By the end of this course, you will be able to
Understand the basics of probability including joint probability, conditional probability, and Bayes' rule.
Determine the use of random variables, distribution, and first-order statistics, and get a simple idea of the values of p, t, and z.
Explain the advantages of Linear algebra tools including vectors, matrices, and their operations.
Course details
- 1 h 48 m/17 lessons
- Last updated: 27/10/2022
- Course completion certificate
Course Content
Definition of Probability
Joint Probability
Definition of Probability
Joint Probability
Independent Events
Conditional Probability
Bayes Rule 1
Bayes Rule 2
Random Variable
Normal Distribution
Mean
Variance
Covariance
P-Value
How to Calculate the P-value
Exercises
Linear Algebra
Vectors
Questions
About this course
This level introduces the mathematical foundations behind data science techniques. It also focuses on probability theory and its applications and covers the basics of linear algebra.
Course requirements and prerequisites
- Graduate of any university (Engineering is not mandatory)
- Previous programming experience of any language is a big plus
- Knowledge of Linear algebra is a big plus
Mentor
Sherif Gamal
Engineer and Senior Member of IEEE
3,135 Learners
5 Courses
