Programs
Admissions
Ateneo De Manila University
Designing Tomorrow
MS Data Science from Ateneo de Manila is a research-oriented degree that provides foundation courses and a range of electives to pursue specific areas of interest. It has a six-unit credit capstone referred to as a thesis which requires an artifact as an output, a written report and an oral presentation. The student must likewise prepare a manuscript of his/her thesis work that is ready for submission to a reputable national or international journal or conference.
An 18-21 month program on a full-time basis, it allows the student to spend up to four months in London and obtain an MS Data Science degree from Ateneo de Manila.
Curriculum
The Data Science curriculum has a total of 36 units. Should the student choose to study at Queen Mary University of London for a semester (during the second semester of the first year), the courses will be credited to the Ateneo degree. There is an option to start during Intersession or the First Semester as shown below.
INTERSESSION INTAKE
|
FIRST YEAR |
|
|
Intersession (June – July) |
|
|
Programming with Databases |
3 |
|
Data Visualization |
3 |
|
First Semester ( August – December) |
|
|
Applied Statistics |
3 |
|
Big Data Processing |
3 |
|
Data Mining |
3 |
|
Methods and Domains Course 1 |
3 |
|
Second Semester (January – May) |
|
|
Methods and Domains Course 2 |
3 |
|
Methods and Domains Course 3 |
3 |
|
Methods and Domains Course 4 |
3 |
|
Methods and Domains Course 5 |
3 |
|
SECOND YEAR |
|
|
Thesis I |
3 |
|
First Semester (August – December) |
|
|
Thesis II |
3 |
|
Total Unit Count |
36 |
FIRST SEMESTER INTAKE
|
FIRST YEAR |
|
|
First Semester ( August – December) |
|
|
Programming with Databases |
3 |
|
Applied Statistics |
3 |
|
Big Data Processing |
3 |
|
Data Mining |
3 |
|
Second Semester (January – May) |
|
|
Methods and Domains Course 1 |
3 |
|
Methods and Domains Course 2 |
3 |
|
Methods and Domains Course 3 |
3 |
|
SECOND YEAR |
|
|
Intersession (June – July) |
|
|
Methods and Domains Course 4 |
3 |
|
Methods and Domains Course 5 |
3 |
|
First Semester (August – December) |
|
|
Thesis I |
3 |
|
Second Semester (January – May) |
|
|
Thesis II |
3 |
Ateneo Electives: Business Intelligence, Computational Science, Pattern Recognition, Machine Learning, Natural Language Processing, Social Computing, Affective Computing, Financial Applications, Modeling and Simulation, Geographic Information Systems and Geospatial Analytics, Big Data Project Management, or other courses that cover methods or domains in data science
Queen Mary Electives: Introduction to Computer Vision, Introduction to Object-Oriented Programming, Machine Learning, Semi-structured Data and Advanced Data Modelling, Business Technology Strategy, Could Computing, Data Analytics, Digital Media and Social Networks, Information Retrieval, Natural Language Processing, Techniques for Computer Vision, The Semantic Web
Retention Policy
Aside from the standard Ateneo and QMUL policies for retention of graduate students, MS Data Science – MSc Big Data Science requires a minimum grade of B+ in each of the foundational courses required in the first two semesters of the program.