What you will learn
Essentials of Computer Science, Probability and Statistics
EDA, Feature Engineering and Unsupervised Learning
Supervised and Semi-Supervised Learning, Training and Validation
Regression Models and Time Series
Ensemble Models and Support Vector Classifiers
Cloud Computing and Databases
Big Data Systems
Neural Networks and Deep Learning
Natural Language Processing
How it works
You’ll complete the most comprehensive data science curriculum and progressively put together a portfolio to demonstrate your skills.
Our curriculum is made up of nine structured modules designed to rapidly develop your knowledge and understanding.
Each module comprises of learning activities, video lectures and project-based homeworks to complete at your own pace.
You'll get practical experience implementing state-of-the-art libraries and learn industry best practices to produce production-ready code.
You will access our Knowledge Assessment Teaching Engine (KATE) - a online learning environment that simulates industry-style software development.
With KATE, you’ll get automatic and immediate feedback on your code submissions to develop and improve your skills.
Our expert tutors offer office hours to provide guidance and stimulate discussion to ensure you can reason about your methodology.
Interact with like-minded professionals via slack and peer-learn through mutual code reviews.
Receive personalised, data-driven improvement plans based on your code submissions to keep on track.
You'll also get a report of common error feedback to support your learning progress.
Develop the industry specific skills to work effectively with data science and data analyst teams.
Understand the capabilities of machine learning models, and when/where to apply each technique to solve complex problems.
After completing the nine modules, you will work independently on an end-to-end project from our supporters and industry partners. We will match you with an exciting data science problem and help you make professional contacts in the field.
Final projects come from a range of sectors. Some examples include:
- Deep Learning: automatic image classification
- Time Series: visualising a portfolio of stocks
- NLP: topic modeling for crowdfunding campaigns
- Working on your own work related project is also supported
Upon completion you’ll earn an Applied Data Science certification supported by our academic and industry backers.
We're dedicated to supporting your success and provide introductions to hiring partners for new job opportunities.
Make meaningful connections as part of the Cambridge Spark community of data scientists, students and alumni.
- Elementary Python programming and use of the command line.
- Basic probability and linear algebra.
- Familiarity with Git.
Our course is designed for professionals looking to upskill while keeping their job. Check out your structured learning path.The Applied Data Science Journey
|Early-bird Price (until 31 March)||£2,450|
|Deposit at time of enrolment||£295|
|9 monthly payments||£295|
Satisfaction guaranteed receive a full refund within 7 days if you are not happy with the course.