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دسته بندی دوره ها

2024 Bootcamp: Generative AI + LLM App Development

سرفصل های دوره

From zero to professional level: learn the keys to AI and build the most potential Generative AI applications.


1. Program presentation
  • 1.1 001BENG-PRESENTATION.pdf
  • 1. Program presentation
  • 2. Opportunities this program will open for you
  • 3. What will you learn in this program
  • 4. Materials included in the program
  • 5. Who is this program for
  • 6. What makes this program different
  • 7. Introduction of the Instructor
  • 8. Share your progress

  • 2. Tips for the students
  • 1.1 002BENG-PRACTICAL TIPS.pdf
  • 1. Tips for the students
  • 2. Practical tips for the students
  • 3.1 003BENG-THE SECRET TO SUCCESS.pdf
  • 3. The secret to successfully completing this bootcamp

  • 3. INTRODUCTION LLM Apps, the key to the New AI
  • 1.1 004BENG-LLM APPS, THE UNIVERSALIZATION OF AI.pdf
  • 1. LLM Apps, the key to the New AI
  • 2. LLM Apps and the universalization of AI

  • 4. ChatGPT vs. LLM Apps
  • 1. ChatGPT vs. LLM Apps

  • 5. Download the two books included with the program
  • 1.1 EBOOK 100 AI Startups.pdf
  • 1.2 EBOOK Keys to AI.pdf
  • 1. Download the two books included with the program.html

  • 6. PART 1 IMPORTANCE OF ARTIFICIAL INTELLIGENCE AND GENERATIVE AI
  • 1.1 006BENG-WHAT IS AI.pdf
  • 1.2 007BENG-CHANGES INTRODUCED.pdf
  • 1. Intro to Artificial Intelligence
  • 2. Artificial Intelligence What is it Why is so popular now How important is it
  • 3. Changes introduced by AI Introduction

  • 7. AI Changes in Employment
  • 1.1 008BENG-CHANGES IN EMPLOYMENT.pdf
  • 1. AI Changes in Employment
  • 2. Jobs that will benefit the most from AI
  • 3. Jobs most affected by AI
  • 4. Jobs least affected by AI
  • 5. New professions created by AI
  • 6. The new AI Engineers

  • 8. AI Changes in Businesses
  • 1.1 009BENG-CHANGES IN BUSINESS (1).pdf
  • 1. AI Changes in Businesses
  • 2. Consequences of the changes in employment
  • 3. Industries with high impact
  • 4. Industries with median impact
  • 5. Industries with immediate impact

  • 9. AI Changes in Startups
  • 1.1 010BENG-CHANGES IN STARTUPS.pdf
  • 1. AI Changes in Startups
  • 2. Opportunities for Startups Characteristics of the New AI
  • 3. Opportunities for Startups Changes in Employment
  • 4. Opportunities for Startups AI impact on Businesses
  • 5. Opportunities for Startups Book 100 AI Startups

  • 10. AI Changes in Society
  • 1.1 011BENG-CHANGES IN SOCIETY.pdf
  • 1. AI Changes in Society
  • 2. Social changes generated by the New AI
  • 3. Social challenges generated by the New AI

  • 11. How to introduce AI in your company
  • 1.1 012BENG-HOW TO INTRODUCE AI IN YOUR COMPANY.pdf
  • 1. How to introduce AI in your company
  • 2. Plan to introduce AI in your company
  • 3. Tech and Business Analysis to introduce AI in your company
  • 4. How to select the right pilot project to introduce AI in your company
  • 5. How to form the first AI Team in your company
  • 6. How to prepare the AI Strategy of your company
  • 7. Example Plan to adopt a new LLM App in your company

  • 12. The new AI Training
  • 1.1 013BENG-AI TRAINING.pdf
  • 1. The new AI Training
  • 2. AI Training in your company an strategic necessity
  • 3. Who should get AI Training in your company
  • 4. How to design an AI Training Plan for your company
  • 5. The new AI Training for engineers

  • 13. The new AI creates opportunities for consulting, advisors and marketing agencies
  • 1.1 014BENG-OPPORTUNITIES FOR CONSULTING FIRMS.pdf
  • 1. The new AI creates opportunities for consulting, advisors and marketing agencies
  • 2. Opportunities for consulting firms, business advisors, and marketing agencies

