Mathematics

Essential Math for Data Science

15 Hours of crystallized conceptual program

Estimated Time

15 Hour(s)

Classroom Opens

Coming Soon

Level

intermediate

Description

This course is a primer introducing the learner to the rigor of data science and specially where and how is mathematics used in the field of data science.
The modules covered are : Linear Algebra to determine how algorithms work under the hood, Calculus to formulate the functions used to train algorithms to reach their objective and Statistics and Probability to analyze and visualize data.

Highlights

- •Demystify Vector Spaces
- •Master Essential Linear Algebra
- •Understand Polynomials
- •Get a head start in Functions
- •Work with Probability Distributions
- •Get Initiated in Calculus
- •Learn the concept of Prediction Errors
- •Learn to model a Data Science problem
- •Take a deep dive in Statistics
- •Conceptualize Multivariate Regression

Takeaway

•Develop a rigorous understanding of the principles of Data Science
•Get a head start in your preparation for a masters in Data Science
•Learn from some of the most accomplished Subject Matter Experts
•Allow yourself to talk sense in Interviews
•Give a boost to your Career

What You Will Learn?

MATHEMATICS FOR DATA SCIENCE

Vector Spaces

concept

1 Hour(s)

In-Class

Linear Algebra

concept

2 Hour(s)

In-Class

Functions and Polynomials

concept

1.5 Hour(s)

In-Class

Probability Distributions

concept

3 Hour(s)

In-Class

Introductory Calculus

concept

2 Hour(s)

In-Class

Modeling the Objective Function

concept

1.5 Hour(s)

In-Class

Error Minimization

concept

1 Hour(s)

In-Class

Statistical thinking

concept

2 Hour(s)

In-Class

Introduction to multivariate regression

concept

1 Hour(s)

In-Class

Language

english

Hours

15 Hour(s)

Level

intermediate

For who?

- others
- college-(UG)
- pg-college-(Graduate)
- corporate-employee

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