FAQ

How does the application process work?
The application process consists of three steps. First, candidates apply online through our website. Second stage is an online test. The test assesses analytical and basic programming skills and contains undergraduate level statistics and probability questions, data analysis questions, and short coding challenges (candidates can select from few popular programming languages that our platform supports). The test must be completed within three and a half hours.
Y-DATA will offer two separate 4 day time windows to take the online test during July.Test results will be sent to candidates by 20.8.2019. Candidates who pass the online test will be invited to an in-person interview with Y-DATA team members. The interview is an opportunity for our team to learn more about candidates' background, experiences, and interests.
What is the time commitment for this program? Can I combine it with working or academic studies?
The weekly workload consists of 8 hours of frontal lessons (one mid-week evening + Friday morning) and approximately 15-20 hours of independent work on assignments and projects. We expect at least 80% attendance at lectures and seminars.
Due to the workload, we require our participants to have at least one full weekday available for the coursework in addition to the 8 hours of frontal lectures. Therefore, candidates are required to reduce full-time positions to 80% at most, and strongly recommend reduction to 50% for the program's duration.
Participating in the program while working towards an academic degree is possible but depends greatly on the intensity of individual programs.
Is there a way I can take part in the program if I'm working full time and can't reduce my position?
It's possible, but depends greatly on your commitment.
In our experience, it is extremely difficult to combine the workload of Y-DATA with a full time employment. We strongly recommend all our candidates to reduce their positions in order to fully utilize the opportunities offered by Y-DATA.
On top of that, attendance of at least 80% in lectures and seminars is mandatory (one weekday evening and Friday morning), with weekly classwork and exercises requiring significant amount of time and effort.
If you believe you can combine this workload with a full-time employment, we offer a possibility to take the Y-DATA program without taking part in an Industry Project. In this case, you are still required to take all the courses and complete all the classwork as described, but without the additional workload of the industry project.
What level of math knowledge is expected from the candidates?
We assume our students have at least a bachelor STEM degree or its equivalent. We therefore expect all candidates to have full knowledge of first-year university level material in math. In order to ensure suitable level of pre-existing knowledge, we require all candidates to complete the Mathematics for Machine Learning specialisation on Coursera prior to the beginning of their studies.
Candidates who are accepted to the program will be have the cost of the course deducted from their tuition fee.
What level of statistics and probability knowledge is expected from the candidates?
We assume our students have at least a bachelor STEM degree or its equivalent. We therefore expect all candidates to have full knowledge of first-year university level material in probability and statistics. You may want to review basic topics in those subjects before taking our online test.
During the program we won’t teach these topics from scratch, but we will provide a quick recap before diving into the more advanced topics required for later ML courses.
What level of coding skills is required to enter the program? Can I apply with zero coding experience?
We request some experience in at least one of the common programming languages and an understanding of common data structures. Programming tasks are a large portion of the online test, and assume existing programming background.
Candidates without any coding experience won’t be able to take part in our program. You may want to try completing a couple of beginner level online Python courses before applying to our program.
We recommend candidates to have a working knowledge of Python before starting the course, but the online test may also be done in Java and C++.
Can you provide more details about the online test? What should I do to prepare?
Full details regarding the exam's format and platform will be provided to applicants a week before each exam window.
The time windows for the exam are:
  1. July 3rd 8:00am - July 7th 8:00am
  2. July 31st 8:00am - August 4th 8:00am
Here you can practice on a previous year exam and understand better what kind of questions to expect. No time limit for this sample test. This year's exam will be similar in style and structure.
Besides sample test, we recommend to brush up your coding skills if you don't write code daily. If you'd like to sharpen your Python skills, some good sources are:
You can also refresh your knowledge of statistics and probability, especially if it's been a while since you've used them in practice. Some relevant sources are:
  • Probability by A.N.Shirayev
  • Probability courses on EDX - PurdueX courses (416.1x and 416.2x) cover basic topics well, as well as Data Science: Probability from HarvardX (PH125.3x)
While we don't test directly for math knowledge in the test, we expect all our candidates to have full knowledge of first-year university level material in math. We require all candidates to complete the Mathematics for Machine Learning specialization on Coursera prior to the beginning of their studies. Candidates who successfully passed the online test will be required to complete the specialization during months September-October but if you feel you require more time for this refresher, we recommend to start it on your own time and pace. Cost of this specialization (one month) will be reduced from Y-DATA fee for accepted candidates.
Do I get a certificate at the end of Y-DATA program? What are the conditions for getting it?
Yes, you get a certificate of completion. To get the certificate you should earn sufficient amount of credits and complete all the required coursework (you’ll get instructions for each semester).
During the course of the first semester, at the end of each course there will be an exam, and a passing grade is mandatory in order to advance to the latter courses and the 2nd semester.
Is this program similar to the other Yandex School of Data Analysis branches?
No. The program is different in scope, duration and its final goals.
The program agenda looks very dense, touching almost all aspects of modern machine learning. Is it really feasible to explore all these topics in sufficient depth and gain a working understanding of them?
In order to provide a comprehensive program with elaborate cross-course connections, we thoughtfully designed assignments and a minimum of excess theory. This enables the program to avoid repeating information across multiple courses and to create more time for additional practice.