Admission

The application process consists of three steps. First, candidates apply online through our website. Second, candidates take 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 a 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-August. 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.

We assume our students have at least a bachelor's STEM degree or its equivalent.

We, therefore, expect all the candidates to have full knowledge of the first-year university-level material in math. In order to ensure a suitable level of pre-existing knowledge, we require all candidates to complete the Mathematics for Machine Learning specialization on Coursera prior to the beginning of their studies.

Candidates who are accepted to the program will have the cost of the course deducted from their tuition fee.

We assume our students have at least a bachelor's STEM degree or its equivalent.

We, therefore, expect all the candidates to have full knowledge of the 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.

We require 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. During the program itself, the courses and home assignments will be in Python.

Candidates should have a basic knowledge of Python before taking the test. Some potential resources for people with no prior Python knowledge to get started include:

• Programming for Everybody (Getting Started with Python)
• Python Data Structures
• Python Essential Training

The test takes place in several time-windows over July and August - the exact dates will be announced about a month ahead of time. Full details regarding the exam's format, schedule and platform will be provided to applicants shortly before the test.

We publish past years' exams to candidates which you can use for practice and to better understand what kind of questions to expect - this year’s exam will be similar in style and structure. The sample test has no limit on time or number of attempts (while the real exam has a limit of 3.5 hours and can only be taken once).

Beside the sample test, if you don't write code daily, we recommend brushing up on your coding skills. If you'd like to sharpen your Python skills, some good sources are:

• Python for Data Analysis by Wes McKinney
• From Python to Numpy
• PyData channel on YouTube
• Programming for Everybody (Getting Started with Python)
• Python Data Structures
• Python Essential Training