  • 14. PART 2 LLM APPS, THE GENERATIVE AI APPLICATIONS WITH THE HIGHEST POTENTIAL
  • 1.1 015BENG-WHAT ARE LLM APPS.pdf
  • 1.2 016BENG-THE MYTH OF THE PREREQUISITES FOR LEARNING.pdf
  • 1.3 017BENG-TYPES OF STUDENTS AND REASONS FOR LEARNING.pdf
  • 1.4 018BENG-BUILD VS HIRE.pdf
  • 1.5 019BENG-THE LONG ROAD FROM TOY DEMO TO PROFESSIONAL APP.pdf
  • 1.6 020BENG-PROFESSIONAL OPPORTUNITIES OF THE LLM APP DEVELOPER.pdf
  • 1. Intro LLM Apps, the Generative AI applications with the highest potential
  • 2. What is an LLM App
  • 3. The myth of pre-requisites for learning
  • 4. Most frequent types of students reasons to learn
  • 5. DIY or hire an external professional
  • 6. The long way from the toy demo to the professional app
  • 7. Job opportunities for the LLM App Developer

  • 15. Use Cases for LLM Applications
  • 1.1 021BENG-USE CASES LLMS.pdf
  • 1.2 022BENG-LLMS USE CASES IN DATA ANALYSIS AND CONTENT CREATION.pdf
  • 1.3 023BENG-USES FOR DATA SCIENTISTS.pdf
  • 1.4 024BENG-LLM APP TYPES BY LEVELS OF REASONING.pdf
  • 1.5 028BENG-GEN AI USE CASES.pdf
  • 1.6 041BENG-TOP LLM USE CASES.pdf
  • 1. Use Cases for LLM Applications
  • 2. Use Cases for LLM Apps by Industry
  • 3. Use Cases for LLM Apps in Startups
  • 4. Use Cases for LLM Apps in Professions
  • 5. Most frequent Use Cases for LLM Apps
  • 6. Use Cases for LLM Apps by autonomy level

  • 16. Intro to LLMs
  • 1.1 025BENG-ORIGINS OF LLM APPS AI, ML, NLP, LLM.pdf
  • 1.2 031BENG-HOW BIG ARE LLMS.pdf
  • 1.3 032BENG-WHAT ARE FOUNDATION LLM.pdf
  • 1. Intro to LLMs
  • 2. Origins of LLM Apps AI, ML, NLP, Generative AI, LLMs
  • 3. LLM size, precision, and cost
  • 4. The Foundation LLM Models

  • 17. LLMs Basic Concepts
  • 1.1 033BENG-WHAT IS THE CONTEXT WINDOW.pdf
  • 1.2 034BENG-WHAT ARE TOKENS.pdf
  • 1.3 035BENG-PROMPTS AND RELATIONSHIP WITH CONTEXT.pdf
  • 1.4 036BENG-PROMPT ENGINEERING AND ITS IMPORTANCE.pdf
  • 1.5 037BENG-HALLUCINATIONS.pdf
  • 1. LLMs Basic Concepts
  • 2. What is the Context Window
  • 3. What are Tokens
  • 4. What are Prompts
  • 5. What is Prompt Engineering
  • 6. What are Hallucinations

  • 18. Architecture of an LLM App
  • 1.1 038BENG-BASIC LLM APP ARCHITECTURE.pdf
  • 1.2 039BENG-ADVANCED ARCHITECTURE LLM APP.pdf
  • 1. Architecture of an LLM App
  • 2. Basic Architecture of an LLM App
  • 3. Advanced Architecture of an LLM App
  • 4. Preview of a professional LLM App (1)
  • 5. Preview of a professional LLM App (2)

