Start your journey into model deployment with foundational concepts and hands-on exercises designed for newcomers.
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
BeginnerIBM Data Science Professional Certificate
BeginnerML Model Deployment & MLOps with FastAPI, Streamlit, MLflow
AdvancedIntroduction to Regression with statsmodels in Python
IntermediateIntroduction to Linear Models and Matrix Algebra
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
BeginnerIBM Data Science Professional Certificate
BeginnerML Model Deployment & MLOps with FastAPI, Streamlit, MLflow
AdvancedIntroduction to Regression with statsmodels in Python
IntermediateIntroduction to Linear Models and Matrix Algebra
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
IBM Data Science Professional Certificate
Machine Learning Model Deployment
This course introduces you to regression analysis using the statsmodels library in Python. You'll learn how to build, interpret, and evaluate linear regression models.
This course provides a review of the basics of linear models and matrix algebra, which are foundational concepts for understanding regression methods.
Explore related content to expand your skills beyond this learning path.
Enroll in this path to track your progress and stay motivated.