Introduction to Machine Learning and Data Science
Offline, Online or hybrid
Learn from industry experts!
Get practical knowledge from those who successfully work in the industry.
Our curriculum specialists work on providing a program with a clear path and necessary theoretical information.
Postdoctoral Researcher at INFN
Machine Learning Engineer at AIBotics GmbH
ML engineer at Fimetech
Senior Machine Learning Researcher at Toptal
PHD in Aix-Marseille University
ML Engineer at Picsart
Researcher at ICRANet-Armenia
Senior Machine Learning Engineer at Krisp
Adjunct Lecturer at AUA
ML Engineer at Magical Labs
- Linear Algebra
- Mathematical analysis
- Theory of Probability and Statistics
- Օverview of Python syntax
- Conditions, Loops
- Introduction to OOP
- Model Selection
- Unsupervised Learning
- Introduction to Neural Networks and Deep Learning
Offline, online or hybrid
The quality of our courses is based on the structural organization of the lesson process: theoretical and practical lessons, homework, out-of-class communication with the lecturer.
During the lectures, students get theoretical knowledge, get acquainted with new technologies and working methodologies and discuss the materials.
During the seminars, the students implement the knowledge they received in the theoretical classes. The tutors provide individualized support to each student discussing the problems they encountered.
We are ready to provide comprehensive information about the courses, present their features and possible perspectives, and help you make a final decision. Throughout the admission and study process, the students will be in touch with the course coordinator.
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