  • 19. Details of the advanced architecture of an LLM Application
  • 1.1 040BENG-TOP CONSIDERATIONS TO CHOOSE FOUNDATION MODEL.pdf
  • 1.2 042BENG-TOP LLMs USED.pdf
  • 1.3 043BENG-ALTERNATIVE LLMS PALM.pdf
  • 1.4 044BENG-STACK USED.pdf
  • 1.5 045BENG-ORCHESTRATION FRAMEWORKS.pdf
  • 1.6 046BENG-APP DEBUGGING WITH LANGSMITH.pdf
  • 1.7 047BENG-TOP EVALUATION METHODS.pdf
  • 1.8 048BENG-EVALUATION MEASURING RAG PERFORMANCE.pdf
  • 1.9 049BENG-OPTIMIZING RAG APPS.pdf
  • 1.10 050BENG-TOP CHALLENGES DEPLOYING TO PRODUCTION.pdf
  • 1.11 051BENG-MICROSERVICES ARCHITECTURE.pdf
  • 1. Details of the advanced architecture of an LLM Application
  • 2. Selection of Foundation LLMs
  • 3. Stack of tools
  • 4. Orchestration Frameworks
  • 5. Other interesting notes

  • 20. The RAG Technique (Retrieval Augmented Generation)
  • 1.1 052BENG-OVERCOMING CONTEXT WINDOW.pdf
  • 1.2 053BENG-THE RAG TECHNIQUE.pdf
  • 1.3 054BENG-RAG VS IN-CONTEXT LEARNING.pdf
  • 1.4 055BENG-RAG IS ESSENTIAL FOR LLM APP DEV.pdf
  • 1.5 056BENG-COMPONENTS OF RAG.pdf
  • 1.6 057BENG-EMBEDDINGS.pdf
  • 1.7 058BENG-VECTOR DATABASES.pdf
  • 1.8 059BENG-CHALLENGES OF RAG.pdf
  • 1.9 113BENG-RAG TECHNIQUE ADVANCED CONCEPTS.pdf
  • 1. The RAG Technique (Retrieval Augmented Generation)
  • 2. Basic Concepts
  • 3. Components
  • 4. RAG Technique Advanced Concepts
  • 5. Challenges

  • 21. Selecting Orchestration Framework LangChain, LlamaIndex or OpenAI API
  • 1.1 060BENG-LANGCHAIN, LLAMAINDEX OR OPENAI API .pdf
  • 1. Selecting Orchestration Framework LangChain, LlamaIndex or OpenAI API
  • 2. LangChain, LlamaIndex or OpenAI API

  • 22. Intro to the usage of Programming Languages
  • 1.1 084BENG-PROGRAMMING AND LLM APPS.pdf
  • 1.2 085BENG-PRELIMINARY NOTES.pdf
  • 1.3 086BENG-RECOMMENDATION USE VENV.pdf
  • 1.4 087BENG-TERMINAL.pdf
  • 1.5 088BENG-HIDDEN FILE FOR OPENAI API TOKEN.pdf
  • 1.6 089BENG-OPERATIONS WITH JUPYTER NOTEBOOKS.pdf
  • 1. Intro to the usage of Programming Languages
  • 2. Never programmed before Do not worry.
  • 3. Practical Tips if you are new to programming
  • 4. DEMO W3Schools and ChatGPT in action
  • 5. Virtual environment what is it, why is it important and how to create one (1)
  • 6.1 086BENG-RECOMMENDATION USE VENV.pdf
  • 6. Virtual environment what is it, why is it important and how to create one (2)
  • 7. Terminal what is it, why is it important, basic operations (1)
  • 8.1 087BENG-TERMINAL.pdf
  • 8. Terminal what is it, why is it important, basic operations (2)
  • 9.1 088BENG-HIDDEN FILE FOR OPENAI API TOKEN.pdf
  • 9. File for secret credentials why is it important, how to create it
  • 10. How to create and read Hybrid Notebooks (code + text) with Jupyter (1)
  • 11.1 089BENG-OPERATIONS WITH JUPYTER NOTEBOOKS.pdf
  • 11. How to create and read Hybrid Notebooks (code + text) with Jupyter (2)

