The data-driven world offers more facts and figures and answers than we can use. This makes it all the more important to ask the right questions and use the right tools.

The focus is on the tools of a data analyst - data understanding, analytical approach, appropriate technology.

Upon successful completion of the certificate program, you will be able to,

• Explain and discuss current developments and opportunities in software-based data analysis.
• Distinguish and apply common data modeling and data retrieval techniques.
• Classify, evaluate, and contrast current methods and tools used for data analysis and visualization.
• Select and apply methods and tools in a given context.
• Combine different analysis techniques.
• To visually prepare and communicate results in a way that is appropriate to the subject and the audience.

Would you like to learn how to turn data into decision-relevant information that can create value in the company?

The certificate program is aimed at specialists and managers from all industries in the areas of planning, controlling, reporting, IT, finance, sales, marketing and product management,

• who want to make decisions and perform qualified analyses of data sets for this purpose
• who want to support management or specialist departments in the evaluation of data sets and prepare the results effectively.
• who want to understand tools and methods of statistics, data mining and machine learning and use them purposefully.
• who would like to use practice-relevant software to make their analyses efficient.

Notes on participation:

In the two courses on data analysis, "hands-on" knowledge is taught using a commercially available (statistical) programming language, such as R or Python. A willingness to work with this should be present. Introduction to materials will be provided for the self-study phase prior to the courses.

It is mandatory to have your own notebook with the ability to install and run programs. Your notebook should already have the Microsoft Office package and Google Chrome installed. Various software (e.g., R, RStudio, Orange Data Mining) is typically used in the data analysis courses.

Further participation requirements

• The didactic concept of the certificate program is specifically tailored to working professionals.
• We offer you a high degree of time flexibility through the combination of classroom and online-supported self-learning phases.
• You will link your practical professional experience with scientific theories and methods and thus expand your competencies.
• The high practical relevance of the continuing education is guaranteed by the many years of professional experience of our lecturers in companies and institutions.
• With us you learn in small groups, so we guarantee you optimal support and enough space for your individual questions.
• You will benefit from the exchange with professional colleagues and expand your professional network.

The certificate program takes place in a combination of classroom and self-study units (blended learning). The self-study is accompanied by the online learning platform Moodle. The classroom phases are held in an interactive seminar format, alternating between impulse lectures and practice elements. The knowledge imparted is tested "hands-on" and there is the opportunity to work on individual questions and problems of the participants.

REPORTING MULTIDIMENSIONAL DATA
AND KEY FIGURES

"We are drowning in a flood of information, yet we are starving for knowledge."
Rutherford D. Rogers

In keeping with the adage that "data is the new oil," collecting data has become a given. But collecting alone does not generate value for businesses. Only a fraction of existing data sets are business-relevant and actually suitable for analysis. To make matters worse, data often comes from different sources and exists in different structures. In order to support management, data must be combined and merged in a meaningful way. In addition, the decision-oriented presentation of the obtained key figures is of enormous importance.

In this certificate course, you will deal with the problems of multidimensional data structures and apply solution strategies for data procurement and modeling. With the help of suitable software, you will consolidate data and make it usable. You will select suitable reporting tools and convert key figures into a readable and usable form for decision-makers in the company.

FUNDAMENTAL DATA ANALYSES
Regression & Data Mining.

"True knowledge is knowledge that goes back to causes."
Sir Francis Bacon

Reading current articles in magazines and newspapers, one can come to the conclusion that the analysis of data is either a highly complex process for specialists who master their statistical instruments in their sleep, or a conceivably simple matter that "intelligent" machines do on the side and much more efficiently than humans. As usual, the truth lies in the middle. For everyday operations, comparatively simple approaches often provide an initial insight into data and relationships. For example, groups within the clientele can be quickly identified by clustering methods and subsequently served specifically, or decisions, e.g. for assessing the profitability of business relationships, can be supported quantitatively.

This certificate course explores some of the fundamental tools of data analytics and shows how and for what they can be applied. The goal is for you to learn and try out directly usable techniques of analysis and visualization. In the follow-up course "Advanced Data Analytics - Advanced Analytics & Text Mining" these techniques will be extended and deepened.

ADVANCED DATA ANALYSES
Advanced Analytics & Text Mining.

"If you torture data long enough, it will confess to anything."
Ronald Coase

Fundamental methods of data analysis provide a suitable and quickly applicable foundation course for looking at operational issues. However, they can be extended, configured more specifically or supported by simplifying visualization, e.g. because market experts can combine multidimensional data sets with their background knowledge in this way. Also, when the data is no longer purely numerical, targeted analysis methods must be used to support advanced users in their investigations. For example, automated analysis of text databases can assist in identifying trends in an industry, or online reviews of products can be evaluated for customer sentiment.

This certificate course will show you the adaptations and extensions that can be made to fundamental data analysis methods and how non-numeric data can be handled. You will be introduced to current techniques such as artificial neural networks.

11 attendance days - on request at weiterbildung(at)hsnr.de

• Reporting of multidimensional data and key figures
• Fundamental data analysis - Regression & Data Mining
• Advanced Data Analytics - Advanced Analytics & Text Mining
  
  Between the attendance days there are online-supported self-study phases.
• Total workload: 275 h, thereof 88 h attendance, 11 ECTS
• Registration deadline: --
• Number of participants: approx. 12 persons
• Location: Krefeld South Campus

• Participation fee: 4.100 € | Food and beverages included | Payment in three installments, the first installment 1.400 Euro, the two further ones à 1.350 Euro, is possible | Alumni (5% discount) 3.895 €
• Participation requirements: University degree with at least one year of professional experience or other professional degree with at least three years of professional experience. Sound knowledge of business administration is required. As software and materials are partly taught in English, solid to good knowledge of the English language should be available.
  Further notes on participation (software / technical requirements).
• Degree: Each individual certificate course can be completed with an examination (project assignment and peer review in each case) or with a certificate of attendance (with 75% attendance). If the examination results of all three certificate courses are passed, the Certificate of Advanced Studies Hochschule Niederrhein "Data Analyst" will be awarded.