Big Data, Software Systems, Cloud Computing

About This Course

Big Data and Cloud Computing are at the heart of digital transformation. They empower enterprises and researchers to store, analyze, and act on data at unprecedented scale. In this module, we will study both the conceptual foundations and the practical implementations of big data and cloud systems. Using real-world datasets and industry-standard tools, you will learn how to:

• Understand why big data matters and its role in AI adoption
• Explore cloud service and deployment models (IaaS, PaaS, SaaS; public, private, hybrid)
• Work with databases and SQL for data modeling and manipulation
• Build and query cloud data warehouses with ETL/ELT pipelines
• Manage data ingestion, partitioning, and integration with BI tools
• Apply Docker and containerization for scalable software systems
• Conduct exploratory data analysis (EDA) in the cloud
• Implement and evaluate machine learning workflows on cloud platforms

Through this combination of theory and hands-on work, you will gain a comprehensive understanding of the big data and cloud ecosystem, from infrastructure and data management to analytics and AI integration.

Learning Objectives

By the end of this course, you will be able to:

• Understand the motivation, fundamentals, and terminology of big data and cloud computing
• Analyze the differences between cloud deployment and service models and their business/technical implications
• Design and query databases and data warehouses for large-scale data management
• Implement ETL/ELT pipelines to transform raw data into actionable insights
• Apply containerization (Docker) for building scalable and portable systems
• Perform exploratory data analysis in cloud environments using modern tools
• Train and evaluate machine learning models on cloud platforms
• Critically assess the opportunities, challenges, and compliance issues (e.g., GDPR, security) in big data and cloud adoption

Study Programs

This course is mandatory for the following study programs:

• MBA Digital Technologies
• MBA Digital Transformation
• M.Sc. Advanced Digital Reality
• M.Sc. Applied AI
• M.Sc. Cybersecurity
• M.Sc. Digital Leadership

This course is offered as an elective for the following study programs.

• The course is mandatory for all programs and can, therefore, not be selected as an elective.

Micro Degree

• This course is offered as a micro degree.
• German UDS Micro Degrees are compatible with the European MOOC Consortiums Common Micro Credentials Framework.
• Micro Degrees will be rewarded with an equivalent of 5 ECTS.
• Micro Degrees are offered to non-regular students and require a fee of €900.

Requirements

Knowledge and skills as provided in the Prep courses.

General Information

• Teaching Format: Combination of pre-recorded lectures, guided demos, weekly self-tests, homework assignments, and a final project.
• Total Workload Master: 125h (40h/85h) / 5 ECTS
• Total Workload MBA: 100h (40h/60h) / 4 ECTS
• Total Workload Micro Degree: 125h (40h/85h) / Equivalent to 5 ECTS
• Module coordinator: Prof. Dr. Raad Bin Tareaf
• Examinations: Quizzes, presentation(s), essay(s)/paper(s), project report(s), written exam (tbd) - Details will be announced with course start
• Offered: Even quarters