Uploaded May 2026 | Updated September 2026, 2 weeks ago
Top pick AI engineer courses:
Associate AI Engineer for Developers - datacamp.pxf.io/jRmdn6
Associate AI Engineer for Data Scientists - datacamp.pxf.io/PzbGrN
DataCamp - AI Fundamentals - datacamp.pxf.io/k4Wda3
This AI Engineering Roadmap for Beginners is a Realistic path to becoming properly ready for a job in this new AI industry! Want to learn to be an AI Engineer, check out the full roadmap https://roadmap.sh/ai-engineer
00:00 - Introduction - AI Roadmap
00:22 - Chapter 1 - AI Engineering Overview
00:48 - Chapter 2 - What is AI Engineering
01:26 - Chapter 3 - AI Job Market
01:55 - Chapter 4 - AI Engineer Roadmap Overview
02:34 - Chapter 5 - Python Programming
03:12 - Chapter 6 - AI Terminology - AGI LLM RAG DB
04:02 - Chapter 7 - How LLMs Work - Tokens Context Temp
04:56 - Chapter 8 - DataCamp AI Engineering Track
07:36 - Chapter 9 - Context Engineering
08:16 - Chapter 10 - Context Engineering - RAG
08:30 - Chapter 11 - Context Engineering - Context Compaction
09:03 - Chapter 12 - Context Engineering - Context Isolation
09:30 - Chapter 13 - Prompt Engineering - Zero Shot - Few Shot
10:07 - Chapter 14 - Prompt Engineering - Function Calling
10:38 - Chapter 15 - Prompt Engineering - Streaming Responses
11:08 - Chapter 16 - Prompt Engineering - System Prompting
11:32 - Chapter 17 - Prompt Engineering - Roles and Behaviours
11:50 - Chapter 18 - Prompt Engineering - Context and Constraints
12:09 - Chapter 19 - Prompt Engineering - Structured Outputs
12:26 - Chapter 20 - Types of Models
12:43 - Chapter 21 - Types of Models - Open / Closed Source
13:10 - Chapter 22 - Types of Models - Self Hosted Models
13:27 - Chapter 23 - Types of Models - Choosing the Right Model
14:18 - Chapter 24 - API and SDK
15:07 - Chapter 25 - Embedding Models
16:16 - Chapter 26 - Embedding Models - Vector Databases
16:54 - Chapter 27 - Embedding Models - RAG and Fine Tuning
17:35 - Chapter 28 - Model Context Protocol (MCP)
18:32 - Chapter 29 - Building MCP Servers and MCP Clients
19:03 - Chapter 30 - Security and Safety - Prompt Injection
19:51 - Chapter 31 - Multimodal AI
20:21 - Chapter 32 - AI Assisted Coding Tools - Cursor - Codex - Gemini
A big thanks to DataCamp for sponsoring todays videos, if you want to learn more about them, and their courses and material to learn all about AI, definitely check out the links above!
#ai #roadmap #datacamp
Want to learn web design? ⭐ Check out my course! ⭐
📘 Teach Me Design - Course: enhanceui.com
Top pick AI engineer courses:
Associate AI Engineer for Developers - datacamp.pxf.io/jRmdn6
Associate AI Engineer for Data Scientists - datacamp.pxf.io/PzbGrN
DataCamp - AI Fundamentals - datacamp.pxf.io/k4Wda3
This AI Engineering Roadmap for Beginners is a Realistic path to becoming properly ready for a job in this new AI industry! Want to learn to be an AI Engineer, check out the full roadmap https://roadmap.sh/ai-engineer
00:00 - Introduction - AI Roadmap
00:22 - Chapter 1 - AI Engineering Overview
00:48 - Chapter 2 - What is AI Engineering
01:26 - Chapter 3 - AI Job Market
01:55 - Chapter 4 - AI Engineer Roadmap Overview
02:34 - Chapter 5 - Python Programming
03:12 - Chapter 6 - AI Terminology - AGI LLM RAG DB
04:02 - Chapter 7 - How LLMs Work - Tokens Context Temp
04:56 - Chapter 8 - DataCamp AI Engineering Track
07:36 - Chapter 9 - Context Engineering
08:16 - Chapter 10 - Context Engineering - RAG
08:30 - Chapter 11 - Context Engineering - Context Compaction
09:03 - Chapter 12 - Context Engineering - Context Isolation
09:30 - Chapter 13 - Prompt Engineering - Zero Shot - Few Shot
10:07 - Chapter 14 - Prompt Engineering - Function Calling
10:38 - Chapter 15 - Prompt Engineering - Streaming Responses
11:08 - Chapter 16 - Prompt Engineering - System Prompting
11:32 - Chapter 17 - Prompt Engineering - Roles and Behaviours
11:50 - Chapter 18 - Prompt Engineering - Context and Constraints
12:09 - Chapter 19 - Prompt Engineering - Structured Outputs
12:26 - Chapter 20 - Types of Models
12:43 - Chapter 21 - Types of Models - Open / Closed Source
13:10 - Chapter 22 - Types of Models - Self Hosted Models
13:27 - Chapter 23 - Types of Models - Choosing the Right Model
14:18 - Chapter 24 - API and SDK
15:07 - Chapter 25 - Embedding Models
16:16 - Chapter 26 - Embedding Models - Vector Databases
16:54 - Chapter 27 - Embedding Models - RAG and Fine Tuning
17:35 - Chapter 28 - Model Context Protocol (MCP)
18:32 - Chapter 29 - Building MCP Servers and MCP Clients
19:03 - Chapter 30 - Security and Safety - Prompt Injection
19:51 - Chapter 31 - Multimodal AI
20:21 - Chapter 32 - AI Assisted Coding Tools - Cursor - Codex - Gemini
A big thanks to DataCamp for sponsoring todays videos, if you want to learn more about them, and their courses and material to learn all about AI, definitely check out the links above!
#ai #roadmap #datacamp
Want to learn web design? ⭐ Check out my course! ⭐
📘 Teach Me Design - Course: enhanceui.com
