Technology
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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