learn to build agents, not just apps. Automate reasoning, planning, context retrieval and execution.

Technologies and Tools

4.95

Switchup Rating

11,000+

Alumni

2,500+

Companies Trained

900,000+

Community Members

For who

Who is this bootcamp for?

The Agentic AI Bootcamp is designed for professionals who already understand the basics of LLMs and are ready to take the next leap, building intelligent, autonomous AI agents using real-world tools and techniques.

Data and AI
professionals

You’ve worked with LLMs—now learn to build systems that reason, plan, and act. This bootcamp teaches you how to integrate tools like LangChain, vector databases, and RAG to build truly agentic workflows.

Engineers and
developers

Take your technical skills further by deploying LLM-powered agents in production environments. Learn how to connect APIs, fine-tune performance, and handle edge cases in real-time applications.

Product leaders and builders

Go beyond prompts. Understand the architecture behind AI agents and how to design agentic workflows that solve complex problems, automate internal processes, or power new customer-facing products.

Researchers and advanced learners

If you’re exploring the frontier of autonomous systems, this bootcamp offers a practical foundation in agent frameworks, memory, multi-agent setups, and evaluation methods—taught with the latest tools.

Instructors and guest speakers

Learn from though leaders at the forefront of building agentic AI applications

Qdrant Instructor

Thierry Damiba

Developer Advocate, Qdrant
Zain Hasan Together AI Agentic AI Conference

Zain Hasan

Senior DevRel Engineer, Together AI
sage_headshot

Sage Elliot

AI Engineer, Union AI
Luis Serrano Serrano Academy Agentic Ai Conference

Luis Serrano

Founder, Serrano Academy
Raja Iqbal Ejento AI Agentic AI Conference

Raja Iqbal

Founder, Ejento AI
Kartik - Agentic AI Conference

Kartik Talamadupula

Head of AI, Wand AI
Instructor Hamza Farooq from Traversaal AI, guiding participants through the LLM Bootcamp.

Hamza Farooq

Founder, Travesaal AI
Adam Cowley | Developer Advocate Neo4j

Adam Cowley

Developer Advocate, Neo4j
Instructor Sophie Daly from Stripe , guiding participants through the LLM Bootcamp.

Sophie Daly

Staff Data Scientist, Stripe

Earn A Verified Certificate

Earn a verified certificate from The University of New Mexico Continuing Education:

  • 3 Continuing Education Credit (CEU)
  • Acceptable by employers for reimbursements
  • Valid for professional licensing renewal
  • Verifiable by The University of New Mexico Registrar’s office
  • Add to LinkedIn and share with your network

curriculum

Explore the bootcamp curriculum

Overview of the topics and practical exercises.

Use components like Model I/O, loaders, memory, and retrieval chains to develop applications that retain and use context effectively.

Learn how to create intelligent applications that maintain context over time using LLM-specific tooling and architecture.

Key Topics:

  • Understanding Model I/O: prompts, responses, parsers
  • Retrieval chains using loaders and retrievers
  • Implementing memory: buffer memory, summarization memory, vector-backed memory
  • Combining modules into coherent, state-aware workflows
  • An Introduction to model context protocol
  • Hands-on exercises on module topics

A comprehensive introduction to vector databases

Learn about efficient vector storage and retrieval with vector database, indexing techniques, retrieval methods, and hands-on exercises.

  • Rationale for vector databases
  • Vector search, text search, hybrid search
  • Product Quantization (PQ), Locality Sensitive Hashing (LSH) and Hierarchical Navigable Small World (HNSW)
  • Retrieval: Cosine Similarity, Nearest Neighbor Search
  • Relevance scoring in hybrid search using Reciprocal Rank Fusion (RRF)
  • Using auto-cut feature to remove irrelevant results dynamically
  • Improving search relevance by using language understanding to re-rank search results
  • Challenges: Scaling optimization. Reliability optimization. Cost optimization
  • Hands-on exercise on similarity search, hybrid search, vector compression, generative search and semantic caching.

Build collaborative agents using tools and LangGraph to handle complex, multi-step tasks dynamically.

Build distributed, multi-tasking agents that collaborate to perform complex actions using tools, task routing and modular workflows.

Key Topics:

  • Introduction to tools, agents and autonomous behavior
  • Tools for building multi-agent systems (LangChain agents, toolkits)
  • Designing task-specific agents (e.g., planner, executor, summarizer)
  • Communication protocols between agents
  • Hands-on: Create a multi-agent system for a business use case

Explore LangGraph’s node-based workflows, async execution, and memory-aware agent routing.

Dive into LangGraph’s orchestration engine to create structured workflows, decision trees, and looping behaviors.

