Mathematics for Data Science: Essential Mathematics for Machine Learning and AI
- Offered byFutureLearn
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI at FutureLearn Overview
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI
at FutureLearn
Duration | 4 weeks |
Total fee | ₹900 |
Mode of learning | Online |
Credential | Certificate |
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI at FutureLearn Highlights
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI
at FutureLearn
- Duration 4 weeks
- Weekly study 5 hours
- Included in an ExpertTrack Course 4 of 5
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI at FutureLearn Course details
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI
at FutureLearn
Skills you will learn
More about this course
- A solid foundation in mathematical knowledge is vital for the development of artificial intelligence (AI) systems. What are the key maths skills required to study machine learning and AI?
- If you haven't studied mathematics since school and have forgotten what you've learned, this primer course will provide you with the education you need.
- The course will cover the three main branches of mathematics used in data science and artificial intelligence: linear algebra, calculus and probability. You'll get to learn the essential topics of each of these three areas - from equations, functions and graphs to differentiation and optimization and vectors and matrices.
- Having mastered these concepts and techniques, you'll have the foundational knowledge to kickstart your machine learning career.
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI at FutureLearn Curriculum
Mathematics for Data Science: Essential Mathematics for Machine Learning and AI
at FutureLearn
Course Introduction
About this Course
Algebra Fundamentals
Exponents and Polynomials
Factorisation, Quadratic Equations and Functions
Wrapping Up the Week
Differential Calculus
Differential Calculus Foundations
Derivatives
Differentiation
Wrapping Up the Week
Vectors and Matrices
Vectors
Matrices
Matrix Transformations
Wrapping Up the Week
Statistics and Probability
Visualising Data
Central Tendencies
Probability
Confidence Intervals and Hypothesis Testing
Wrap Up and Course Completion
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