Data ScienceTech Institute Applied Master of Science in Data Analytics
The Data ScienceTech Institute (DSTI) Applied Master of Science in Data Analytics aims to boost business and decision making skills through data analysis. This programme aims to teach students the techniques and tools needed to conduct analyses with relevant and structured reports. Students will develop an analytical mind and database skills throughout this programme. Additionally, they will learn about leader softwares, machine learning and IT and software management.
Various study options exist for this programme. These include:
- On campus with 8 months of courses followed by 5 to 6 months of internship
- Off campus full time with 8 months of online studying and 5 to 6 months of internship
- Apprenticeship where students can choose to study online or on campus and acquire work experience in 12 months
- SPOC - asynchronous mode designed for professionals to study at a pace that suits them over 36 months
- Accelerated programme with 8 months of classes and a mandatory 6-month internship
- Nominal programme spreading the programme over 2 years with 2 internship periods each year
Regardless of how students opt to study, they will be evaluated in a variety of ways over the course of their programme. This includes a multiple choice questionnaire in negative or zero mathematical expectation, DSTI internal exam, an external industrial certification exam (if applicable) and a 6 month internship in the data field.
Curriculum
The curriculum for this programme is split into various modules composed of specific courses.
Warm up
- Applied mathematics and data structures
- Introduction to IT systems
- Introduction to computer science
- Introduction to networks
- Computer systems
Data Analytics
- Applied Mathematics for Data Science
- Foundations of Statistical Analysis and Machine Learning Part 1
- Big Data Processing with R
- Semantic Web technologies for Data Science developments
- Python Machine Learning Labs
Databases
- Data Wrangling with SQL
- Document Databases - NoSQL Part 1
- Document Databases - NoSQL Part 2
- Datawarehousing and ETL
- Data Pipeline Part 1
Data Management and Visualisation
- Advance Excel for Data Analytics and Machine Learning
- Data and Machine Learning Visualisation Ecosystem
- CRM Data Management
- Reporting and Visualisation
Operational Methodologies
- IT Project Management - PMP-PMI and Agile Approaches
- Data Laws and Regulations - Philosophies, Geopolitics and Ethics
Admission requirements
There are no academic requirements to apply for this programme. However, IT and English requirements are required to take part in this programme. Namely a Windows PC with an Intel Core i5 minimum, 8GB RAM minimum, and 512GB of storage minimum are required. Additionally, applicants need to have a C1 level of English on the European scale CEFR which will be assessed at the admission interview to ensure applicants are able to follow the programme.
