Start your journey into ml deployment with foundational concepts and hands-on exercises designed for newcomers.
Start now · step 1 of 7
Not required
Basic programming; comfort with command line
Google’s AI Course for Beginners (in 10 minutes)!
BeginnerHow I'd learn ML in 2025 (if I could start over)
BeginnerNatural Language Processing In 10 Minutes | NLP Tutorial For Beginners | NLP Training | Simplilearn
BeginnerMachine Learning - StatQuest
BeginnerMachine Learning Crash Course - Google Developers
BeginnerMachine Learning by Andrew Ng
BeginnerGetting Started with Stable Diffusion in 2024 for Absolute Beginners
BeginnerGoogle’s AI Course for Beginners (in 10 minutes)!
BeginnerHow I'd learn ML in 2025 (if I could start over)
BeginnerNatural Language Processing In 10 Minutes | NLP Tutorial For Beginners | NLP Training | Simplilearn
BeginnerMachine Learning - StatQuest
BeginnerMachine Learning Crash Course - Google Developers
BeginnerMachine Learning by Andrew Ng
BeginnerGetting Started with Stable Diffusion in 2024 for Absolute Beginners
BeginnerFollow these courses in order to complete the learning path. Click on any course to enroll.
Google’s AI Course for Beginners (in 10 minutes)!
Learn How I'd learn ML in 2025 (if I could start over)
Natural Language Processing In 10 Minutes | NLP Tutorial For Beginners | NLP Training | Simplilearn
Clear and simple explanations of machine learning algorithms. Understand the math and intuition behind ML with Josh Starmer.
Google's fast-paced, practical introduction to machine learning. A self-study guide for aspiring machine learning practitioners.
The original Stanford ML course taught by Andrew Ng
Getting Started with Stable Diffusion in 2024 for Absolute Beginners
Explore related content to expand your skills beyond this learning path.
Start your journey into ml deployment with foundational concepts and hands-on exercises designed for newcomers.
You'll work through Understand core concepts and foundations; Build your first projects with guided tutorials; Gain confidence with hands-on exercises; Design and implement ML pipelines; Version control data and models effectively; Automate model training and deployment.
About 26 hours of study across 7 courses — and you can go at your own pace.
It's pitched at beginner level — a solid starting point if you're new to the topic.
7 curated courses, sequenced from foundational to advanced.
The courses in this path can be started for free.
Enroll in this path to track your progress and stay motivated.