AI engineering roadmap with resources

Here’s a comprehensive, in‑depth guide to AI Engineering - including structured learning paths, key topics, practical projects, essential tools, YouTube videos & channels, and resources.

📌 What AI Engineering Is

AI Engineering is the discipline of designing, building, testing, deploying, and scaling real‑world AI systems and intelligent apps. It blends:

• Software engineering

• Machine learning & deep learning

• Data science & data pipelines

• Large Language Models (LLMs) & generative AI

• MLOps & production deployment practices
  This field emphasizes applied AI (not just theory) — turning models into products. (FreeCodeCamp)

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🧠 Core AI Engineering Roadmap

Phase 1 - Foundations

Goal: Build core skills that every AI engineer needs

• Python programming — essential language in AI

• Math for ML: linear algebra, statistics, probability, calculus

• Python libraries: NumPy, Pandas, Matplotlib

• Version control: Git & GitHub

Tip: Solid foundations make advanced topics much easier.

🔗 YouTube Starter Video:
📺 What is AI Engineering? — Telusko (intro to role + skills):
👉

(youtube.com)

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Phase 2 - Machine Learning & Deep Learning

Goal: Master the core techniques that power AI

• Supervised/unsupervised learning

• Feature engineering

• Deep neural networks

• Convolutional & recurrent nets

Must‑watch YouTube Course:
📺 AI Engineer Roadmap — How to Learn AI in 2025 (freeCodeCamp.org):
👉

(youtube.com)

This ~1‑hour roadmap video covers:

• What AI Engineering is

• Math & stats essentials

• ML fundamentals

• Deep learning basics

• LLMs & Generative AI

• Ethics & career paths (youtube.com)

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Phase 3 - Applied AI Engineering

Goal: Build real AI products and workflows
Focus on practical implementation:

• APIs & open‑source models (OpenAI, Hugging Face)

• Prompt engineering

• Large Language Models (LLMs)

• Generative AI tools (DALL‑E, Whisper, etc.)

• Chaining and multi‑modal flows

🔗 YouTube Project Workshop:
📺 AI Engineering 101 – Build 5 Projects with GPT, DALL‑E & Whisper
(Hands‑on real projects) (Class Central)
(Search on YouTube or Class Central for the exact video)

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📺 YouTube Channels & Playlists to Follow

🔥 General AI Engineering & ML

• freeCodeCamp.org – deep, structured tutorials

• DeepLearningAI – career‑focused, advanced topics (DigitalOcean)

• AI Engineering (channel) – practical tutorials for developers (BestYoutubeChannels)

• Jordan Harrod – tech & educational AI videos (Wikipedia)

🧮 Math & Theory

• 3Blue1Brown — Essence of Linear Algebra

• StatQuest with Josh Starmer

🔍 Research & Insights

• Two Minute Papers – AI research explained

• Yannic Kilcher – deep dives into model architectures

🛠 Projects, Tools & Deployment

• Krish Naik/CodingKnowledge – real‑world Python/ML projects

• Corey Schafer – practical Python coding

• MLOps Community – deployment workflows (cloud, containers)

👉 Pro playlist lists often shared on LinkedIn — e.g., Karpathy’s Neural Networks, Stanford Transformer series. (LinkedIn)

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🧑‍💻 Practical Projects You Should Build

Transform theory into skill by building:

1. Chatbot with OpenAI/GPT API

2. Image generator with DALL‑E or Stability AI

3. Speech‑to‑Text with Whisper

4. Retrieval‑Augmented Generation (RAG) pipeline

5. End‑to‑end web app serving LLM responses

Project Tutorials:

• Chatbot with YouTube integration (Python/Flask + OpenAI) (Class Central)

• GPT, DALL‑E & Whisper workshop (hands‑on) (Class Central)

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🛠 Real Tools, Libraries & Platforms

📦 Core Libraries

• Python

• NumPy / Pandas / Matplotlib

• Scikit‑Learn

• TensorFlow / PyTorch

🤖 LLM & GenAI

• OpenAI API (GPT, DALL‑E, Whisper)

• Hugging Face Transformers & Datasets

• LangChain (building AI workflows)

• RAG libraries (retrieval + LLM)

☁️ Cloud & Deployment

• Docker & containers

• CI/CD pipelines

• AWS, GCP, Azure for production scaling

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🎓 Recommended Courses & Books

(Not all are free, but widely respected)

• Andrew Ng’s ML & Deep Learning Specialization (Coursera)

• fast.ai – Practical Deep Learning for Coders

• Hugging Face Learn (free) — Transformers + Agents

• The AI Engineer’s Handbook (referenced guide) (Class Central)

• Stanford CS231n / CS224n (class lectures on YouTube)

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🧠 Summary - Recommended YouTube Learning Stack

🎥 Intro & Roadmap

• What is AI Engineering? — Telusko (youtube.com)

• AI Engineer Roadmap — freeCodeCamp.org (youtube.com)

📺 Project & APIs

• AI Engineering 101 (Build Projects) (Class Central)

• Chatbot project tutorial (Class Central)

📺 Channels to Subscribe

• freeCodeCamp.org

• DeepLearningAI

• AI Engineering

• Jordan Harrod

• Two Minute Papers

• StatQuest / 3Blue1Brown

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