Beeline Data School, on the Neva
Hello, Habr! You have already heard more than once that we conduct machine learning and data analysis courses at the Beeline Data School . Today we are celebrating the 6th issue on our analytical course and the 4th on the course for managers . Just having managed to graduate one course, we recruit a new one. After each next release, we collect feedback from our students, analyze it and make our program even more saturated with practice and examples from real business.
They write to us from all over the country and from beyond its borders with questions when the Data School will appear in their city. We have responded to these wishes and are expanding our presence.
Today we are pleased to announce the launch of our program in St. Petersburg! We gathered the best teachers in this glorious city, prepared a wonderful program and in this post we will tell you all the details of the training.
The course starts on October 28th and will take place on Mondays and Fridays in the evening from 19.00 to 21.00 in the Beeline company office at 21 Vasilievsky Island, line 6, letter A (the nearest metro station is Vasileostrovskaya).
There are 18 lessons ahead of us (the course is designed for 9 weeks), at which we will try to cover the most important topics of data analysis.
A distinctive feature of our classes is their practical orientation.
Our country has always been famous for its mathematics school, and today there are already many people who can build high-quality models win Kaggle competitions. But over the course of our practice, we have repeatedly seen that this is not enough to make ready-made products that can bring business measurable financial benefits.
It is important to have an idea of product metrics, it is important to know about the algorithm development process, how often and how to retrain models correctly, and much more. Therefore, in our courses, we devote a lot of time to analyzing pitfalls, various "rakes" and all that can be encountered on the way to the implementation of a finished analytical product.
Our program consists of an important section of data analysis, such as Machine Learning, which is about a third of our course. Next, we introduce students to the most popular areas of data analysis - “Analysis of social networks”, “Recommender systems”, “Text analysis”, “Big data”, “Large Scale Machine Learning”, and finally we talk about the best algorithms that were winners at Kaggle - in particular, we discuss stacking / blending approaches, ensembles and much more.
You can read more about the course on the main page , but for now we would like to introduce you to some of our teachers:
Sergey Nikolenko
Specialist in the theory and practice of machine learning, in particular word processing, big data analysis, Bayesian methods and models. Senior Researcher, Laboratory for Internet Research, HSE St. Petersburg, Researcher, POMI RAS, Leading Specialist, Deloitte Analytics Institute.
He is the author of more than one hundred scientific publications on machine learning, analysis of network algorithms, complexity theory and higher algebra, the author of several scientific monographs.
Andrey Filchenko
Candidate of physico-mathematical sciences, associate professor of the computer technology department, head of the machine learning group in the international computer technology laboratory of ITMO University. Lecturer in machine learning and data analysis courses. Previously, a researcher at the Laboratory of Interdisciplinary and Theoretical Studies of SPIIRAS. Organizer of a series of conferences on data analysis and machine learning.
He graduated from the Faculty of Mathematics and Mechanics of St. Petersburg State University.
Natalya Pritykovskaya
Data mining developer at Odnoklassniki, previously worked as a data analysis specialist at AdRiver and Yandex.
Natalya graduated from the Faculty of Mathematics of St. Petersburg State University with a degree in Statistical Modeling, as well as Computer Science Center (Yandex ShAD Department in St. Petersburg).
Ivan Drokin
Currently, he takes part in the implementation of a number of projects related to in-depth training and analysis of images and video stream. Previously, a leading specialist in data analysis at CJSC BIOCAD and a leading specialist in the closed hedge fund Finance Dialog.
He graduated from St. Petersburg State University with a degree in Applied Mathematics and Computer Science, graduate school in the field of System Analysis, Management and Information Processing, is preparing to defend a dissertation for the degree of candidate of physical sciences in deep education.
Clement Merzlyakov
Analyst at NAO Yulmart. Data Analysis Consultant for Alol and Paradox Brewery. Clement graduated from St. Petersburg State University, as well as DM Labs. Participant in analytics conferences.
Evgeny Putin
Engaged in neural networks. He worked at Kaspersky Lab, Samsung, Siemens. He graduated from St. Petersburg State University in 2014.
Our teachers are people who are engaged in practical data analysis every day and have extensive experience in applying it in real work.
You can learn more about the School and register for the course on our page.
See you in the classroom!