Probability Crash Course
Data Science & AI › Statistics & Math for ML

Probability Crash Course

A practical, project-based path to Probability in Statistics & Math for ML

By Rohan Kapoor ★ 0.0 (0 ratings) Intermediate English 0 learners

What you'll learn

  • Understand the core concepts of Probability and how they fit together
  • Build hands-on projects using Probability that you can add to your portfolio
  • Apply Probability to solve real, practical problems in Data Science & AI
  • Follow industry best practices and avoid common Probability mistakes
  • Gain the confidence to use Probability at work and in interviews

Skills you'll gain

Probability Practical Projects Debugging Best Practices Problem Solving Statistics & Math for ML

About this course

Learn Probability 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. Rohan Kapoor keeps things clear and example-led, so you build genuine, transferable skill. By the end you'll be ready to use Probability confidently at work and in interviews.

Curriculum

Getting Started

  • Welcome and what you'll build video · 13:00 ▶ Free preview
  • Probability in 10 minutes video · 14:00 ▶ Free preview
  • Your first Probability walkthrough video · 15:00
  • Hands-on exercise video · 16:00

Core Concepts

  • 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

Hands-On Practice

  • Performance and optimisation video · 15:00
  • Testing your work video · 16:00
  • Welcome and what you'll build video · 17:00

Building Real Projects

  • Welcome and what you'll build video · 10:00
  • Probability in 10 minutes video · 11:00
  • Your first Probability walkthrough video · 12:00
  • Hands-on exercise video · 13:00

Going Deeper

  • 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