  • 23. Basic LangChain
  • 1.1 lc-v010-001.zip
  • 1. Warning Modifications introduced by the LangChain v0.1.0 version
  • 2. Examples of .env file and data folder
  • 3. Links to data folder and example of .env file.html
  • 4. Basic LangChain
  • 5.1 090BENG-BASIC LANGCHAIN IN 15 MIN.pdf
  • 5.2 v1-052-langchain-in-15-mins.zip
  • 5. Basic LangChain in 15 minutes
  • 6.1 062ENG-LANGCHAIN MODELS.pdf
  • 6.2 v1-401-langchain-models.zip
  • 6. Models
  • 7.1 063BENG-LANGCHAIN PROMPTS AND PROMPT TEMPLATES.pdf
  • 7.2 v1-403-langchain-prompts.zip
  • 7. Prompts and prompt templates
  • 8.1 064BENG-FEW SHOT PROMPT TEMPLATE.pdf
  • 8.2 v1-801-langchain-few-shot-template.zip
  • 8. Few shot prompt templates
  • 9.1 065BENG-LANGCHAIN OUTPUT PARSERS.pdf
  • 9.2 v1-404-langchain-output-parsers.zip
  • 9. Output parsers
  • 10.1 066BENG-LANGCHAIN MEMORY.pdf
  • 10.2 v1-405-langchain-memory.zip
  • 10. Memory
  • 11.1 067BENG-LANGCHAIN CHAINS.pdf
  • 11.2 v1-406-langchain-chains.zip
  • 11. Chains
  • 12.1 068BENG-LANGCHAIN DOCUMENT LOADERS.pdf
  • 12.2 v1-407-langchain-document-loaders.zip
  • 12. Document loaders
  • 13.1 069BENG-LANGCHAIN SPLITTERS.pdf
  • 13.2 v1-408-langchain-splitters.zip
  • 13. Splitters
  • 14.1 070BENG-LANGCHAIN CALLBACKS.pdf
  • 14.2 v1-803-langchain-callbacks.zip
  • 14. Callbacks
  • 15.1 071BENG-LANGCHAIN OPENAI FUNCTIONS.pdf
  • 15.2 v1-804-langchain-openai-functions-app-avanzada-comida-china.zip
  • 15. OpenAI functions
  • 16.1 072BENG-LANGCHAIN CONNECT WITH FASTAPI.pdf
  • 16.2 v1-805-basic-rag-app-qa-to-fastapi.zip
  • 16. Connect with fastAPI
  • 17.1 073BENG-LANGCHAIN AGENTS.pdf
  • 17.2 v1-806-langchain-agents.zip
  • 17. Agents
  • 18.1 074BENG-LANGCHAIN INDEXING API.pdf
  • 18.2 v1-807-langchain-indexing-api.zip
  • 18. Indexing API

  • 24. LangChain Expression Language
  • 1. LangChain Expression Language
  • 2.1 075BENG-LCEL CHAINS.pdf
  • 2.2 v1-809-lcel-chains.zip
  • 2. LCEL Chains
  • 3.1 076BENG-LCEL OUTPUT PARSERS.pdf
  • 3.2 v1-810-lcel-output-parsers.zip
  • 3. LCEL Output parsers
  • 4.1 077BENG-LCEL ARGUMENTS.pdf
  • 4.2 v1-811-lcel-kargs-arguments.zip
  • 4. LCEL Arguments
  • 5.1 078BENG-LCEL OPENAI FUNCTIONS.pdf
  • 5.2 v1-812-lcel-openai-functions.zip
  • 5. LCEL OpenAI functions
  • 6.1 079BENG-LCEL RAG APPS.pdf
  • 6.2 v1-813-lcel-basic-rag-app-qa.zip
  • 6. LCEL Aplicaciones RAG

  • 25. LangChain Advanced Components
  • 1. LangChain Advanced Components
  • 2.1 080BENG-LANGCHAIN LANGSMITH.pdf
  • 2.2 v1-808-langchain-langsmith.zip
  • 2. LangSmith
  • 3.1 081BENG-LANGCHAIN LANGSERVE.pdf
  • 3.2 v1-814-langserve.zip
  • 3. LangServe
  • 4.1 082BENG-LANGCHAIN TEMPLATES.pdf
  • 4.2 v1-816-langchain-templates.zip
  • 4. LangChain Templates
  • 5.1 083BENG-LANGCHAIN CHAT WITH LANGCHAIN.pdf
  • 5. The new LangChain Chatbot

