Udemy

2026 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI

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  • 更新於 10/2025
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課程資料

報名日期
全年招生
課程級別
學習模式
教學語言
英語
授課導師
Julio Colomer
證書
  • 可獲發
  • *證書的發放與分配,依課程提供者的政策及安排而定。
評分
4.3
(3,374 個評分)
27次瀏覽

課程簡介

2026 Bootcamp: Generative AI, LLM Apps, AI Agents, Cursor AI

From zero to professional level: learn the keys to Generative AI, LLM Apps, AI Agents, and Cursor AI.

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, the most potential applications of Generative AI. You will also learn how to build Advanced RAG LLM Apps, Multimodal LLM Apps, AI Agents, Multi-Agent LLM 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.

- 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, 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.

  • 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.

  • You will learn to use the LangChain Expression Language (LCEL).

  • You will learn LCEL in depth.

  • You will learn to use the new versions v010 and v020 of LangChain.

  • 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.

  • 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 (demos) of LLM applications with LangChain and Streamlit.

  • 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.

  • 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.

  • 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 the new Multi-Agent LLM Applications.

  • You will learn to use LangGraph.

  • You will learn to use CrewAI.


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.

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 650 lessons divided into sections.

  • More than 650 videos.

  • More than 320 attached presentations.

  • More than 220 practical notebooks.

  • 50 practical code repositories on Github.

  • 45 LLM applications of different difficulty levels: basic, intermediate, and advanced.

  • Material for more than 400 hours of study and practice for the student.

  • 2 downloadable books valued at $50: "Keys to Artificial Intelligence" and "100 AI Startups that made more than $500,000 before the first year".


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 v010, LangChain v020, 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.

