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Want to study machine learning, but worried that your math skills may not be up to it? Do words like “algebra’ and “calculus” fill you with dread? Has it been long since you studied math at school that you’ve forgotten much of what you learned in the first place? The course provides a hands-on approach to working with data and applying the techniques you’ve learned.


This course does not involve any written exams. Students need to answer 5 assignment questions to complete the course, the answers will be in the form of written work in pdf or word. Students can write the answers in their own time. Each answer needs to be 200 words (1 Page). Once the answers are submitted, the tutor will check and assess the work.


Edukite courses are free to study. To successfully complete a course you must submit all the assignment of the course as part of the assessment. Upon successful completion of a course, you can choose to make your achievement formal by obtaining your Certificate at a cost of £49. Having an Official Edukite Certification is a great way to celebrate and share your success. You can:

  • Add the certificate to your CV or resume and brighten up your career
  • Show it to prove your success


Course Credit:  Microsoft 

Course Curriculum

module :1
Welcome 00:01:00
Preparing for the Labs 00:03:00
Getting Started with Equations 00:02:00
The Distributive Property 00:01:00
Introduction to Linear Equations 00:01:00
Intercepts and Slope 00:03:00
Systems of Equations 00:00:00
Exponentials, Radicals, and Logarithms 00:03:00
Polynomials 00:01:00
Polynomial Operations 00:04:00
Factorization 00:03:00
Factoring Squares 00:03:00
module :2
Introduction to Quadratic Equations 00:02:00
Functions 00:02:00
Rates of Change 00:02:00
Introduction to Limits 00:02:00
Continuity 00:01:00
Finding Limits 00:04:00
Introduction to Differentiation 00:03:00
Differentiability 00:01:00
Derivative Rules and Operations 00:03:00
Using Derivatives to Analyze Functions 00:05:00
Second Order Derivatives 00:03:00
Optimizing Functions 00:02:00
Multivariate Differentiation 00:02:00
Introduction to Integration 00:01:00
module :3
Introduction to Vectors 00:04:00
Vector Addition 00:01:00
Vector Multiplication 00:02:00
Introduction to Matrices 00:01:00
Matrix Mulitplication 00:01:00
Identity Matrices 00:33:00
Matrix “Division” 00:03:00
Solving Systems of Equations with Matrices 00:01:00
Matrix Transformations 555 00:01:00
Eigenvalues and Eigenvectors 00:02:00
Data 00:02:00
module :4
Visualizing Data 00:02:00
Measures of Central Tendency 00:04:00
Measures of Variance 00:04:00
Comparing Data 00:02:00
Probability Basics 00:02:00
Conditional Probability and Dependence 00:07:00
Binomial Variables and Distributions 00:05:00
Sample and Sampling Distributions 00:02:00
Confidence Intervals 00:02:00
Hypothesis Testing 00:04:00
Submit Your Assignment 00:00:00
Certification 00:00:00

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