Data Science
Everyone is talking about digital transformation. Digital transformation refers to the challenges that companies and organisations face in terms of renewing and improving their business models through the opportunities offered by digitalisation. In the age of big data, the ability to intelligently evaluate the amount of data generated during business operations and in transactions with customers plays a key role. Data analytics is therefore the engine of digital transformation:
- A car insurer offers its customers a special rate which is tailored to their personal driving behaviour.
- A consumer goods manufacturer analyses customers’ discussions about product use in social media networks and then adjusts its marketing message and pricing accordingly.
- A mobile operator plans to introduce a new mobile phone rate and is able to forecast the number of customers that will migrate and subscribe to the new rate.
- A manufacturer of lifts uses sensors to collect data in their lifts, integrates this data into a real-time monitoring system, thereby reducing lift malfunctions with the provision of a predictive service.
- An online bank uses data analytics with the aim of making loan decisions fully automatically and online within seconds by calculating an individual credit score with a high degree of accuracy using just a few data points.
The Data Science certificate course teaches the theory and methods of digital transformation with analytics and explains how corporate decisions can be made on the basis of data in order to achieve a competitive edge.
If you want to streamline operational decisions in various areas of your company, such as production, logistics, marketing or controlling, by using data-based analysis of the current state of your company, then Data Science is the right course for you.
Course participants are shown how to create the "data-based company" by generating information from large and confusing amounts of data ("big data") and making fact-based recommendations for action that underpin corporate decisions. Possible uses of data science in companies and organisations are manifold and include customer relationship management, risk analysis and quality management.
The majority of the lectures are held online.
Target group
This certificate course is aimed at people with an advanced analytical-methodical understanding and who want to build and implement analytical models in different areas of application.
Admission requirements
In order to qualify for the certificate course, you must have at least two years’ professional experience, preferably in an area related to IT, or a university degree.
Opportunity to further your qualifications
After successfully completing the certificate course, course participants without formal university entry qualifications qualify for university admission and can start a bachelor's degree at the Neu-Ulm University of Applied Sciences.
Contents
The term "data science" combines the following subjects into an overall discipline:
- databases
- statistics
- machine learning
- data mining, mathematics
- visualisation
This combination of subjects enables participants to make focused decisions on the basis of data.
Format and teaching
This certificate course can be studied on a part-time basis. All lectures are held online except for two weekends of university-based teaching, keeping your travel time to and from the Neu-Ulm University of Applied Sciences to a minimum. In this programme, you have the flexibility to attend lectures wherever you have access to the Internet.
Qualification
Upon successful completion of the programme, the Neu-Ulm University of Applied Sciences will award you the Certificate of Advanced Studies (CAS) in Data Science, which equates to 10 ECTS points.
SCHEDULE AND DATES
Data Science – Principles and Strategy
- Digital transformation and data science
- The data-driven company
- Big Data: volume, velocity, variability, veracity
- The professional profile of the data scientist
Format
- Online
Big Data Technologies
- Overview and comparison of front-end tools for big data applications
- Distributed processing of large data volumes in horizontally scaled server infrastructures (e.g. in the cloud)
- NoSQL databases
- Apache Hadoop and Spark
- MapReduce method
- Introduction to the implementation of machine learning methods (e.g. neural networks) in such environments
Format
- Online
Data Mining and Predictive Analytics
- CRISP procedure model for data mining projects
- Introduction to the following data mining methods:
- Descriptive methods: associations, clustering, correlations
- Forecasting: classification, logistic regression, decision trees, linear regression
- Neural networks (MLP and CNN)
- Introduction to programming with Python based on Jupyter notebooks
- Application-related exercises for the above-mentioned data mining methods based on:
- RapidMiner: interactive tool for data mining by graphical definition of data processing
- Python: object-oriented programming of data mining projects using TensorFlow, Keras and SciKit
Format
- Online
Visual Analytics
- Principles of effective visualisation
- Data story telling
Format:
- Online
Data Engineering
- Design of analytical information systems
- OLAP vs OLTP
- ELT process and data integration
- Data integration tools
- Practical exercises with Talend Data Integration Tool
Format:
- Online
Written Examination / Case Studies Project-based Assignment
Format
- Online
The Process of Data Science
- Data science life cycle
- Standard process model for data mining
Format
- Online
Case studies – presentations
Format
- Online
FAQs - FREQUENTLY ASKED QUESTIONS
Who is the course for?
The Data Science certificate course is aimed at people who prepare and provide support services in various areas of their companies, such as in logistics, marketing and controlling, by providing data-based analysis of corporate activities.
The objective of the data scientist is to create the "data-based company" by generating information from large and confusing amounts of data ("big data") and making fact-based recommendations for action that underpin corporate decisions.
This certificate course is aimed at people with a detailed technical understanding who want to build and implement analytical models.
What are the benefits for course participants?
Increasing digitalisation results in vast amounts of data (big data) for companies. New technologies in the field of data mining, analytical databases and graphic visualisation offer a wide range of innovative options for data analysis, data compression and prediction of corporate activities. Information can be generated and new information can be gained from large amounts of structured and unstructured data.
The term "data science" covers various specialist areas including databases, statistics, machine learning, data mining, mathematics and visualisation. These areas are combined to form a general discipline: data science. Data science makes it possible to make focused decisions based on data.
As a "data scientist", you act as an interface between IT and the relevant department/company management. You are able to design specific analytical models in the field of data mining for operational activities and you can select the required data from different data sources and apply them using the appropriate tools.
When does the teaching take place?
This certificate course can be studied on a part-time basis.
The lectures take place in 10 on-campus block sessions, mostly on Fridays and Saturdays. The course starts with a two-day university-based block, with subsequent lectures taking place online. Course participants are also required to sit a written examination at the university and complete case study work and project-based assignments.
What qualification does the course offer?
Upon successful completion of the certificate course, the Neu-Ulm University of Applied Sciences will award you the Certificate of Advanced Studies (CAS) in Data Science which equates to 10 ECTS points.
Upon completion of this certificate course, the obtained ECTS points can be credited to the master's programme in "Digital Leadership and IT Management".
How much does the certificate course cost?
€ 2,400
What should you look out for when applying for this certificate course on the application portal?
Please note that the certificate course must be selected in the application portal under Certificate of Continuing Education ZDS. ZDS stands for Certificate in Data Science.
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