Masters of Business Administration
The Masters of Business Administration (MBA) at Modul University, Austria, is designed ...
BSc in Applied Data Science
Vienna
INTAKE: Feb & Sept
Program Overview
The BSc in Applied Data Science at Modul University, Austria, is a cutting-edge program designed to equip students with the essential skills and knowledge needed to navigate the rapidly growing field of data science. Combining theoretical foundations in mathematics, computer science, and statistics with practical applications in data analysis and machine learning, this program prepares students for a wide range of roles in industries that rely on data-driven decision-making. Graduates are equipped to handle complex data sets, apply advanced algorithms, and utilize modern tools to extract insights, making them highly competitive in the global job market.
Curriculum: The curriculum of the BSc in Applied Data Science focuses on providing a comprehensive understanding of data science concepts, algorithms, and techniques, with a strong emphasis on hands-on learning. Core courses include programming, data mining, machine learning, statistical analysis, and data visualization. Students also explore topics such as big data management, artificial intelligence, cloud computing, and ethical considerations in data science. The program combines theoretical coursework with practical projects, enabling students to work on real-world data challenges and gain the experience needed to excel in the field. Furthermore, students can specialize in areas such as data analytics, business intelligence, or data engineering.
Research Focus: Modul University’s BSc in Applied Data Science is rooted in research that bridges academic theory with real-world data applications. The research focus includes areas such as predictive analytics, machine learning, artificial intelligence, and the use of data to solve complex societal, business, and technological problems. Students have opportunities to engage in research projects that explore innovative data-driven solutions for industries such as healthcare, finance, tourism, and e-commerce. The faculty, comprising experienced researchers and industry professionals, regularly publish research findings that contribute to the advancement of data science practices, encouraging students to engage in collaborative, cutting-edge research.
Industry Engagement: Industry engagement is a key component of the BSc in Applied Data Science. Modul University has established strong partnerships with leading companies in data science and technology, offering students access to internships, industry projects, and collaborations. Students benefit from networking events, guest lectures, and mentorship from professionals in the field, gaining exposure to the latest tools, trends, and challenges in data science. These industry connections provide valuable opportunities for students to apply their knowledge to real-world problems, expand their professional network, and enhance their employability after graduation.
Global Perspective: The BSc in Applied Data Science at Modul University offers a global perspective on the data science field, preparing students to work in an interconnected and increasingly data-driven world. The program attracts a diverse student body from around the world, creating an international learning environment that fosters cross-cultural collaboration and global business awareness. Through case studies, global data trends, and opportunities for international internships, students gain insights into how data science is applied across various industries and cultures. The global perspective ensures that graduates are prepared to work in multinational companies or pursue careers in international markets, where data science plays a pivotal role in shaping business strategies and technological advancements.
Location
Vienna
Score
IELTS 6.5
Tuition Fee
€ 15480
Undergraduate Entry Requirements
Application Fee: € 100
Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 55% or above in their previous academic qualifications.
English Language Proficiency:
- IELTS: Overall band score of 6.5 with a minimum of 6.0 in each component.
Modul University Austria offers a range of scholarships designed to support international students in their academic journey. These scholarships aim to alleviate the financial burden of studying abroad and encourage high-achieving students to pursue their education in one of Europe’s most prestigious institutions.
Merit-Based Scholarships: Modul University offers merit-based scholarships for outstanding international students based on their academic achievements and potential. These scholarships are awarded to students who demonstrate excellence in their previous studies and have a strong academic track record. The scholarships can significantly reduce tuition fees and are available for both undergraduate and graduate programs.
Need-Based Financial Aid: In addition to merit-based scholarships, Modul University also provides need-based financial aid to international students who demonstrate financial need. The university assesses each student's financial situation on a case-by-case basis and offers assistance to ensure that students have the resources needed to complete their studies.
Early Bird Scholarships: Modul University offers early bird scholarships for students who apply early for their program. This scholarship provides a discount on the tuition fees for those who meet the early application deadlines. It encourages students to plan ahead and secure their place in the program while benefiting from reduced costs.
Partner Scholarships: Modul University has collaborations with various organizations and educational institutions around the world. Through these partnerships, the university offers additional scholarship opportunities for students from specific countries or partner institutions. These scholarships aim to foster international collaboration and exchange.
Graduates of the BSc in Applied Data Science from Modul University, Austria, have access to a diverse range of career opportunities across various sectors that rely heavily on data-driven decision-making and analysis. With the increasing demand for skilled data professionals, graduates are well-prepared to step into high-impact roles in both the private and public sectors.
Data Scientist: Leveraging expertise in statistics, machine learning, and programming to analyze and interpret complex data, providing actionable insights that help organizations make informed decisions.
Data Analyst: Collecting, processing, and analyzing data to uncover trends, patterns, and insights that drive business strategies. Data analysts often work closely with stakeholders to ensure data findings are aligned with business goals.
Machine Learning Engineer: Developing and deploying machine learning models and algorithms to automate processes, enhance decision-making, and improve operational efficiencies in various industries, including technology, finance, and healthcare.
Business Intelligence Analyst: Using data visualization tools and statistical techniques to interpret business data, helping organizations make strategic decisions based on real-time data and predictive analytics.
Big Data Engineer: Designing, implementing, and managing big data infrastructures, ensuring large-scale data sets are efficiently stored, processed, and analyzed. Big data engineers work with advanced technologies such as Hadoop, Spark, and NoSQL databases.
Data Engineer: Developing and maintaining systems that allow data collection, storage, and retrieval, ensuring data pipelines are efficient and scalable to meet the needs of data scientists and analysts.
Artificial Intelligence Specialist: Applying artificial intelligence and machine learning algorithms to solve real-world problems, often working in industries like robotics, healthcare, and autonomous systems.
Data Consultant: Providing expert advice to organizations on how to harness the power of data for business optimization, assisting in the implementation of data solutions and strategies tailored to specific business needs.
Quantitative Analyst: Analyzing complex data sets and financial models, often working in finance and investment sectors to identify market trends, assess risk, and optimize trading strategies.
Data Privacy and Security Analyst: Ensuring that data management practices align with regulations and security standards, protecting sensitive information from breaches and ensuring compliance with data privacy laws.
Data-Driven Marketing Specialist: Utilizing data analytics to develop targeted marketing campaigns, measure their effectiveness, and optimize customer engagement strategies based on data insights.
Health Data Analyst: Analyzing healthcare data to improve patient outcomes, optimize hospital operations, and contribute to research that leads to better healthcare policies and treatments.
Operations Research Analyst: Using mathematical models and data analysis to solve problems related to logistics, supply chain management, and operational efficiency in industries ranging from manufacturing to transportation.
