Applied Data Science Course

Become a Data Scientist in 6 months, taught over weekends


  • 03 February 2018 Apply now
  • In-person training, London
  • 6 month, part-time course

About

Applied Data Science is an intensive, part-time course designed to equip you with the most relevant Data Science skills matching industry needs through a combination of hands-on training, independent learning and collaborative projects.

In this course you will:

  • Attend 10 intensive in-person training weekends
  • Build a professional portfolio completing projects on real-world data
  • Complete an end-to-end industry sponsored project
  • Earn industry recognised certification
  • Receive 1-on-1 mentorship from experts

To receive further information about our course curriculum and advisory board

Request course outline

What you will learn

  • Weeks 01-02 Essentials of Computer Science, Probability and Statistics
  • Weeks 03-04 EDA, Feature Engineering and Unsupervised Learning
  • Weeks 05-06 Supervised and Semi-Supervised Learning, Training and Validation
  • Weeks 07-08 Regression Models and Time Series
  • Weeks 09-10 Ensemble Models and Support Vector Classifiers
  • Weeks 11-12 Cloud Computing and Databases
  • Weeks 13-14 Big Data Systems
  • Weeks 15-16 Neural Networks and Deep Learning
  • Weeks 17-18 Natural Language Processing

Course Breakdown

155+ hours live tuition and support

Our on-site weekends include specialist lectures, hands-on activities and regular opportunities to present your work, discuss your findings and receive feedback.

300+ hours completing projects with a team of fellow students

Between each training weekend, you will receive a range of self-guided research tasks and project-based assignments to work on collaboratively.

90+ hours contributing to a real-world problem

After completing the nine modules, you will work independently on an end-to-end project sponsored by the Cambridge Judge Business School.


Why attend?

Gain hands on experience working on industry-sponsored data science problems

Get exposure to the latest tools, techniques and industry best practices

Develop the essential reasoning and communication skills to explain your methods

Build your professional network and attend alumni events in London, Cambridge and Oxford

Enjoy a blend of flexible self-directed learning and in-person training weekends

Gain the most relevant qualification to join a Data Science team and hit the ground running


Our curriculum advisory board


Prerequisites

  • Elementary Python programming and use of the command line. You can acquire these skills at our Python bootcamp.
  • Basic probability and linear algebra.

Audience

Individuals who want to master new technical skills and learn the latest techniques and industry best practices to work effectively with Data Science teams.


Pricing

Professional Development Track

Master new Data Science skills
Attend intensive training weekends, get mentored by industry experts and access a range of industry-sponsored problems to build your portfolio.

Register your interest

Data Science Career Track

Land a job in Data Science
Get the entire Professional Development track + comprehensive career support and introductions to our network of hiring companies.

Register your interest

Included in the course price? Professional Development Track Career Track
155+ hours of in-person tuition ✓ ✓
300+ hours of collaborative projects ✓ ✓
90+ hours of end-to-end data science problems ✓ ✓
Expert advice and feedback ✓ ✓
Applied Data Science Certification ✓ ✓
Two Cambridge college formal dinners ✓ ✓
Evening drinks and networking ✓ ✓
Continuous careers support ✓
Technical interview preparation ✓
Recommended job opportunities ✓
Introductions to hiring companies ✓
Standard Price £6,960 £8,400
Early-bird Price – until 30 Sept £5,940 £7,290
Deposit at time of enrolment £990 £990
Monthly payments £550 £700

All prices include VAT.


Find out More

Simply register your interest. Our team will be in touch with the full curriculum and course information.

Register your interest