# This article was written by Swati Kashyap. Swati is a data science & analytics enthusiast. Currently,she is learning data science at Analytics Vidhya.

Mathematics & Statistics are the founding steps for data science and machine learning. Most of the successful data scientists I know of, come from one of these areas – computer science, applied mathematics & statistics or economics. If you wish to excel in data science, you must have a good understanding of basic algebra and statistics.

However, learning Maths for people not having background in mathematics can be intimidating. First, you have to identify what to study and what not. The list can include Linear Algebra, calculus, probability, statistics, discrete mathematics, regression, optimization and many more topics. What do you do? How deep to you want to get in each of these topics? It is very difficult to navigate through this by yourself.

If you have faced this situation before – don’t worry! You are at the right place now. I have done the hard work for you. Here is a list of popular open courses on Maths for Data science from Coursera, edX, Udemy and Udacity. The list has been carefully curated to give you a structured path to teach you the required concepts of mathematics used in data science. Which course is suitable for you?

To help you navigate through the courses, I have divided the article into beginners, intermediate and advanced section. Choose your level of expertise in mathematics before delving further. Further, I have added the pre-requisites for each course. You can check if you know these topics before starting the course.

Few courses may require you to finish the preceding course for better understanding. So, make sure that you either know the subject or have undergone these courses.

Read on to find out the right course for you!

Beginners Mathematics / Statistics

• Data Science Maths Skills
• Intro to Descriptive Statistics
• Intro to Inferential Statistics
• Introduction to Probability and Data
• Math is Everywhere: Applications of Finite Math
• Probability: Basic Concepts & Discrete Random Variables
• Mathematical Biostatistics Boot Camp 1
• Applications of Linear Algebra Part 1
• Introduction to Mathematical Thinking

Intermediate Mathematics / Statistics

• Bayesian Statistics: From Concept to Data Analysis
• Game Theory 1
• Game Theory II: Advanced Applications
• Advanced Linear Models for Data Science 1: Least Squares
• Advanced Linear Models for Data Science 2: Statistical Linear Models
• Introduction to Linear Models and Matrix Algebra
• Maths in Sports

• Discrete Optimization
• Statistics for Genomic Data Science
• Biostatistics for Big Data Applications

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