[PimpMyMoney] Aurimas Griciunas - End-to-End AI Engineering Bootcamp

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[PimpMyMoney] Aurimas Griciunas - End-to-End AI Engineering Bootcamp (Size: 1.7 GB)
  0. Sprint – Problem Framing, Infrastructure Setup & RAG Foundations
  001 Understanding the AI product lifecycle.html 20.2 MB
  002 Tooling overview (LangGraph, vector DBs, LLM APIs, etc.).html 1.9 MB
  003 What is RAG.html 2.5 MB
  004 Embedding models & vector DB integration.html 1.1 MB
  005 Implementing basic observability foundations.html 1002.8 KB
  006 Evaluating basic end-to-end retrieval and generation.html 1.6 MB
  007 Hands-On Section.html 4.5 MB
  008 Amazon Electronics Category Dataset Overview.html 1.3 MB
  009 [OPTIONAL] AI Project Canvas.html 1.5 MB
  010 [OPTIONAL] Success metrics & evaluation frameworks.html 4.9 MB
  1. Setting Up Your Environment
  1. Setting up your development environment.mp4 103.9 MB
  2. Setting up your development environment.mp4 94 MB
  3 Setting up your development environment.mp4 79.2 MB
  4. Setting up your development environment.mp4 80.6 MB
  Setting up your development environment..html 2.4 MB
  2. Bootcamp Preparation
  001 12 JAN End-to-end AI Engineering bootcamp Prep.mp4 198.1 MB
  3. Hands on Sections
  002 Hands-On Section 1.mp4 187.2 MB
  003 Hands-On Section 2.mp4 137.2 MB
  004 Hands-On Section 3.mp4 68.2 MB
  005 Hands-On Section 4.mp4 104.7 MB
  006 Hands-On Section 5.mp4 111.1 MB
  007 Hands-On Section 6.mp4 126.2 MB
  008 Hands-On Section 7.mp4 111.9 MB
  009 Hands-On Section 8.mp4 94.9 MB
  4. Sprints
  010 Sprint Review Project framing, tooling overview, and repo setup.mp4 251.3 MB

Description


The field of artificial intelligence is rapidly evolving, and technical professionals need specialized skills to build production-ready AI systems. For developers, data scientists, and technical leaders looking to transition into AI engineering or enhance their existing capabilities, comprehensive training is essential to stay competitive in today's market.
The End-to-End AI Engineering Bootcamp by Aurimas Griciunas offers a structured pathway to mastering the complete AI development lifecycle. This intensive program focuses on transforming prototypes into fully deployed applications, addressing the gap that many professionals face when trying to implement AI solutions in real-world scenarios.
What You'll Learn and Build

Throughout this bootcamp, participants develop a complete AI application from concept to deployment. You'll progress through each phase of the AI development process, building practical skills that can be immediately applied to your work or personal projects.
Technologies Covered

The curriculum includes essential AI engineering technologies that are in high demand across industries:
Large Language Model APIs (Gemini, Claude, GPT)

Vector databases and Retrieval-Augmented Generation (RAG)

AI agent frameworks (LangChain, LangGraph)

Containerization and deployment (Docker, FastAPI, Kubernetes)

Cloud deployment strategies

Observability and performance evaluation

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