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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

Luis - Agentic AI Panelist

Luis Serrano

Founder, Serrano Academy
Raja Iqbal-Data Science Dojo

Raja Iqbal

Founder, Ejento AI
Sebastian Witalec | Weaviate

Sebastian Witalec

Director of Developer Relations, Weaviate
John Gilhuly | Arize AI | Data Science Dojo

John Gilhuly

Head of Developer Relations, Arize AI
Kartik - Agentic AI Conference

Kartik Talamadupula

Head of AI, Wand AI
Jerry Agentic AI Panelist

Jerry Liu

CEO/Co-founder, LlamaIndex
Zain - Agentic AI Panelist

Zain Hasan

Senior DevRel Engineer, Together AI
1703300423927 (1)

Sage Elliot

AI Engineer, Union AI
Instructor Sophie Daly from Stripe , guiding participants through the LLM Bootcamp.

Sophie Daly

Staff Data Scientist, Stripe
Rehan Jalil Securiti AI

Rehan Jalil

Co-Founder | CEO, Securiti AI
Adam Cowley | Developer Advocate Neo4j

Adam Cowley

Developer Advocate, Neo4j
hamza farooq

Hamza Farooq

Founder, Travesaal AI
Qdrant Instructor

Thierry Damiba

Developer Advocate, Qdrant

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

Upcoming sessions

Reserve your spot

Learn to build AI Agentic applications from leading experts in industry. 

Agentic AI Bootcamp

Use AGENTIC500 for USD 500 discount

Confused ? Schedule a call with an Advisor 

Pace

Dates

Time

Price

Enroll Now

Online

Sept 30 -> Nov 18

Every Tuesday
9 AM to 12 PM PT

$2499

Online

Oct 09 -> Nov 27

Every Thursday
5 PM to 8 PM PT

$2499

A Word From Our Alumni

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FAQ

Your 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.

What is the duration of the Bootcamp?

The bootcamp is an 8-week, 30-hour program.

Is the program accredited?

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

Will I get a Certificate after the completion of the Bootcamp?

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.

What is the difference between the Agentic AI and the LLM Bootcamp?

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.

Are the online sessions live?

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

What benefits will I receive in the Agentic AI Bootcamp?

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
What if I’m unable to attend a live session?

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.

What does the preparatory material include?
  • 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
Are there any prerequisites for the bootcamp?

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

When will I receive the preparatory material for the 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.

Are cloud subscriptions included?

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

What is the transfer policy for the bootcamp?

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

What is the refund policy?

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.

Will I get a job after completing the Bootcamp?

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.

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.

What is the duration of the Bootcamp?

The bootcamp is an 8-week, 30-hour program.

What benefits will I receive in the Agentic AI Bootcamp?

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
Is the program accredited?

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

Will I get a Certificate after the completion of the Bootcamp?

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.

What is the difference between the Agentic AI and the LLM Bootcamp?

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.

Are the online sessions live?

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

What if I’m unable to attend a live session?

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.

Are there any prerequisites for this bootcamp?

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

When will I receive the preparatory material for the 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.

Are cloud subscriptions included?

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

What does the preparatory material include?
  • 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
What is the transfer policy for the bootcamp?

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

What is the refund policy?

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.

Will I get a job after completing the Bootcamp?

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.