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Machine Learning
Master scikit-learn in 2026
Master scikit-learn with hands-on projects and real-world examples
By Tara Krishnan
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Intermediate
English
0 learners
What you'll learn
- Understand the core concepts of scikit-learn and how they fit together
- Build hands-on projects using scikit-learn that you can add to your portfolio
- Apply scikit-learn to solve real, practical problems in Data Science & AI
- Follow industry best practices and avoid common scikit-learn mistakes
- Gain the confidence to use scikit-learn at work and in interviews
Skills you'll gain
scikit-learn
Practical Projects
Debugging
Best Practices
Problem Solving
Machine Learning
About this course
scikit-learn is one of the most useful skills in Data Science & AI today, and this course makes it approachable and practical. Through guided projects in Machine Learning, you'll build real understanding rather than memorising steps. Created by Tara Krishnan, the course pairs clear explanations with hands-on practice so the ideas stick. You'll come away able to apply scikit-learn to your own work and on job-relevant, Hyrespot-matched roles.
Curriculum
Getting Started
- Welcome and what you'll build video · 16:00 ▶ Free preview
- scikit-learn in 10 minutes video · 17:00 ▶ Free preview
- Your first scikit-learn walkthrough video · 06:00
- Hands-on exercise video · 07:00
Core Concepts
- Common patterns in practice video · 11:00
- Building the project — part 1 video · 12:00
- Debugging and troubleshooting video · 13:00
- Performance and optimisation video · 14:00
- Testing your work video · 15:00
Hands-On Practice
- Performance and optimisation video · 06:00
- Testing your work video · 07:00
- Welcome and what you'll build video · 08:00
Building Real Projects
- Welcome and what you'll build video · 13:00
- scikit-learn in 10 minutes video · 14:00
- Your first scikit-learn walkthrough video · 15:00
- Hands-on exercise video · 16:00
Going Deeper
- Common patterns in practice video · 08:00
- Building the project — part 1 video · 09:00
- Debugging and troubleshooting video · 10:00
- Performance and optimisation video · 11:00
- Testing your work video · 12:00