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Master in Business Analytics & Data Science | Taught in English

Master in Business Analytics & Data Science | Taught in English

EU Business School

Máster presencial

Barcelona y 2 más


más de 9000€

Duración : 1 Año

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Sedes

Localización

Fecha inicio

Genève
Enero 2024
Barcelona
Enero 2024
München
Enero 2024

Requisitos

Admission Requirements:* 1 certified copy of bachelor's degree and transcripts Proof of English level: TOEFL score 89 (internet-based), 233 (computer-based); IELTS 6.5; CAE C1 with a minimum score of 176; English native or equivalent Applicants must also meet one of the following: A GPA of 3.0 on a 4.0 scale A satisfactory score on the GMAT or GRE An interview with the academic dean * Students who do not meet the criteria will have an interview with the admission committee and will be considered on a merit basis.

Temario completo de este curso

A sample of the program courses:
MADSC101 Introduction to Big Data and Data Science (3 CH/4 ECTS)
Data is truly everywhere. Digitization, computing and the Internet have revolutionized the accumulation, volume and use of data. Today we can collect, store and preserve more data than ever before. Working with these large amounts of dynamic and unstructured data requires a whole new set of skills and technologies. This course introduces students to the landscape of big data, data science, machine learning and statistics and how they can be used together to derive business value from data.
MADSC102 The Data Science Toolkit (3 CH/4 ECTS)
This hands-on course introduces students to the main tools used in data science, including Python and the Jupyter ecosystem. Students will understand how to create a virtual environment and install libraries for different data science projects and identify the main advantages of Python and R as tools for data science. They will also complete an end-to-end data analysis project using the Pandas library.
MADSC103 The Big Data Toolkit (3 CH/4 ECTS)
Students will learn about the tools available for dealing specifically with big data. Students will gain hands-on experience with the different models available for big data, including SQL databases, NoSQL databases, Hadoop ecosystem and Apache Spark. Emphasis will be placed on the different business problems that each model helps us solve, and their advantages and shortcomings will be assessed.
MADSC104 Data Security & Privacy (3 CH/4 ECTS)
In today’s regulatory landscape, data security and privacy are at the forefront of every enterprise. Students will understand the principle legal structures governing how organizations can collect, store and handle their data; understand the main threats in the cybersecurity landscape; and become equipped with the right set of tools and knowledge for handling them. Real-world examples illustrate the complex nature of ethical and social issues underlying the technology industry and students will understand the best strategies for success from the perspective of security, privacy and ethics.
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