
Discover how the 2026 bootcamp series on generative AI fits into our program, outlining bootcamp zero, one, and two, and how AI tools transform software engineering.
Discover flexible learning paths and rhythms tailored to your profile in this 2026 bootcamp, from beginner foundations to expert tracks, with monthly updates and hands-on lm applications and agents.
Explore the 2024 generative AI landscape, from large language models to agents and networks, and learn how text, images, and video creation enable enterprise productivity and new opportunities.
Develop generative AI skills to advance professionally, leveraging AI capabilities to improve workplace outcomes.
Discover who this program serves, from executives and engineers to entrepreneurs, professionals, and students, and that no prior knowledge is required.
Meet Julio Colomer, director of bootcamp and CEO of AI accelerator, with 20 years as a software and AI engineer in Silicon Valley, and author of four generative AI books.
Learn how this bootcamp uses two learning systems and two program parts, with keys to success through practice, repetition, and self-discipline, plus downloadable materials and coaching.
Trace the evolution of artificial intelligence from machine learning to generative AI. Learn why LLM applications are at the core of the universalization era and how to develop them.
Do not leave the program or rate it mid-theory; read reviews from peers who stayed, and follow the learning routes and rhythms from theory to practical projects to unlock value.
Explore the 2026 edition updates to keys to artificial intelligence and 100 AI startups, revealing strategic knowledge, new chapters on agents, vive coding, regulation, and practical market applications.
This updated edition highlights how generative AI adoption skyrocketed, offering extraordinary opportunities and threats; learn how agents, bytecoding, and regulation shape careers, salaries, and thriving startups.
Trace the evolution of AI engineering and the rise of the AI engineers who blend machine learning, software engineering, and product management into full stack app engineers for LM applications.
Explore how the data scientist and machine learning engineer differ from the new generative ai engineer, highlighting five key differences in data, models, workflow, and roles.
Adopt generative ai across your organization as its adoption is universal, accelerating, and in early stages. Lead the change by piloting ai transformation with human collaboration across all departments.
learn how to form the first ai team after pilot projects, pairing a hybrid manager with tech-focused members to align with company priorities and ai project types.
Analyze how artificial intelligence will replace tasks rather than eliminate jobs. Short-term impact affects administrative, customer service, and legal roles at about 7%, with long-term predictions from leaders.
AI training in your company is a strategic necessity that will reshape competition. Executives must prepare for change, investing in AI training to get ahead and grow the business.
Identify who should receive AI training in your company—engineers, managers, leaders, and AI project leaders—and equip them with technical, operational, strategic, feasibility, resource allocation, and progress monitoring skills.
Design an AI training plan in five steps, from an introductory program to technical and business analysis, an AI pilot, building an AI team, and shaping the company's AI strategy.
Explore the 2026 edition's largely new content, featuring 100 startup success cases in finance and fintech, plus strategic chapters and an introduction to the AI startup ecosystem.
Identify opportunities for startups by leveraging the paradigm shift of artificial intelligence, emphasizing agility, market understanding, and niche focus to move from demos to robust and scalable products.
This Online Bootcamp is a compact and accelerated version of our 400-hour in-person master's program.
It has four parts:
- In Part 1, you will learn the keys to Artificial Intelligence and the new Generative AI, as well as its potential to revolutionize businesses, startups, and employment.
- In Part 2, you will learn to build professional-level LLM Applications and AI Agents using a safe and error-free learning environment. You will also learn how to build Advanced RAG Apps, Multimodal Apps, Dynamic Agents, Multi-Agent Apps, and how to manage LLMOps.
- In Part 3, you will learn how to build traditional and Gen AI apps without coding using Cursor AI and the new AI Coding Assistants. You will learn what are AI Coding Assistants like Cursor AI, Claude AI, v0, o1, Replit Agent, etc, and how to increase their performance by combining them with tools like the Replit platform, simplified backends like Firebase, Replicate AI, Stable Fusion, or Deepgram. You will also learn about the new AI Agents that can work in your computer: Open Claw Bots, Clawdbots, Moltbots, and Moltbook.
- In Part 4, you will learn how to create SaaS applications without coding using Cursor AI. You’ll also see, through two high-level real-world examples, how Generative AI is transforming the SaaS (Software as a Service) model.
By the end of this program, you will know how to do the following:
AI AND BUSINESS
Know the businesses that AI puts at risk of disappearing.
Know the new opportunities created by AI for businesses.
Design a plan to introduce AI into your company.
Select an appropriate pilot project to introduce AI into your company.
Form the first AI team in your company.
Prepare your company's AI strategy.
AI AND STARTUP
Identify 100 opportunities to create AI startups.
AI AND EMPLOYMENT
Know the professions that AI puts at risk of disappearing.
Know the new professions created by AI.
LLM APPLICATIONS AND AI AGENTS, THE APPLICATIONS WITH THE GREATEST POTENTIAL OF GENERATIVE AI.
Know the main use cases of LLM Applications in businesses and startups.
RAG LLM Applications.
