Intermediate
Certificate included
English
Machine Learning A-Z: Foundations to Deployment
From core ML concepts to deploying models in production
by Priya Sharma
About this course
This course covers the full machine learning workflow - from understanding core algorithms to training, evaluating, and deploying models. Every concept is paired with a hands-on exercise using real datasets.
What you'll learn
- Understand core machine learning algorithms
- Train and evaluate models with scikit-learn
- Handle feature engineering and data preprocessing
- Avoid common pitfalls like overfitting
- Deploy a trained model as an API
Requirements
- Working knowledge of Python
- Basic understanding of statistics is helpful
Curriculum
4 sections • 12 lessonsA quick orientation before diving into Machine Learning A-Z: Foundations to Deployment.
Course Introduction and Roadmap
Preview
7:00
Setting Up Your Environment
Preview
9:00
How This Course Works
The main skills you will build in this course.
Understand core machine learning algorithms
10:00
Train and evaluate models with scikit-learn
11:00
Handle feature engineering and data preprocessing
12:00
Avoid common pitfalls like overfitting
13:00
Deploy a trained model as an API
14:00
Apply what you learned to realistic exercises.
Guided Project: Machine Learning A-Z: Foundations to Deployment
15:00
Independent Challenge Exercise
Course Recap and Next Steps
6:00
Final Assessment and Certificate
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ETB 64.99 ETB 94.99
Sign Up to Enroll - Intermediate level
- 33h total
- Certificate of completion
- Full lifetime access