  • 26. Level 1 Applications Toy Demos with LangChain
  • 1. Reminder Modifications introduced by the LangChain v0.1.0 version
  • 2. Reminder Examples of .env file and data folder
  • 3. Reminder Link to data folder and sample .env file.html
  • 4. Level 1 Applications Toy Demos with LangChain
  • 5.1 091BENG-BASIC APP SUMMARIZE A LONG ARTICLE.pdf
  • 5.2 v1-053-basic-app-summarization.zip
  • 5. Basic app summarize long article
  • 6.1 092BENG-BASIC RAG APP QA OF DOCUMENT.pdf
  • 6.2 v1-054-basic-rag-app-qa.zip
  • 6. Basic RAG app document QA
  • 7.1 093BENG-BASIC APP EXTRACT DATA FROM CONVERSATION.pdf
  • 7.2 v1-055-basic-app-text-extraction.zip
  • 7. Basic app extract structured data from conversation
  • 8.1 094BENG-BASIC APP EVALUATE A QA APP.pdf
  • 8.2 v1-056-basic-app-evaluation.zip
  • 8. Basic app eval of QA app
  • 9.1 095BENG-BASIC APP ASK A DATABASE.pdf
  • 9.2 v1-057-basic-app-querying-tabular-data.zip
  • 9. Basic app ask a database
  • 10.1 096BENG-BASIC APP ASK A GITHUB REPO.pdf
  • 10.2 v1-058-basic-app-qa-a-github-repo.zip
  • 10. Basic app ask a github repo
  • 11.1 097BENG-BASIC APP ASK TO AN API.pdf
  • 11.2 v1-059-basic-app-interacting-with-api.zip
  • 11. Basic app ask an API
  • 12.1 098BENG-BASIC APP CHATBOT WITH MEMORY.pdf
  • 12.2 v1-060-basic-app-chatbot.zip
  • 12. Basic app chatbot with personality and memory
  • 13.1 099BENG-BASIC APP RAG WITH DEEPLAKE.pdf
  • 13.2 v1-061-basic-rag-with-deeplake.zip
  • 13. Basic app RAG with DeepLake
  • 14.1 100BENG-BASIC APP A SIMPLE AGENT.pdf
  • 14.2 v1-062-basic-app-simple-agent.zip
  • 14. Basic app simple agent
  • 15.1 101BENG-BASIC APP ADVANCED OUTPUT PARSER.pdf
  • 15.2 v1-063-basic-app-with-pydantic-output-parser.zip
  • 15. Basic app advanced output parser

  • 27. Level 2 Applications Toy Demos with LangChain and Toy UIs with Streamlit
  • 1.1 lc-v010-001.zip
  • 1. Reminder Modifications introduced by the LangChain v0.1.0 version
  • 2. Reminder Examples of .env file and data folder
  • 3. Reminder Link to data folder and sample of .env file.html
  • 4. Level 2 Applications Toy Demos with LangChain and Toy UIs with Streamlit
  • 5.1 v1-102BENG-END TO END APPS WITH STREAMLIT.pdf
  • 5. Intro to the level 2 apps
  • 6.1 103BENG-FROM POC TO PRODUCTION.pdf
  • 6. From Proof of Concept to Production
  • 7.1 104BENG-BASIC STREAMLIT.pdf
  • 7. Basic Streamlit
  • 8.1 105BENG-WRITING APP IMPROVE REDACTION.pdf
  • 8. App for re-writing informal text
  • 9. Link to download the code of the app in Github and URL to try the app.html
  • 10.1 106BENG-WRITING APP BLOG POST.pdf
  • 10. App to write a Blog Post from a topic
  • 11. Link to download the code of the app in Github and URL to try the app.html
  • 12.1 107BENG-SUMMARIZING APP TXT FILE.pdf
  • 12. App to summarize the content of a TXT file
  • 13. Link to download the code of the app in Github and URL to try the app.html
  • 14.1 108BENG-SUMMARIZING APP WRITING TEXT.pdf
  • 14. App to summarize text
  • 15. Link to download the code of the app in Github and URL to try the app.html
  • 16.1 109BENG-EXTRACTING APP KEY DATA FROM PRODUCT REVIEW.pdf
  • 16. App to Extract Key Data from a Product Review
  • 17. Link to download the code of the app in Github and URL to try the app.html
  • 18.1 110BENG-RAG APP PDF.pdf
  • 18. RAG App to ask about the content of a private PDF file
  • 19. Link to download the code of the app in Github and URL to try the app.html
  • 20.1 112BENG-RAG APP CSV.pdf
  • 20. RAG App to ask about the content of a private CSV file
  • 21. Link to download the code of the app in Github and URL to try the app.html
  • 22.1 114BENG-EVALUATING APP RAG.pdf
  • 22. App to Evaluate a RAG App
  • 23. Link to download the code of the app in Github and URL to try the app.html