Key Topics:

  • Graph-based orchestration models
  • A Practical Guide to Coordinated LLM Agents Using LangGraph: Nodes (functions or agents), Edges (data/control flow), Cycles (iteration, self-correction), State
  • Add memory or context passing between agents
  • Node-based task design
  • Async vs sync execution in agentic flows
  • Conditional routing and stateful transitions
  • Integrating memory into LangGraph workflows
  • Hands-on exercises using LangGraph

Implement reusable LLM behavior patterns like ReAct, Reflection, and CodeAct for dynamic reasoning and action.

Implement advanced reasoning and decision-making patterns that enable LLMs to plan, reflect, and act intelligently.

Key Topics:

  • ReAct (Reason + Act) framework
  • Reflection: self-checking and improvement
  • CodeAct: write + execute code dynamically
  • Combining patterns into flexible agents
  • Use cases: coding agents, research agents, evaluators
  • Hands-on exercises on building ReAct, Reflection and CodeAct agentic workflows

Understand how agents communicate and collaborate across platforms like Google A2A and others for seamless orchestration.

Learn how to make agents interoperable across platforms, tools, and APIs for broader AI orchestration.

Key Topics:

  • Google A2A (Agents-to-Agents) overview
  • Cross-agent communication architecture
  • Creating API-ready agents
  • Token hand-off strategies across multiple LLMs
  • Building language-agnostic agent endpoints
  • Hands-on: Deploy agents that call and respond to each other

Track, debug, and evaluate agent behavior and LLM performance using robust observability tools.

Establish robust monitoring to understand agent behavior, debug workflows, and ensure safety and reliability in production.

Key Topics:

  • Logging and tracing agent decisions
  • Callback mechanisms in LangChain & LangGraph
  • Tracking token usage, latency, success rate
  • Visual debugging of agent flows

Hands-on Exercise:

  • Add observability to your agent workflow 

Attend the Agentic AI Bootcamp for free

We Accept Tuition Benefits

All of our programs are backed by a certificate from The University of New Mexico, Continuing Education. This means that you may be eligible to attend the bootcamp for FREE.

Not sure? Fill out the form so we can help.

Get a certificate from The University of New Mexico Continuing Education with 3 CEUs

UNM's continuing education | Data Science Dojo

Agentic AI Bootcamp

Use AGENTIC500 for USD 500 discount

Online

Morning Cohort

Sept 30 -> Nov 25

Every Tuesday 9 AM to 12 PM PT

$3000

$2499

Online

Evening Cohort

Oct 09 -> Dec 4

Every Thursday 5 PM to 8 PM PT

$3000

$2499

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Frequently asked questions, answered.

Who does the Agentic AI Curriculum target?

The Agentic AI bootcamp is designed for both technical and non-technical professionals, including engineers, product managers, and business leaders alike. While it includes high-level modules on AI fundamentals, prompt engineering, and strategic deployment, it also dives deep into technical components for developers.

The bootcamp is an 9-week, 30-hour program.

Yes. You will receive a certificate from The University of New Mexico with 3 CEUs.

Yes, participants who complete the bootcamp will receive a certificate of completion in association with the University of Mexico. This certificate can be a valuable addition to your professional portfolio and demonstrate your expertise in building large language model applications.

The LLM bootcamp covers the fundamentals of large language models and takes you through a complete learning track—from the basics to deployment.

In contrast, the Agentic AI bootcamp focuses specifically on building and deploying AI agents, so we dive straight into hands-on development. 

Yes, these sessions are live and are designed to be highly interactive.

When you join the Agentic AI bootcamp, you will receive:

  • Live sessions with industry experts
  • 1-year access to dedicated learner sandboxes
  • Exclusive access to Agentic AI coding labs
  • Access to all session recordings for review at your convenience
  • A verified certificate upon completion

Each live session is recorded and made available for review to both online and in-person participants a few days after the boot camp concludes, allowing them to view it at their convenience.

  • Basic understanding of LLM fundamentals and Python
  • LLM architectures: foundation models, prompts, embeddings, fine-tuning
  • Challenges & risks: prompt brittleness, context limits, security, cost
  • Transformers & attention: self-attention, multi-head attention, tokenization

You need a very basic level of Python programming for our Agentic AI bootcamp.

The preparatory material will be shared about two weeks before the bootcamp starts. You’ll receive an email with access details and instructions closer to the start date.

No, cloud subscriptions are not included. Participants will need to use their own accounts.

Transfers are allowed once with no penalty. Transfers requested more than once will incur a $200 processing fee.

If, for any reason, you decide to cancel, we will gladly refund your registration fee in full if notified five business days before the start of the training. We would also be happy to transfer your registration to another cohort. Refunds cannot be processed if you have transferred to a different cohort after registration.

While we do not specifically focus on job placement, we actively promote networking with our partners, attendees, and an extensive network of alumni. Once you register for the bootcamp, we are happy to assist with introductions if you’re looking to connect with professionals in your desired field.