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How to Become
a Data Scientist

Data science is a complex and intricate field. It is comprised of structuring and analyzing large-scale volumes of data, applying machine learning to make predictions, identifying patterns, and drawing conclusions. Data scientists are needed in business, manufacturing, and science. They work with such essential tools as Python and its libraries, including Scikit-Learn and XGBoost, Jupyter Notebook, and SQL. Our mission is to teach you how to use these tools.

Salary of a Data Scientist

Source: indeed

What You’ll Get

You will master the skills required to become a data scientist and build a portfolio of projects during the 8 months, 10 hour per week training course. Projects you will work on:

Predict traffic levels for Yandex.Navigator
Train an algorithm that predicts the severity of daily traffic jams.
Select an ad to display on an internet community page
If the community has multiple sponsors, you’ll want each user to see the ad they’re most likely to click on. Your algorithm will predict how likely each click is.
Predict available time slots for a courier
Train an algorithm for a courier service that predicts which time slots will be used on a particular day.

About Yandex

Yandex is one of the largest IT companies in Europe. We build intelligent products and services powered by machine learning all over the world.

Russia's leading search engine on mobile

According to Yandex.Radar

Russia’s leading music streaming service with over 2 million subscribers

According to Yandex.Music

World’s first and only profitable ride-hailing service

According to

Over 100 self-driving vehicles currently tested on public roads in the US, Russia, and Israel

According to

30 offices in 10 countries across the world

According to

Listed on the NASDAQ since 2011

According to

You will Study in a Unique Technological Environment

Full immersion in the world of IT involves constant exposure to industry technologies and using them to carry out hands-on projects while keeping in regular contact with your mentor. We've developed our own exclusive learning environment to help you do just that.


Interactive Online Platform

You'll start performing real-life tasks from day one. Information is given to you bit by bit, which you will apply immediately by writing your own code in our interactive platform.


Independent Work

The interactive platform is just one part of the overall learning process. You will acquire the essential skills while working on real-life projects using the same tools as professional developers.


Mentor Support

Our professional team of mentors will check and review your code, help you to overcome any difficulties and even give you the professional advice to help you succeed.

Who are Your Mentors?

They are experienced analysts from Yandex and other prominent IT companies. Some of them made careers in IT after leaving their previous jobs. Just like you, they had to start from the ground up.

Professional Certificate

The certificate is an official document that proves you completed professional training and is only issued upon passing your final project. It shows employers that you are competent in data analysis and personally completed all the projects in your portfolio.

Price Breakdown

Introductory Course —
$100            per month

You discover what data analysis is and find out what is the difference between data analysts and data scientists. You will then study the basics of Python, a key tool in this particular craft. After that you’ll know if you have the time and motivation to continue.
  • you will receive access to the first course on our interactive platform
  • a free 20 hours of skill and knowledge acquisition
  • and 1 research project based on real data

Paid Course —
$140 $100            per month

For 8 months of training

After completing the free portion of the course, you can then move ahead with your studying. From that point on, you can start mastering your new profession.
The paid course gives you:
  • full access to the interactive platform
  • a 300 hour-long professional course
  • mentor support
  • a professional certificate
  • skills and knowledge required by the industry
  • and a 17-project portfolio

Course structure


Python and Data Analysis Basics: Free Introductory Course

20 hours

The process and stages of the data scientist’s work — essential terms, methods, and tools of data analysis. Data preparation. Python programming language and its Pandas library. Jupyter development environment.

1 project for your portfolio


Data Preprocessing

20 hours

Learning how to deal with outliers, gaps, and duplicates while also converting different data formats.

1 project for your portfolio

Show entire program

Research Data Analysis


Statistical data analysis

20 hours

Learning how to use statistical methods to analyze relations in data. Finding out what statistical significance, hypotheses, and confidence intervals are.

2 projects for your portfolio


Introduction to machine learning

20 hours

Mastering the basics of machine learning. How the scikit-learn library works and how to use it in order to build your very first machine learning project.

