Data Science

An intensive remote-friendly course prepared by employers for future employees.
Tailored to prepare mid-level specialists.

Next start date
01 Dec 2020
Addmissions deadline
11 Nov 2020

"Good data scientists are in huge demand. Turing College is a place to become one."

- Dovydas Čeilutka, Team Lead at Vinted

Ready to kickstart your career?

Fully remote studies

All classes are remote-friendly, and the training process takes place through our unique platform.

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Peer to peer learning

The Turing Platform groups students so they can code in teams, give peer reviews, and learn faster.

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Soft skills

Today’s students should focus on developing both hard and soft skills. These are critical for successful integration into any tech company.

Scholarships to become a team lead

For the top 10% of Turing College students who have potential to become team leaders, we have established a 300 € per month scholarship while studying. Additionally, these students will get exclusive mentorship from a senior team lead.

Job guarantee

Your future employers can’t wait to work with you. They want you to study fast and effectively. Our data-driven peer-to-peer learning environment is designed to satisfy the need for skilful data science professionals.

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Study pace

We expect students to finish the full-time program in 6 months and part-time in 9 months. Yet, these time frames are just benchmarks. If you dedicate more time, you can graduate faster. On the other hand, those who encounter difficulties and need a slower learning pace will be accommodated as well.

Duration
6 months
Format
Remote
Start date
01 Nov 2020
Admissions deadline
11 Oct 2020
Duration
9 months
Format
Remote
Start date
01 Dec 2020
Admissions deadline
11 Nov 2020

What will you learn?

6 month course

Data Science Fundamentals

Data Wrangling and Storytelling, Statistical Tests and Experiments, Linear Algebra.

Data Engineering

Software Engineering, SQL and Databases, Deploying Machine Learning Models.

Machine Learning

Linear Models, Tree-Based Models, Applied Modelling.

Deep Learning

Computer Vision, Natural Language Processing, Practical Deep Learning.

Team Specialization module

Participate in our in-house apprenticeship by building a real-world project in a small team.

Specialization module

Choose a real world project from a hiring partner's technological stack.

What will you get?

In a short period, you will get powerful skills to boost your career.

Python
Data visualization
Linear Algebra
Statistics & modeling
Team work
Soft skills
Databases
Machine learning

Suggested timetable

If you prefer to study on the weekends or at midnights, you would be able to do it.

Monday-Thursday
9:00 - 10:00
Introduction of the day
Personal time to investigate the day’s mini-project
10:00 - 13:00
Study-time on mini-project
Students start mini-projects, systemize questions
13:00 - 14:00
Lunch break
Instructors answer questions
14:00 - 16:00
Study-time on mini-project
Finishing mini-project, p2p learning session
16:10 - 17:00
P2P stand-up
Helping each other summarize the day’s topic before a minitest
17:00 - 17:30
Minitest
A test, which helps you reflect the level of knowledge you have acquired
17:30 - 18:00
Stand-up with instructor
Meeting a professional instructor in groups of 8, who will help you reflect the day’s progress and struggles
Friday
9:00 - 10:00
Introduction of the day
Personal time to investigate the day’s project
10:00 - 13:00
Study-time on project
Students start a project by applying knowledge from the mini-project, students systemize questions
13:00 - 14:00
Lunch break
Instructors answer questions
14:00 - 17:00
Study-time on project
Finishing project, p2p learning session
17:10 - 18:10
Global P2P assessment hours
Instructors are available for any project adjustments
18:10 - 18:40
Stand-up with instructor
Meeting a professional instructor in groups of 8, who will help you reflect the day’s progress and struggles
Monday-Friday
18:10 - 18:40
Stand-up with instructor
Meeting a professional instructor in groups of 8, who will help you reflect the day’s progress and struggles
2 hours
per day
Study-time on mini-project
Personal time to investigate the day’s mini-project, start working on it and systemize questions
1 hour
per day
Study-time on project
Finishing project, p2p learning session
Notes:
  • Learning should be done everyday: Monday to Friday, plus a full 6th day of your choice (Saturday or Sunday)

  • Part-time students can join stand-up sessions in the evenings with full-time students

  • Part-time students need to join stand-up upon finishing full-day’s mini-project

Prepared by market leaders

Machine learning team lead at Vinted, where he leads a team working on various machine learning projects. Dovydas is President of the Artificial Intelligence Association of Lithuania and a founder of Tribe of AI, an artificial intelligence learning community.

As CTO, Giedrius led ed-tech projects ranging from globally operating startups (Westudysmart) to market-leading platforms (EDUKA). Worked as a team lead web developer at Western Union and co-founded a web development agency Appmakers. Graduated University of Edinburgh with First class computer science award.

Co-Founder of Three Thirds and AI researcher. Marie Skłodowska-Curie postdoctoral fellow at KU Leuven (Belgium) and MIT (USA). Published by top machine learning venues.

Admission process

Although experience is not required, there’s a several-stage route to the college.

More about admissions
Application

Start with simple survey. Just fill the information out and send it to us.

Challenge

We will send you a task to test your technical programming knowledge.

Interview

We will ask you some questions so we can learn more about your personal traits.

Welcome

After the evaluation process, you will receive a decision. Congrats! You have made it!

Have questions?

Contact us

Enroll in our Data Science curriculum

Part-time applications will close in:
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Part-time course will start at December 1st, 2020, applications are available until November 11th, 2020. You can also join full-time waiting list.