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Statistics & Math for ML
Practical Calculus for ML for Beginners
Go from fundamentals to job-ready Calculus for ML skills
By Nikhil Jain
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Intermediate
English
0 learners
What you'll learn
- Understand the core concepts of Calculus for ML and how they fit together
- Build hands-on projects using Calculus for ML that you can add to your portfolio
- Apply Calculus for ML to solve real, practical problems in Data Science & AI
- Follow industry best practices and avoid common Calculus for ML mistakes
- Gain the confidence to use Calculus for ML at work and in interviews
Skills you'll gain
Calculus for ML
Practical Projects
Debugging
Best Practices
Problem Solving
Statistics & Math for ML
About this course
This course is a hands-on, project-driven introduction to Calculus for ML, part of our Data Science & AI track. Designed for learners in India and beyond, every concept is taught with practical examples and exercises you can add to your portfolio. Taught by Nikhil Jain, it starts from the fundamentals and builds toward real-world, job-ready skills in Statistics & Math for ML. By the end you'll have the confidence to apply Calculus for ML at work, in interviews, and on Hyrespot-matched roles.
Curriculum
Getting Started
- Welcome and what you'll build video · 10:00 ▶ Free preview
- Calculus for ML in 10 minutes video · 11:00 ▶ Free preview
- Your first Calculus for ML 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
- Calculus for ML in 10 minutes video · 08:00
- Your first Calculus for ML 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