Multimodal LLM Applications.
AI Agents.
Multi-Agent LLM Applications.
CREATION OF PROFESSIONAL LLM APPLICATIONS AND AI AGENTS.
You will learn the differences between LLM Applications and AI Agents.
You will learn the Architecture of an LLM Application.
You will learn how to learn programming languages like Python and Javascript.
You will learn to work with your computer's terminal.
You will learn to work with Jupyter notebooks.
You will learn to work with code editors like Visual Studio Code.
You will learn to work with virtual environments.
You will learn to work with hidden files to save credentials.
You will learn how to use different LLM models (OpenAI, DeepSeek, Meta, Mistral, Anthropic, Groq, etc).
You will learn the RAG (Retrieval Augmented Generation) technique.
You will learn to use LangChain, including the new 1.0 version and later.
You will learn to use the LangChain Expression Language (LCEL).
You will learn LCEL in depth.
You will learn how to work with Middleware and Dynamic Agents.
You will learn to use the new versions of LangChain (1.0 and later).
You will learn to use LlamaIndex.
You will learn to use the OpenAI API.
You will learn to use OpenAI's functions.
You will learn to use LangSmith.
You will learn to use LangServe and the new ways to deploy LangChain apps.
You will learn to use templates of LangChain and LlamaIndex.
You will learn what AI Agents are and how to create them.
You will learn to create prototypes of LLM applications and AI Agents with LangChain, Streamlit, and Agent Chat UI.
You will learn to create full-stack CRUD applications with Nextjs, FastAPI, and Postgres.
You will learn to create professional full-stack LLM applications with LangChain, LlamaIndex, Nextjs, Tailwind CSS, FastAPI, Flask, and Postgres.
You will learn to use vector and traditional databases.
You will learn to deploy applications on Vercel and Render.
You will learn to use AWS S3 as a remote storage platform.
You will learn to use ChatGPT as a programming assistant.
You will learn to use GPT4-Vision and GPT4o.
You will learn to work with Github and Github Codespaces.
You will learn what LLMOps is and how to use it in your LLM Applications and Agents.
You will learn the principles of Responsible AI and how to use them in your LLM Applications.
You will learn how to build advanced RAG LLM Applications and Agents.
You will learn how to build the new Multimodal LLM Applications.
You will learn how to build the new AI Agents.
You will learn how to build Multi-Agent Applications.
You will learn to use LangGraph.
You will learn to use CrewAI.
You will learn about the new Deep Agents framework.
APP DEVELOPMENT WITHOUT CODING USING CURSOR AI AND THE NEW AI CODING ASSISTANTS
Cursor AI, the new AI Coding Assistants and the future of software development.
Analysis of Cursor AI and the top AI Coding Assistants.
Top strategies and techniques to get the most from Cursor AI.
The best Cursor AI combo for beginners: custom starter template, Replit, v0, and Firebase.
How to build 6 complete projects without coding using Cursor AI: from a simple to-do list app, to a social network, a chatbot, a tex-to-image app, a voice-to-text app, and a basic full-stack SaaS app with authentication and payment systems.
You will also learn about the new AI Agents that can work in your computer: Open Claw Bots, Clawdbots, Moltbots, and Moltbook.
HOW GENERATIVE AI IS DISRUPTING THE SAAS BUSINESSES
How Generative AI is replacing major SaaS apps like Salesforce and Workday.
How AI Agents are killing SaaS apps.
The future of SaaS and Micro SaaS.
The Bootcamp consists of:
More than 750 lessons divided into sections.
More than 750 videos.
More than 400 attached presentations.
More than 300 practical notebooks.
60 practical code repositories on Github.
55 LLM applications of different difficulty levels: basic, intermediate, and advanced.
Material for more than 400 hours of study and practice for the student.
3 downloadable books valued at $100: "Keys to Artificial Intelligence", "100 AI Startups that made more than $500,000 before the first year" and "Prompt Engineering for Beginners".
Topics included in this Bootcamp:
AI, Generative AI, AI Applications, LLM Applications, Multimodal LLM Applications, chatGPT, Llama2, GPT-4 Vision, GPT4o, Full-Stack Applications, LangChain, LangChain Expression Language (LCEL), LangChain v1.0 LlamaIndex, OpenAI, OpenAI API, RAG, RAG Technique, Vector databases, Postgres, Pinecone, Chroma, DeepLake, Streamlit, Nextjs, Tailwind CSS, Vercel, FastAPI, Flask, Render, AWS S3, LangSmith, LangServe, LangChain Templates, LlamaIndex Templates, LLMOps, Responsible AI, LangGraph, CrewAI, Multi-Agent LLM Apps, AI Agents, Groq, Llama3, Mixtral, Cursor AI, Cursor, Composer, v0, Claude AI, Claude 3.5 Sonnet, o1, o1-preview, o1-mini, Replit Agent, Replit, Firebase, Supabase, Replicate AI, Stable Fusion, Deepgram, SaaS, Micro SaaS, DeepSeek, Deep Agents.