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

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size1.7 GB
  • Uploaded ByCryOrDie2
  • Downloads86
  • Last checkedJul. 16th '26
  • Date uploadedJul. 16th '26
  • Seeders 21
  • Leechers5

Infohash : 02E7BE906C9D153980E725112D684F5B85084FD5

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

Files:

Aurimas Griciunas - End-to-End AI Engineering Bootcamp 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 (1,002.8 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 (94.0 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)

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