  • 28. LlamaIndex
  • 1. LlamaIndex
  • 2.1 1004-llamaindex.zip
  • 2.2 116BENG-LLAMAINDEX.pdf
  • 2. Introduction to LlamaIndex
  • 3.1 1008-llamaindex-deep-dive.zip
  • 3.2 117BENG-LLAMAINDEX IN DEPTH.pdf
  • 3. LlamaIndex in depth

  • 29. The OpenAI API
  • 1. The OpenAI API
  • 2.1 1001-changes-opeai-api.zip
  • 2.2 118BENG-THE NEW OPENAI API VS LANGCHAIN.pdf
  • 2. The OpenAI API as alternative to LangChain and LlamaIndex
  • 3.1 1002-openai-api.zip
  • 3.2 119BENG-OPENAI API.pdf
  • 3. The OpenAI API in depth
  • 4.1 120BENG-OPENAI FUNCTIONS.pdf
  • 4. The OpenAI Functions

  • 30. Intro to Level 3 LLM Applications Professional Applications
  • 1. Intro to Level 3 LLM Applications Professional Applications
  • 2. Intro to Full-Stack Applications (1)
  • 3.1 121BENG-INTRO TO WEB APPS.pdf
  • 3. Intro to Full-Stack Applications (2)
  • 4. Front-End Key Elements in a Level 3 Application
  • 5.1 1009-vercel-deep-dive.zip
  • 5.2 122BENG-NEXTJS AND VERCEL IN DEPTH.pdf
  • 5. Next.js and Vercel
  • 6.1 1012-llamaindex-with-vercel.zip
  • 6.2 123BENG-LLAMAINDEX WITH VERCEL.pdf
  • 6. Front-End Key Elements with an Orchestration Framework LlamaIndex
  • 7. Link to download the code of the previous lesson from Github.html
  • 8. Back-End Key Elements in a Level 3 Application
  • 9.1 1022-fastapi.zip
  • 9.2 124BENG-FASTAPI.pdf
  • 9. FastAPI
  • 10. Link to download the code of the previous lesson from Github.html
  • 11.1 1023-minimal-lc-fastapi-starterkit.zip
  • 11.2 125BENG-FASTAPI WITH LANGCHAIN.pdf
  • 11. Back-End Key Elements with an Orchestration Framework LangChain
  • 12. Link to download the code of the previous lesson.html