課程章節

  • 81 個章節
  • 712 堂課
  • 第 1 章 Program presentation
  • 第 2 章 Tips for the students
  • 第 3 章 INTRODUCTION: LLM Apps, the key to the New AI
  • 第 4 章 Download the two books included with the program
  • 第 5 章 PART 1: IMPORTANCE OF ARTIFICIAL INTELLIGENCE AND GENERATIVE AI.
  • 第 6 章 AI: Changes in Employment
  • 第 7 章 AI: Changes in Businesses
  • 第 8 章 AI: Changes in Startups
  • 第 9 章 AI: Changes in Society
  • 第 10 章 How to introduce AI in your company
  • 第 11 章 The new AI Training
  • 第 12 章 The new AI creates opportunities for consulting, advisors and marketing agencies
  • 第 13 章 UPDATED REPORT: The State of The Generative AI Revolution
  • 第 14 章 PART 2: LLM APPS, THE GENERATIVE AI APPLICATIONS WITH THE HIGHEST POTENTIAL
  • 第 15 章 Use Cases for LLM Applications
  • 第 16 章 Intro to LLMs
  • 第 17 章 LLMs: Basic Concepts
  • 第 18 章 [NEW] Prompt Engineering: Do you speak Generative AI? A Beginner's Guide
  • 第 19 章 Architecture of an LLM App
  • 第 20 章 Details of the advanced architecture of an LLM Application
  • 第 21 章 The RAG Technique (Retrieval Augmented Generation)
  • 第 22 章 Selecting Orchestration Framework: LangChain, LlamaIndex or OpenAI API?
  • 第 23 章 Intro to the usage of Programming Languages
  • 第 24 章 [NEW] LangChain: Conceptual Intro, Evolution, and Learning Roadmap
  • 第 25 章 [NEW] LangChain Learning Stack: Videos, Detailed Notebooks, and stable Code.
  • 第 26 章 [NEW] LangChain Basics: How to start talking with an LLM
  • 第 27 章 [NEW] LangChain Basics: How to Work with Data. RAG Basics.
  • 第 28 章 [NEW] LangChain Basics: LCEL Chains and Runnables, the key LangChain tools
  • 第 29 章 [NEW] LangChain Basics: Memory. Can LLM Apps remember?
  • 第 30 章 [NEW] LangChain Basics: The LangChain Ecosystem
  • 第 31 章 [NEW] LangChain Level 1 Apps: The Top 10 LangChain Apps
  • 第 32 章 [NEW] LangChain Level 2 Apps: Temporary Frontend to test your Proof-of-Concept
  • 第 33 章 LlamaIndex
  • 第 34 章 The OpenAI API
  • 第 35 章 Intro to Level 3 LLM Applications: Professional Applications
  • 第 36 章 Level 3 LLM Applications: Professional Applications
  • 第 37 章 LLM Applications: Advanced Concepts
  • 第 38 章 [NEW] MCP: Model Context Protocol
  • 第 39 章 Cost control in LLM Applications
  • 第 40 章 LLMOps
  • 第 41 章 [NEW] LLMOps with LangSmith: LLMOps Cycle & How LangSmith solves the challenges
  • 第 42 章 [NEW] LLMOps with LangSmith: LangSmith in Depth
  • 第 43 章 [NEW] LangSmith Versions
  • 第 44 章 [NEW] LangSmith At Work: From Basic Example to Professional Project
  • 第 45 章 [NEW] Multimodal LLM Applications with LangChain
  • 第 46 章 [NEW] LLM RAG Applications with LangChain in Depth
  • 第 47 章 [NEW] RAG vs. Large Context LLM Models: Is RAG dead, or stronger than ever?
  • 第 48 章 [NEW] Phases of a RAG Application: Code and Resources
  • 第 49 章 [NEW] Building a Level 3 Advanced FullStack RAG Application with LangChain
  • 第 50 章 [NEW] Advanced techniques to improve the functionality of RAG Apps in LangChain
  • 第 51 章 [NEW] Advanced techniques to improve the performance of RAG Apps
  • 第 52 章 [NEW] Multi-Agent LLM Apps in Depth
  • 第 53 章 [NEW] Intro to AI Agents
  • 第 54 章 [NEW] AI Agents in LangChain
  • 第 55 章 [NEW] Intro to Multi-Agent LLM Apps: AutoGen, LangGraph and CrewAI
  • 第 56 章 [NEW] Multi-Agent LLM App Development: How to Use The LangGraph Framework
  • 第 57 章 [NEW] Multi-Agent LLM App Development: How to Use the CrewAI Framework
  • 第 58 章 [NEW] A low cost option: CrewAI with Groq, Llama3 and Mixtral
  • 第 59 章 [NEW] Full Stack Multi-Agent LLM App with CrewAI (Level 3 App)
  • 第 60 章 [NEW] PART 3: HOW TO BUILD APPS USING CURSOR AI AND AI CODING ASSISTANTS
  • 第 61 章 [NEW] Intro to the new Gen AI Coding Assistants: A Revolutionary Change
  • 第 62 章 [NEW] Cursor AI and other Gen AI Coding Assistants: Essential concepts
  • 第 63 章 [NEW] Cursor AI, Claude, o1, v0, Replit: Top Gen AI Coding Assistants Today
  • 第 64 章 [NEW] Top Strategies to get best results with Cursor AI and Coding Assistants
  • 第 65 章 [NEW] A few caveats before starting with Cursor AI: cost options and others
  • 第 66 章 [NEW] Building a Basic Full-Stack App with Cursor AI, v0, Replit, and Firebase
  • 第 67 章 [NEW] Replit in depth
  • 第 68 章 [NEW] Cursor AI in depth
  • 第 69 章 [NEW] Building Advanced Apps with Cursor AI, Replit, Replicate AI, Deepgram, etc
  • 第 70 章 [NEW] Cursor AI is just the beginning: buckle up for a frantic future!!!
  • 第 71 章 [NEW] The new Claude Code
  • 第 72 章 [NEW] The new Codex from OpenAI
  • 第 73 章 [NEW] How to use Coding Assistants and Vibe Coding Tools properly
  • 第 74 章 [NEW] PART 4: HOW GENERATIVE AI IS DISRUPTING SAAS APPS AND BUSINESSES
  • 第 75 章 [NEW] How Generative AI is changing SaaS Businesses: Two Real Cases
  • 第 76 章 [NEW] Understanding the SaaS Business Model
  • 第 77 章 [NEW] SaaS and Micro SaaS: do not be fooled by "get-rich-quick" schemes
  • 第 78 章 [NEW] Building a SaaS App with Cursor AI
  • 第 79 章 Top Information Channels for AI Engineers
  • 第 80 章 Congrats! Next steps.
  • 第 81 章 BONUS SECTION: This will interest you!

