Major code: SCI3095

Entry points: Aalto, Technical University Eindhoven (TU/e), Royal Institute of Technology (KTH), Technical University of Madrid (UPM), Université Côte d'Azur (UCA), Polytechnic University of Milan (POLIMI), University Paris Sud and Eötvös Loránd University (ELTE).

Exit points with specializations:
Aalto: Machine Learning, Big Data Management, and Business Analytics
ELTE: Real-time Data Analytics
KTH: Distributed Systems and Data Mining for Big Data
TU Berlin: Design, Implementation, and Usage of Data Science Instruments
TU/e: Business Process Intelligence
UCA: Multimedia and Web Science for Big Data
UPM: Infrastructures for Large Scale Data Management and Analysis
UPS: Natural language Processing
University of Trento (UNITN): Variety and Veracity for Big Data at Trento


Professor in charge 2018-2019:Aristides Gionis
Academic coordinator as of 2019-2020:Wilhelmiina Hämäläinen
Other professors of the major:Rohit Babbar

Objectives of the programme

The Aalto specialization aims to provide students a versatile and diverse set of skills for managing very big data, extracting knowledge from data, learning models and making inferences, creating meaningful visualizations to interact with data, and using data-driven methods in business analytics and intelligence, as well as in other applications. These are all necessary skills to becoming a successful data scientist, one of the top professional careers world-wide. An ideal candidate to the Aalto specialization is mathematically inclined, technically proficient, has entrepreneurial spirit, and interest in solving real-life problems.

Entry year, autumn semester 2018 and 2019

Compulsory major courses (24 ECTS)

CodeCourse nameCredits
SCI-E1010Introduction course for Master's students: Academic Skills1 ECTS
LC-xxxx

Language course: Compulsory degree requirement, both oral and written requirements

3 ECTS
CS-E3210

Machine Learning Basic Principles

5 ECTS
CS-E3190Principles of Algorithmic Techniques5 ECTS
CS-E4640Big Data Platforms5 ECTS

Compulsory I&E Courses (7 ECTS)

CodeCourse nameCredits

CS-E5120

Introduction to Digital Business and Venturing

3 ECTS

CS-E5130

Digital Business Management

4 ECTS

Elective major courses - select at least 7 ECTS over the two semesters.

Autumn courses

CodeCourse nameCredits
CS-E5710Bayesian Data Analysis5 ECTS
CS-E4600Algorithmic Methods of Data Mining5 ECTS
CS-E4850Computer Vision5 ECTS
CS-E4100Mobile Cloud Computing5 ECTS
CS-E5740Complex Networks5 ECTS
CS-E4002Special Course in Computer Science1-10 ECTS
CS-E4003Special Assignment in Computer Science1-10 ECTS
ELEC-E5422Convex Optimization I5 ECTS
ELEC-E5500Speech Processing5 ECTS
ELEC-E5510Speech Recognition5 ECTS
31E00910Applied Microeconometrics I6 ECTS
23E47000Digital Marketing6 ECTS

Entry year, spring semester 2019 and 2020

Compulsory major courses (10 ECTS)

CodeNameCredits
CS-E4800Artificial Intelligence5 ECTS
CS-E4890Deep Learning5 ECTS


Compulsory I&E Courses (17 ECTS)

CodeCourse nameCredits

TU-E4100

Startup Experience

9 ECTS

CS-E5140

Global Business in the Digital Age

4 ECTS

CS-E5430

ICT Innovation Summer School

4 ECTS


Elective major courses - select at least 7 ECTS over the two semesters.

Spring courses:

Code

Name

Credits
CS-E4820Machine Learning: Advanced Probabilistic Methods5 ECTS
CS-E4830Kernel Methods in Machine Learning5 ECTS
CS-E4840Information Visualization5 ECTS
CS-E4580Programming Parallel Computers5 ECTS
CS-E4002Special Course in Computer Science1-10 ECTS
CS-E4003Special Assignment in Computer Science1-10 ECTS
MS-C1620Statistical Inference5 ECTS
ELEC-E5550Statistical Natural Language Processing5 ECTS
30E03000Data Science for Business6 ECTS
31C01000Economics of Strategy for Online and Digital Markets6 ECTS

Total for the whole year: 60 ECTS

Note for exit year at partner university: According to Finnish legislation, a master's thesis is a public document and its contents cannot be confidential. Therefore, the material of the thesis must be chosen so that it does not include any information that could be classified as a business secret of the financing company. More information about Master's thesis process for Aalto entry students here.

