Bachelor in Data Science - Grado en Ciencia de Datos

The Data Science BSc programme sets out to develop the skills needed to cut through the deluge of data we’re dealing with on a global scale. Students learn to cut through the noise and employ automated analytical tools to create useful knowledge out of big data.

YEAR 1

In the first year, students obtain the foundational theoretical knowledge they need to become data scientists. The programme builds the mathematical basis upon which students will develop understanding of programming, statistics, machine learning and data management during following years. The courses are mostly given in a form of lectures and takeaway coursework.

Topics
Combinatorics & Graphs - 1
Foundations of Programming: C/C++
Calculus – 1
Foundations of Mathematical Logic
Linear Algebra -1
Algorithms and Data Structures – 1
Combinatorics and Graphs - 2
Object Oriented Programming: Python
Calculus – 2
Algorithms and Data Structures – 2
Linear Algebra -2
Computer Organisation and Systems
Combinatorics and Graphs - 3
Operating Systems
Calculus - 3
Capstone Project - 1
Seminars & Workshops - 1

YEAR 2

In the second year, students learn programming, statistics and machine learning in addition to courses that will further establish the mathematical foundations they need in data science.

The second year also contains courses that start covering tremendously useful data science tools as well as technical writing instruments. Most courses require practical coursework and a course project enabling students to get a feel for the challenges and approaches used in this field. The students will also begin developing software for the Capstone project.

By the end of this year, students will be able to write programmes, use primary data science tools and conduct data analysis and will be ready to study applied courses during the final year of the programme.

Topics
Probability Theory
Introduction to Statistics
Java Programming
Practical Unix
Parallel and Distributed Computing
Introduction to Optimization
Machine Learning – 1
R, Matlab, SPSS
Stochastic Processes
Introduction to Computer Networking
Database Systems Principles
Computational Complexity Theory
Introduction to Cryptography
Convex Optimization
Python for Massive Data Analysis
Capstone Project - 2
Seminars & Workshops - 2

YEAR 3

During the third, the final year, students will complete their studies of programming and data analysis and will primarily focus on applications of data science. The programme offers many of practical and interdisciplinary courses. The courses are taught by researchers and professionals who practice the courses they teach either academically or by sharing their professional experiences in their field.

Topics
Information Theory
MapReduce
Parallel and Disrtibuted Computing
Machine Learning – 2
Stochastic and Hugescale Optimization
Bioinformatics
Big Data & Emerging Technologies
Performance Oriented Computing
Text Mining
Software Development Process
Computational Genomics
Image Analysis
Technical Project Management
Web-graphs
Data Visualization
Neural Networks
Leadership and Group Dynamics
Writing, Documentation, TeX, JavaDoc, Academic
Introduction to Interaction Design
Capstone Project - 3
Seminars & Workshops - 3

Junior Data Scientist
Data Scientist
Senior Data Scientist
Principal Data Scientist
Chief Data Officer