課程內容

  • Keys to AI, Generative AI, LLM Apps, and new AI Coding Assistants like Cursor AI.
  • LLM Apps with LangChain, CrewAI, LangGraph, LangServe and LangSmith.
  • How to build apps without coding using Cursor AI and AI Coding Assistants.
  • How to build the new Multimodal and Multi-Agent LLM Applications.
  • Opportunities and threats of AI for businesses, startups, and jobs.
  • RAG Applications in Depth: Full Stack RAG Apps and Advanced Techniques.
  • How to manage LLMOps: Observability, Evaluation, Testing, Etc.
  • Professional opportunities opened by Artificial Intelligence.
  • Steps to become an Artificial Intelligence Engineer.
  • How to introduce Artificial Intelligence into your business.
  • Keys to LLM Applications, the highest potential applications of Generative AI.
  • Architecture of professional LLM Applications.
  • The RAG Technique (Retrieval Augmented Generation).
  • Artificial Intelligence Agents.
  • Basic and advanced LangChain, LangChain LCEL, and LangChain v010. LangSmith, LangServe, LangChain Templates.
  • LCEL (LangChain Expression Language) in depth.
  • Basic and advanced LlamaIndex. LlamaIndex Templates.
  • ChatGPT, OpenAI, OpenAI functions, and the OpenAI API.
  • Large Language Models (LLM): ChatGPT, Llama2, Mistral, Falcon, etc.
  • Vector databases: Postgres, Pinecone, Chroma, FAISS, DeepLake, etc.
  • Full-Stack Applications: Nextjs and FastAPI.
  • Professional deployment: Vercel and Render.
  • Provisional deployment: Streamlit.
  • Cloud hosting: AWS S3.
  • How to apply the principles of Responsible AI.
  • Daily tools of the AI Engineer: Jupyter Notebooks, Python, Terminal, Github, Codespaces, etc.


評價

  • V
    Vivek Birla
    4.5

    great course!

  • G
    Govin Cootapen
    5.0

    Throughout my career, I’ve explored many sectors but never felt the pull to specialise in just one. My foundation has always been in Accounting and Finance and while I watched others pursue professional qualifications like ACCA or CFA, something inside me urged patience. Deep down, I knew that path wasn’t mine. At times, this left me feeling behind and yes, some people looked down on me. I still remember two interviews with two major companies: one interviewer told me I was a “jack of all trades, master of none,” while another suggested I had only moved forward through luck and good interviews. Those words could have discouraged me, but instead I used them as fuel to keep going. Then, the missing piece clicked into place. When I joined the AI Accelera Bootcamp, I realised that AI isn’t confined to one sector, it’s the future of every industry. Suddenly, my diverse background in Private Equity, Education, Fintech and Travel became not a weakness, but a unique strength. Each experience added perspective and adaptability that I can now bring into the world of AI. I am deeply grateful to Julio and the Accelera team for opening this door. For the first time, my CV feels like it has a story that makes sense. I’ve discovered a field I am passionate about, a career path that excites me and most importantly, a sense of belonging. The journey has just begun, but I’m ready. I can’t wait to dive into the next chapter with the AI Agents Bootcamp. Govin

  • C
    Carl VanS
    5.0

    I’m not a programmer by trade, but I’ve spent over 25 years working as an IT Systems Engineer and Business Analyst on SAP projects, so I’ve definitely seen my fair share of IT/tech. Over the years, I’ve taken 119 Udemy courses, and this one truly stands out. At first, the pace may seem a bit slow, but don’t let that mislead you. If you’re looking to get started with generative AI, LLM applications, or AI agents, this course does a fantastic job of breaking down complex concepts into something you can actually grasp and apply. What I really appreciate is how thorough and supportive it is. Unlike many other courses that rush to the finish line and skip over key steps (often assuming you already have a coding background), this one walks you through the process in a clear, structured way. You get the full picture, actual working projects, with detailed guidance, even if you’re new to programming. If you’re curious about AI and want a practical, no-fluff introduction, I highly recommend this bootcamp. It delivers on its promise. One quick tip: I’ve been watching it at 1.25x speed, which makes the pacing feel just right. And since it offers around 80 hours of high-quality content for the same price as many much shorter courses, it’s a real value. If you already know specific topics, just skip ahead to the chapters that are most relevant to you.

  • B
    Bob
    5.0

    Great coverage to help understand and build LLM apps from start to finish. Definitely recommend this course.

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