Master in Business Analytics & Data Science

Program Overview

This Master's program in Business Analytics & Data Science provides a comprehensive foundation in data science, using industry-leading software and tools. The program is taught by experienced faculty and features guest lectures from industry professionals, preparing graduates for careers in data science, business analytics, and related fields.

Program Outline

• This program provides students with a comprehensive foundation in data science, using industry-leading software, tools, and applications.
• Students gain practical experience with advanced web-based applications and toolsets.

Degree Awarded:

• A university master's degree (título propio) awarded by Universidad Católica San Antonio de Murcia (UCAM), Spain.
• A master's degree from EU Business School Switzerland, which is internationally accredited by ACBSP, IACBE, IQA, and certified by eduQua.

Overall Focus:

• Applying a hands-on approach to give students a comprehensive foundation in data science.
• Learning how to apply data management skills to a business setting to effectively implement data-driven solutions.

Outline:

Program Content:

• Data Analytics
• Business Intelligence
• Machine Learning
• Big Data
• Statistical Modeling
• Data Visualization
• Database Management
• Programming Languages (e.g., Python, R)
• Data Ethics

Course Schedule and Modules:

• Term 1:
• Introduction to Data Science
• Business Analytics
• Statistical Modeling
• Data Visualization
• Programming for Data Science (Python)
• Term 2:
• Machine Learning
• Big Data Analytics
• Database Management
• Data Mining
• Deep Learning
• Term 3:
• Advanced Data Analytics
• Business Intelligence
• Data Ethics
• Capstone Project

Module Descriptions:

• Introduction to Data Science: Provides a foundational understanding of data science concepts and methodologies.
• Business Analytics: Introduces students to the various techniques used to analyze business data and extract meaningful insights.
• Statistical Modeling: Teaches students how to build and interpret statistical models for data analysis.
• Programming for Data Science (Python): Equips students with the essential Python programming skills needed for data analysis.
• Machine Learning: Introduces students to the key concepts and algorithms of machine learning, with a focus on practical applications.
• Big Data Analytics: Covers the technologies and techniques used to analyze large and complex datasets.
• Database Management: Provides students with the knowledge and skills to design, implement, and manage databases for data storage and retrieval.
• Deep Learning: Introduces students to the advanced concepts and techniques of deep learning, a powerful subset of machine learning.
• Advanced Data Analytics: Offers an in-depth study of advanced data analytics techniques and applications.
• Data Ethics: Explores the ethical implications of data collection, analysis, and use.
• Capstone Project: Provides students with the opportunity to apply their acquired knowledge and skills to a real-world data science problem.

Assessment:

• A combination of coursework assessments, exams, and a capstone project is used to evaluate student learning.
• Coursework assessments may include quizzes, assignments, and presentations.
• Exams are typically written and cover the material taught in each module.
• The capstone project requires students to apply their data science skills to a real-world problem and present their findings in a comprehensive report.

Teaching:

• The program is taught by experienced faculty with expertise in data science, business analytics, and related fields.
• The faculty uses a variety of teaching methods, including lectures, case studies, group work, and hands-on exercises.
• The program also features guest lectures from industry professionals, providing students with real-world insights into the field of data science.

Careers:

• Graduates of this program are well-prepared for a variety of careers in data science, business analytics, and related fields.
• Potential career paths include data scientist, business analyst, data analyst, data engineer, and machine learning engineer.
• The program also provides students with the skills and knowledge they need to pursue further studies in data science or related fields.

Other:

• The program is offered on a full-time basis and can be completed in one year.
• The program is available entirely online, making it accessible to students worldwide.
• The program is taught in English.
• The program curriculum is regularly updated to reflect the latest advancements in data science and technology.
• The program provides students with access to a dedicated career services team to assist them with their job search.
• The program has a strong alumni network that provides graduates with valuable networking and career opportunities.