Exit year, autumn semester 2018


Aalto specialization – Machine Learning, Big Data Management and Business Analytics

Compulsory major courses (17 ECTS)

CodeCourse nameCredits
SCI-E1010Introduction course for Master's students: Career and working life skills1 ECTS

 LC-xxxx

Language course: Compulsory degree requirement,
both oral and written requirements

3 ECTS

CS-E4620Introduction to Analytics and Data Science2 ECTS
57E00700Capstone: DigitalSM Challenge6 ECTS
Select at least one course of the following:
CS-E3210Machine Learning Basic Principles5 ECTS
CS-E5710Bayesian Data Analysis5 ECTS
CS-E4600Algorithmic Methods of Data Mining5 ECTS


Compulsory I&E Courses (6 ECTS)

CodeCourse nameCredits

CS-E5425

I&E Study Project

6 ECTS


Optional major courses (7 ECTS)

CodeCourse nameCreditsSemester
CS-E3190Principles of Algorithmic Techniques5 ECTSautumn
CS-E5740Complex Networks5 ECTSautumn
ELEC-E5510Speech Recognition5 ECTSautumn
CS-E4830Kernel Methods in Machine Learning5 ECTSspring
CS-E4002Special Course in Computer Science1-10 ECTSautumn/spring
CS-C3170Web Software Development6 ECTSautumn&spring
CS-E4870Research Project in Machine Learning and Data Science5-10 ECTSautumn/spring
CS-E4003Special Assignment in Computer Science1-10 ECTSautumn/spring
CS-E4004Individual Studies in Computer Science1-10 ECTSautumn/spring
CS-E4000Seminar in Computer Science5 ECTSspring
CS-E4800Artificial Intelligence5 ECTSspring
CS-E4840Information VIsualization5 ECTSspring
37E01600Data Resources Management6 ECTSautumn/spring
CS-E4640Big Data Platforms5 ECTSautumn
CS-E4580Programming Parallel Computers5 ECTSspring
23E47000Digital Marketing6 ECTSautumn
30E03000Data Science for Business6 ECTSspring
CS-E4890Deep Learning5 ECTSspring
CS-E4850Computer Vision5 ECTSautumn
MS-C2128Prediction and Time Series Analysis5 ECTSautumn
ELEC-E8125Reinforcement Learning5 ECTSautumn

Total: 30 ECTS

Exit year, autumn semester 2019 (note: curriculum updated)


Aalto specialization – Machine Learning, Big Data Management and Business Analytics

Compulsory major courses (14 ECTS)

CodeCourse nameCredits
SCI-E1010Introduction course for Master's students: Career and working life skills1 ECTS

 LC-xxxx

Language course: Compulsory degree requirement,
both oral and written requirements

3 ECTS

Select at least two courses of the following:
CS-E3210Machine Learning Basic Principles5 ECTS
CS-E5710Bayesian Data Analysis5 ECTS
CS-E4600Algorithmic Methods of Data Mining5 ECTS
CS-E4640Big Data Platforms5 ECTS


Compulsory I&E Courses (6 ECTS)

CodeCourse nameCredits

CS-E5425

I&E Study Project

6 ECTS


Optional major courses (10 ECTS)

CodeCourse nameCreditsSemester
CS-E3190Principles of Algorithmic Techniques5 ECTSautumn
CS-E5740Complex Networks5 ECTSautumn
ELEC-E5510Speech Recognition5 ECTSautumn
57E00700Capstone: DigitalSM Challenge6 ECTSautumn
CS-E4830Kernel Methods in Machine Learning5 ECTSspring
CS-E4002Special Course in Computer Science1-10 ECTSautumn/spring
CS-C3170Web Software Development6 ECTSautumn&spring
CS-E4870Research Project in Machine Learning and Data Science5-10 ECTSautumn/spring
CS-E4003Special Assignment in Computer Science1-10 ECTSautumn/spring
CS-E4004Individual Studies in Computer Science1-10 ECTSautumn/spring
CS-E4000Seminar in Computer Science5 ECTSspring
CS-E4800Artificial Intelligence5 ECTSspring
CS-E4840Information VIsualization5 ECTSspring
37E01600Data Resources Management6 ECTSautumn/spring
CS-E4580Programming Parallel Computers5 ECTSspring
23E47000Digital Marketing6 ECTSautumn
30E03000Data Science for Business6 ECTSspring
CS-E4890Deep Learning5 ECTSspring
CS-E4850Computer Vision5 ECTSautumn
MS-C2128Prediction and Time Series Analysis5 ECTSautumn
ELEC-E8125Reinforcement Learning5 ECTSautumn

Total: 30 ECTS

Exit year, spring semester 2019 and 2020

CodeCourse nameCredits

CS.thes

Master’s Thesis

30 ECTS

Total: 30 ECTS


Total for the whole year: 60 ECTS