1 project for your portfolio


Supervised learning (classification and regression)

20 hours

Diving into the most highly demanded area of machine learning: supervised learning. Understanding how to work with imbalanced data.

1 project for your portfolio


Machine Learning for Business

20 hours

Apply what you know about machine learning to meet the business needs. Discover business metrics, KPIs and A/B testing.

2 projects for your portfolio


Linear Algebra

20 hours

Taking a more in-depth look at some algorithms you’ve already learned and understanding how to apply them. Get a hands-on feel for the main concepts behind linear algebra: linear space, linear operators, and Euclidean space.

1 project for your portfolio


Numerical Methods and Algorithms

20 hours

Pulling apart a number of algorithms that use numerical methods and applying them to handle practical assignments. Learning about approximate calculation, evaluating algorithm complexity, and gradient descent.

1 project for your portfolio


Texts, Time Series, and Feature Engineering

20 hours

Learning about feature engineering as a whole, applying it to texts and time series. Learning how to vectorize texts using word2vec, GloVe, and fastText.

2 projects for your portfolio


Data Extraction

20 hours

Learning about main data storage systems: relational and distributed databases. Extract their data using requests written in SQL and methods from the PySpark library.

1 project for your portfolio


Computer Vision

20 hours

Learning how to handle simple computer vision jobs using premade neural networks and the Keras library. Briefly becoming acquainted with deep learning.

1 project for your portfolio

Hide program

Recommenders and Unsupervised Learning

20 hours

Learn about recommendation systems and build your own, not to mention diving into a number of unsupervised learning tasks.

2 projects for your portfolio


Start Your Free Course

Try your hand at data science and learn the basics of it.

Is this the career for me?
This is exactly what our free course will help you decide. Work your way through 20 hours of free material if you’re still not sure whether this profession is for you.
Is it possible to get a new profession in 8 месяцев?
We believe so, assuming that you dedicate no less than 10 hours a week to studying, completing assignments on time, and keeping in touch with your mentor. In 8 месяцев you will acquire the necessary skills, put a portfolio together, and start a new career.
How do I start?
All you need is high school education and a willingness to study at least 10 hours a week.
Who will teach me?
The course is put together by experienced educators, methodologists, and professionals from Yandex, School of Data Analysis, and other professionals at the forefront of the IT industry.
How is studying arranged?
There are three main components — theoretical breakdown followed by practical tasks on our interactive online platform, assignments to practice on your own, and coding under your mentor's supervision. You can practice on our platform at any time that is convenient for you, but assignment completion is time-restricted.
What if I can't keep up with the workload?
If during the course you realize that you need to take a break or get some extra time to practice, you can take a month-long academic leave. Our program's schedule also includes two-week-long study breaks.
Will I be able to find work when I'm done?
You will, but it won't be easy. The market needs skills in addition to knowledge. We'll teach you how to apply knowledge and help you build a portfolio of practical projects, but making a name for yourself takes a lot of work. In the end, the more projects there are in your portfolio, the better your chances are of landing a job at a reputable company.
How will you help me get a job?
At Practicum, we strive to help you reach your full professional and personal potential, which is why we've developed a two-step support system for our graduates. First, we offer an optional career prep course where you have to complete weekly assignments aimed at helping you speak the same language as your employers. During the course, you will study and practice networking, as well as learn job interview techniques and work on perfecting your resume and portfolio. Secondly, we will share our researched market insights that will help you choose the right career path. After you complete the course, our staff will guide you through current job opportunities and help you better grasp the situation through networking and resume sourcing. Should you have any particular issues getting hired, you will receive personal help. Please note that help with finding a job can only be given to those who are eligible to work in the US.
Can I get my money back if I'm not satisfied?
The short answer is yes, whenever you want. Of course, if you've already gone through some of the course, you will only receive your money back for the uncompleted part. You can read about this in more detail in our terms and conditions.