Master's in Business Analytics

Education objectives

The Master’s in Business Analytics aims at the development of solid technical, organizational, leadership, critical thinking and communication competencies for future managers and leaders of organizations (public or private, for-profit or not-for-profit) in a context increasingly dependent on algorithms and hybrid (human-machine) systems for decision making. It is therefore focused on the education of translators, i.e., people who understand organizations and the managerial problems they face and know how to use technology and leverage data to solve them.

information available >> https://www.novasbe.unl.pt/en/programs/masters/business-analytics/overview


General characterization

DGES code

MB04

Cicle

Master (2nd Cycle)

Degree

Master

Access to other programs

Allows access to other cycles of education 

information available >> https://www.novasbe.unl.pt/en/programs/phds   

Coordinator

Professor Doutor Rodrigo Belo

Opening date

A disponibilizar brevemente

Vacancies

210

Fees

11.900 Euros 

information available >> https://www.novasbe.unl.pt/en/programs/masters/business-analytics/fees


Schedule

Full-time, on-campus

Teaching language

English

Degree pre-requisites

 With a collaboration with the Department of Computer Science of Nova School of Science and Technology, the program brings together the technical and personal competencies of management with technology.

This multidisciplinary is key to attract applicant profiles with a first cycle educational background in sciences, technology, engineering or mathematics, but also economics, finance or management.

 The masters (*) have a minimum of 3 semesters of instruction, including a curriculum part and the work project.

For obtaining the mater's degree is required to complete a minimum of 90 ECTS, being the maximum of 120 ECTS, which decompose in:

a) curriculum approval: minimum of 60 ECTS course approval;

b) work project approval: 30 ECTS.

(*) For the graduation, students must complete the degree academic requirements and the necessary number of ECTS, according to the course’s list offered in the academic year. The list of courses offered is subject to change. 

information available >> https://www.novasbe.unl.pt/en/programs/masters/business-analytics/program


Conditions of admittance

Eligible candidates must hold a bachelor's degree, have a solid quantitative background (i.e. economics, mathematics, statistics, physics, etc.), and have exceptional analytical skills.

Provide proof of B2-level English language proficiency, possess up to 2 years of professional experience, and be under 26 years of age. 

information available >> https://www.novasbe.unl.pt/en/programs/apply/masters/admission


Evaluation rules

Throughout the master's program, and depending on the courses, students are evaluated through various methods such as exams, assignments, projects, presentations, and participation on class discussions.   

information available >> https://www.novasbe.unl.pt/en/programs/masters/business-analytics/program

Structure

Fall
Code Name ECTS
2597 Advanced Data Analysis 3.5
2582 Competitive Strategy: an analytical approach 7
2484 Corporate Strategy and Transformation 7
2578 Mastering Your Career 2
2421 Applied Entrepreneurship 7
Spring
Code Name ECTS
2610 Business Analytics Special Project 7
2220 Entrepreneurial Finance & Venture Capital 7
2484 Corporate Strategy and Transformation 7
2280 Data Analytics for Finance 7
2638 Design Thinking for Social Innovation 7
2578 Mastering Your Career 2
2421 Applied Entrepreneurship 7
2487 Machine Learning 7
Fall 1st Half
Code Name ECTS
2621 Algorithmic governance 3.5
2389 Machine Learning 7
2659 Data Curation for Business Analytics 3.5
2481 Product Design and Development 3.5
2606 Data Ecosystems and Governance in Organizations 3.5
2639 Entrepreneurial Strategy 3.5
2352 Quality Management 3.5
2270 Financial Modeling 3.5
2128 Competition Policy 3.5
2599 Project scoping 3.5
2496 Strategic Foresight and Scenario Planning 3.5
Fall 2nd Half
Code Name ECTS
2621 Algorithmic governance 3.5
2440 Big Data Analysis 3.5
2493 Marketing Analytics 3.5
2609 Data Visualization for Business Analytics 3.5
2218 Derivatives 3.5
2607 Digital Markets 3.5
2588 Science-Based Entrepreneurship and Innovation 3.5
2649 Energy and Climate change 3.5
2359 Operations Management 3.5
2448 Business Model Innovation 3.5
2441 Digital Marketing 3.5
2346 Modeling Business Decisions 3.5
2270 Financial Modeling 3.5
2644 Sustainable Operations 3.5
2185 Game Theory 3.5
Spring 1st Half
Code Name ECTS
2663 AI Impact on Business 3.5
2440 Big Data Analysis 3.5
2493 Marketing Analytics 3.5
2622 Blockchain fundamentals 3.5
2371 Circular Economy: Eliminate, Circulate and Regenerate 3.5
2616 Cracking the Sales Code 3.5
2389 Machine Learning 7
2218 Derivatives 3.5
2481 Product Design and Development 3.5
2135 Economics of Health and Health Care 3.5
2273 Fintech Ventures 3.5
2468 Technology Strategy 3.5
2352 Quality Management 3.5
2214 Asset Management 3.5
2465 Open Innovation 3.5
2641 Modeling Business decisions for Operations 3.5
2623 Network Analytics 3.5
2612 Advanced Programming for Data Science 3.5
2496 Strategic Foresight and Scenario Planning 3.5
2615 Web and Cloud Computing 3.5
Spring 2nd Half
Code Name ECTS
2622 Blockchain fundamentals 3.5
2616 Cracking the Sales Code 3.5
2442 Design and Construction of Data-Centric Apps 3.5
2588 Science-Based Entrepreneurship and Innovation 3.5
2451 Operations Strategy 3.5
2468 Technology Strategy 3.5
2397 Innovation Management 3.5
2214 Asset Management 3.5
2359 Operations Management 3.5
2465 Open Innovation 3.5
2448 Business Model Innovation 3.5
2441 Digital Marketing 3.5