DS206
Introduction to Machine Learning
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
Machine Learning is revolutionizing our world right now: Recommendation systems, Dialog systems, Computer vision algorithms, autonomous vehicles and much more. It has a huge impact on all aspects of our lives and will achieve even more influence in the nearest future.
Modern Machine Learning systems can be very complicated. Their development may include choosing the right data processing algorithms, designing an appropriate model and training pipeline, building quality validation schemes.
In this course, we will give you a basic knowledge of Machine Learning - a foundation on top of which you will grow your knowledge and skills in this topic.
This introductory course gives students the skills to find and analyze potential Machine Learning problems and provides many simple yet effective methods to solve them.
After this course, you will know how to define and solve regression and classification problems with ML algorithms. You will understand where you should pay attention when building ML systems.
We will introduce you to the basics of neural networks and their applications.
Learning highlights
- Machine Learning: problem formulation, model building and evaluation.
- ML algorithms: linear models, naive bayes, KNN, decision trees and their compositions, basic statistical text processing, basic neural networks and basic unsupervised methods.
Course outline
15 classes
Session 1
Machine Learning applications overview. Naive Bayes classifier. kNN
Session 2
Linear regression
Session 3
Logistic regression
Session 4
Support Vector Machine. Principal Component Analysis. Validation strategies
Session 5
Decision trees and bagging
Session 6
Gradient boosting. Bias-Variance Tradeoff
Session 7
Midterm. Q & A
Session 8
Neural networks basics
Session 9
Optimization and regularization for neural networks
Session 10
Recurrent neural networks
Session 11
Convolutional neural networks
Session 12
Attention in neural networks
Session 13
Unsupervised learning
Session 14
Recommender systems
Session 15
Final exam
Prerequisites
Object-oriented programming in Python
Probability theory (basic)
Linear Algebra, Calculus (basic)
Statistics (basic)
Algorithms and data structures(basic)
Methodology
Our sessions consist of two parts: a lecture session with slides and theoretical materials followed by a practice session devoted to the discussed topic. The practice sessions will include programming tasks and interactive problem-solving on real-life examples. Throughout the course, multiple home assignments will enable students to get hands-on experience in implementing machine learning pipelines.
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
Introduction to Machine Learning
by Radoslav Neychev
Total hours
45 Hours
Dates
Jan 31 - Feb 18, 2022
Fee for single course
€1500
Fee for degree students
€750
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.