Digital and Technology Solutions Specialist (Data Analytics) Masters Degree Apprenticeship

Program Overview

This Master's Degree Apprenticeship in Digital and Technology Solutions (Data Analytics) equips individuals with the skills to analyze and interpret data using industry-standard software. The program covers data management, interpretation, and project management, preparing graduates for careers as data analysts, data scientists, and other data-driven roles. It offers flexibility to accommodate diverse backgrounds and provides opportunities for professional qualifications and industry collaborations.

Program Outline

Objectives:

• Train data specialists who can effectively analyze and interpret data using industry-standard software.
• Develop advanced skills in quantitative methods, data analysis, communication, and business intelligence.
• Equip graduates with the tools and knowledge to tackle real-world data challenges across various industries.

Outline:

The program structure focuses on three core areas:

• Data Management: Covers data structuring and manipulation techniques for optimal analysis.
• Data Interpretation: Explores Machine Learning and statistical analysis methods using industry-standard software (R, SAS, Python).
• Project Management: Equips students with the tools and skills to approach data analytics projects from a strategic business perspective.

Modules:

• Core Modules:
• Introduction to Statistical Data Analysis with R
• Business Analytics Strategy and Practice
• Data Management
• Data Mining and Knowledge Discovery in Data
• Final Apprenticeship Project in Data Analytics
• Optional Modules:
• Risk Analysis and Retail Finance
• Multivariate Analysis and Statistical Modelling
• Medical Statistics
• Programming for Analytics with SAS
• Project in Statistical Data Analysis with R
• Machine Learning and Artificial Intelligence
• The Analysis of Time Series
• Flexibility: The program offers adaptation to accommodate students' backgrounds and interests.

Assessment:

Evaluations are conducted through various methods:

• Presentations: Effective communication of findings and research.
• Practical Assignments: Hands-on application of skills and knowledge using industry-standard software.

Teaching:

The program employs a blend of teaching methods:

• Lectures: Conveying core concepts and theoretical frameworks.
• Tutorials: In-depth exploration of specific topics and individualized guidance.
• Workshops: Hands-on learning through practical exercises and data analysis tasks.

Teaching Staff:

Highly qualified faculty with expertise in various data analytics fields, including:

• Dr. Sónia Timóteo Inácio: Course Leader, specializing in data mining and machine learning.
• Dr. Alexey Chernov: Expertise in mathematical foundations of Machine Learning and Artificial Intelligence.
• Dr. Anestis Touloumis: Research focusing on novel statistical methods and R software development.

Careers:

Graduates can pursue diverse career paths in various industries, including:

• Data Analyst
• Data Scientist
• Business Intelligence Analyst
• Quantitative Analyst
• Market Research Analyst
• Statistical Modeler
• Data Management Specialist

Other:

• Uniquely designed to cater to non-specialist backgrounds.

• Apprenticeship offers 20% of paid working hours for studies and off-the-job learning.

• Focus on research-informed learning and critical thinking.