Data ScienceTech Institute Applied Master of Science in Data Analytics

Created by Tiana Zignani

Posted 05 September 2022

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:

Full-time mode
Part-time - Apprentice mode
Continuing education - Blended learning
Blended learning - Accelerated mode
Blended learning - Self-paced Online Course (SPOC)

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 (75 hours - 6 ECTS)

Fundamental Applied Mathematics (10hrs)
Data structure and applied Machine Learning using Python & R (20hrs)
Introductions to:
- Data Management (5hrs)
- AI Awareness (5hrs)
- Computer Architecture (5hrs)
- Networking (5hrs)
Computer Systems Labs (10hrs)
Clean IT (10 hrs)
Excel Basics (5hrs)

Data Analytics (125hrs – 30 ECTS)

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 (105hrs – 26 ECTS)

Data Wrangling with SQL
Graph Databases - NoSQL Part 1
Document Databases - NoSQL Part 2
Data Warehousing and ETL
Data Pipeline Part 1

Data Management and Visualisation (125hrs – 24 ECTS)

Advance Excel for Data Analytics and Machine Learning
Data and Machine Learning Visualisation Ecosystem
Analysis & Design of Information Systems
CRM Data Management
Reporting and Visualisation

Management, Ethics & Law (50hrs – 4 ECTS)

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.