Math402
Math Refresher for Masters
Faculty
Radoslav Neychev
Harbour.Space AI Track Director, Girafe-ai founder
Course length
Duration
Total hours
Credits
Language
Course type
Fee for single course
Fee for degree students
Skills you’ll learn
Overview
Understanding Machine Learning requires fundamental knowledge in mathematical areas such as linear algebra, calculus, optimization, probability and statistics. The Math Refresher course focuses, through practical examples and assignments, on revising the necessary topics that will allow students to join future Machine Learning courses and gain thorough knowledge about modern Artificial Intelligence.
Learning highlights
- Helping students acquire a solid foundation for key mathematical concepts
- Possibility to understand Machine Learning algorithms.
Course outline
10 classes
Session 1
Euclidean spaces
- Vectors. Scalar product. Norms, length and distances. Angles and Orthogonality.
Vector spaces
- Linear independence. (Orthogonal) basis. The dimensionality of a space.
Session 2
Matrices
- Matrix arithmetics. Determinant. Trace. Rank. Matrix norm. Matrix inverse.
Systems of linear equations
- Gaussian elimination. Linear regression.
Session 3
Matrix decomposition
- Eigenvalues and eigenvectorsPrincipal Components Analysis.
Linear Algebra Review & Exam
Session 4
Univariate functions
- Monotonicity. Convexity. Limit of a function.
Extrema of a function
- First and second derivatives. Chain rule. Extrema.
Session 5
Integration
Standard antiderivatives. Change of Variable and Integration by Parts. Definite Integral.
Session 6
Optimization
- Constrained Optimization and Lagrange Multipliers.
- Convex optimization.
Numerical optimization. Gradient Descent.
Session 7
Basic Probability
- (Conditional) probability and Independence. Bayes’ theorem.
Discrete Random variables
- Common discrete distributions and their properties.
Session 8
Random variables properties
- Expectation, variance, covariance and correlation.
Continuous Random variables
- Density. Common continuous distributions and their properties.
Session 9
Statistics
- Descriptive vs inferential statistics. Parameter estimation. Method of maximum likelihood
Session 10
Final Review & Exam
Prerequisites
Basic knowledge of Mathematics and Programming paradigms (e.g. Python basics)is required. Previous courses on Linear Algebra, Calculus, Optimization, Combinatorics or Probability and Statistics are appreciated.
Methodology
The course will consist of three-hour sessions and self-study practical assignments. The sessions will contain both theoretical and practical parts, with the ratio depending on the covered topics.
Grading
Radoslav Neychev is a data scientist with focus on Deep Learning and Reinforcement Learning techniques. He has worked on variety of research (CERN LHCb, MIPT Machine Intelligence Lab, CC RAS) and industrial projects (Yandex, RaiffeisenBank) in different domains vary from particle identification problem to fraudulent transactions detection.
Radoslav graduated from Moscow Institute of Physics and Technology, majoring in Applied Mathematics and Machine Learning. Radoslav is reading lectures and organising practical classes at Russian top-tier universities, tech companies and summer schools.
See full profileApply for this course
Math Refresher for Masters
by Radoslav Neychev
Total hours
30 Hours
Dates
Oct 18 - Oct 29, 2021
Fee for single course
€1000
Fee for degree students
€500
How to secure your spot
Complete the form below to kickstart your application
Schedule your Harbour.Space interview
If successful, get ready to join us on campus
FAQ
Will I receive a certificate after completion?
Yes. Upon completion of the course, you will receive a certificate signed by the director of the program your course belonged to.
Do I need a visa?
This depends on your case. Please check with the Spanish or Thai consulate in your country of residence about visa requirements. We will do our part to provide you with the necessary documents, such as the Certificate of Enrollment.
Can I get a discount?
Yes. The easiest way to enroll in a course at a discounted price is to register for multiple courses. Registering for multiple courses will reduce the cost per individual course. Please ask the Admissions Office for more information about the other kinds of discounts we offer and what you can do to receive one.