  • 31. Level 3 LLM Applications Professional Applications
  • 1. Level 3 LLM Applications Professional Applications
  • 2. Reminder Architecture of an Advanced LLM App
  • 3. Reminder Preview of a Professional LLM App (1)
  • 4. Reminder Preview of a Professional LLM App (2)
  • 5.1 1006-sec-insights.zip
  • 5.2 1007-full-stack-app-components.zip
  • 5.3 126BENG-RAG APP PRODUCTION-READY TEMPLATE.pdf
  • 5.4 127BENG-SEC INSIGHTS FULL STACK APP LLAMAINDEX.pdf
  • 5.5 128BENG-SEC INSIGHTS ANALYSIS OF THE COMPONENTS.pdf
  • 5. Reminder main elements of a Professional LLM App
  • 6.1 1014-todo-app-fastapi-vercel-fullstack.zip
  • 6.2 130BENG-FULL STACK LEVEL 1 APP TO DO APP.pdf
  • 6. Basic Level 3 App CRUD with FastAPI, Postgres and Next.js
  • 7. Link to download the code of the Basic Level 3 App from Github.html
  • 8. Basic Level 3 App What is CRUD (1)
  • 9. Basic Level 3 App What is CRUD (2)
  • 10. Basic Level 3 App How to build the Backend (1)
  • 11. Basic Level 3 App How to build the Backend (2)
  • 12. Basic Level 3 App How to build the Backend (3)
  • 13. Basic Level 3 App How to build the Frontend (1)
  • 14. Basic Level 3 App How to build the Frontend (2)
  • 15. Basic Level 3 App How to start the Full Stack App (1)
  • 16. Basic Level 3 App How to start the Full Stack App (2)
  • 17. Basic Level 3 App How to deploy the backend to Render.com (1)
  • 18. Basic Level 3 App How to deploy the backend to Render.com (2)
  • 19. Basic Level 3 App How to deploy the frontend to Vercel.com (1)
  • 20. Basic Level 3 App How to deploy the frontend to Vercel.com (2)
  • 21.1 1019-pdf-app-fastapi-vercel-fullstack.zip
  • 21.2 131BENG-FULL STACK LEVEL 2 APP PDF APP.pdf
  • 21. Medium Level 3 App CRUD integrated with AWS S3 (1)
  • 22. Link to download the App code from Github.html
  • 23. Medium Level 3 App CRUD integrated with AWS S3 (2)
  • 24. Medium Level 3 App CRUD integrated with AWS S3 (3)
  • 25.1 1024-langchain-plus-todo-app.zip
  • 25.2 132BENG-TEMPLATE ENGLISH.pdf
  • 25. Basic Level 3 App with Orchestration Frameworks and LLMs (1)
  • 26. Reminder Modifications introduced by LangChain v010
  • 27. Link to download the App code from Github.html
  • 28. Basic Level 3 App with Orchestration Frameworks and LLMs (2)
  • 29.1 1025-langchain-pdf-app.zip
  • 29.2 133BENG-LANGCHAIN IN THE PDF FULL STACK APP.pdf
  • 29. Medium Level 3 App with Orchestration Frameworks and LLMs (1)
  • 30. Link to download the App code from Github.html
  • 31. Medium Level 3 App with Orchestration Frameworks and LLMs (2)
  • 32.1 1016-deep-dive-sec-insights.zip
  • 32.2 129BENG-DEEP DIVE SEC INSIGHTS FULL STACK APP.pdf
  • 32. Advanced Level 3 LLM App (1)
  • 33. Advanced Level 3 LLM App (2)
  • 34.1 1017-create-llama.zip
  • 34.2 1018-chat-llamaindex.zip
  • 34.3 134BENG-FULL STACK STARTER WITH CREATE LLAMA.pdf
  • 34.4 135BENG-FULL STACK APP CHAT LLAMAINDEX.pdf
  • 34. Other interesting Level 3 LLM Apps (1)
  • 35. Other interesting Level 3 LLM Apps (2)

  • 32. LLM Applications Advanced Concepts
  • 1. LLM Applications Advanced Concepts
  • 2.1 136BENG-PREPARATION OF PRIVATE DATABASES.pdf
  • 2. Database preparation
  • 3.1 137BENG-ADVANCED CONCEPTS TO OPTIMIZE RAG.pdf
  • 3. RAG Optimization Advanced Concepts
  • 4.1 138BENG-LATENCY AND SPEED OF LLM APPS.pdf
  • 4. Latency and Speed in LLM Applications

  • 33. Cost control in LLM Applications
  • 1.1 139BENG-COST OF LLM APPS.pdf
  • 1. Cost control in LLM Applications

  • 34. LLMOps
  • 1. LLMOps
  • 2.1 140BENG-LLM OPS.pdf
  • 2. Intro to LLMOps
  • 3.1 141BENG-EVALUATION LLM APPS MISALIGNED BEHAVIOR.pdf
  • 3. Evaluation Misaligned Behavior
  • 4.1 142BENG-EVALUATION LLM APPS AND LACK OF REPRODUCIBILITY.pdf
  • 4. Evaluation Lack of Reproducibility
  • 5.1 143BENG-LLM OPS MODEL LIFECYCLE MANAGEMENT.pdf
  • 5. Lifecycle Management
  • 6.1 144BENG-LLM OPS RESPONSIBLE AI.pdf
  • 6. Responsible AI
  • 7.1 145BENG-LLM OPS SOLUTIONS.pdf
  • 7. LLMOps Solutions

  • 35. Top Information Channels for AI Engineers
  • 1.1 146BENG-TOP INFORMATION CHANNELS.pdf
  • 1. Top Information Channels for AI Engineers

  • 36. Congrats! Next steps
  • 1.1 147BENG-CONGRATS.pdf
  • 1. Congrats! Next steps.
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