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Statistics & Math for ML
Learn Linear Algebra from Scratch
Master Linear Algebra with hands-on projects and real-world examples
By Deepak Joshi
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0.0
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Intermediate
English
0 learners
What you'll learn
- Understand the core concepts of Linear Algebra and how they fit together
- Build hands-on projects using Linear Algebra that you can add to your portfolio
- Apply Linear Algebra to solve real, practical problems in Data Science & AI
- Follow industry best practices and avoid common Linear Algebra mistakes
- Gain the confidence to use Linear Algebra at work and in interviews
Skills you'll gain
Linear Algebra
Practical Projects
Debugging
Best Practices
Problem Solving
Statistics & Math for ML
About this course
Learn Linear Algebra the practical way. This Data Science & AI course focuses on doing: you'll work through real examples in Statistics & Math for ML, understand the why behind each technique, and finish with projects for your portfolio. Deepak Joshi keeps things clear and example-led, so you build genuine, transferable skill. By the end you'll be ready to use Linear Algebra confidently at work and in interviews.
Curriculum
Getting Started
- Welcome and what you'll build video · 10:00 ▶ Free preview
- Linear Algebra in 10 minutes video · 11:00 ▶ Free preview
- Your first Linear Algebra walkthrough video · 12:00
- Hands-on exercise video · 13:00
Core Concepts
- Common patterns in practice video · 17:00
- Building the project — part 1 video · 06:00
- Debugging and troubleshooting video · 07:00
- Performance and optimisation video · 08:00
- Testing your work video · 09:00
Hands-On Practice
- Performance and optimisation video · 12:00
- Testing your work video · 13:00
- Welcome and what you'll build video · 14:00
Building Real Projects
- Welcome and what you'll build video · 07:00
- Linear Algebra in 10 minutes video · 08:00
- Your first Linear Algebra walkthrough video · 09:00
- Hands-on exercise video · 10:00
Going Deeper
- Common patterns in practice video · 14:00
- Building the project — part 1 video · 15:00
- Debugging and troubleshooting video · 16:00
- Performance and optimisation video · 17:00
- Testing your work video · 06:00