Pre-Course for Statistics

Program Overview

Pre-Course for Statistics

Overview

The Pre-Course for Statistics is designed for students who wish to pursue a Master's degree in Data Science at the University of Europe for Applied Sciences (UE). This course provides students with the necessary basic knowledge of statistics, which is an admission requirement for the Data Science program.

Syllabus

The Pre-Course for Statistics covers the following topics:

• Graphical and tabular descriptive techniques
• Numerical descriptive techniques: measure of location and variability
• Correlation and Contingency
• Lineare Regression
• Probability
• Introduction to estimation

Key Facts

• Duration: 22.5 hours
• Period: Approximately 1 month
• Credits: 3 ECTS
• Start dates: Every winter and summer semester (March and September)
• Location: Online (Live & On-Demand)
• Tuition fees: € 245 (EU and Non-EU Applicants)

Admission Requirements

To apply for the Pre-Course for Statistics, students must meet the following requirements:

• Meet the admission requirements for the UE
• Provide proof of basic knowledge of statistics

Fees and Financing

For more information on tuition fees and financing options, please refer to the UE's fees and financing page.

Learn from Our Experts

Our professors are experienced in their fields and are dedicated to providing students with a high-quality education. For more information on our professors, please refer to the UE's faculty page.

Contact Us

For more information on the Pre-Course for Statistics, please contact us at the University of Europe for Applied Sciences.

Program Outline

Pre-Course for Statistics

Degree Overview:

• The Pre-Course for Statistics is designed to equip students with the fundamental statistical knowledge required for the Tech & Software Master's degree program in Data Science at the University of Europe for Applied Sciences (UE).
• It provides a foundational understanding of essential statistical concepts, allowing students to confidently pursue advanced data science studies.
• The course is also suitable for those seeking to enhance their statistical knowledge for personal or professional development.
• It focuses on practical application, enabling students to actively apply the core statistical concepts in various exercises and hands-on tasks.

Outline:

• This course comprises 22.5 hours of learning spread over approximately one month.
• It addresses essential statistical topics including:
• Graphical and tabular descriptive techniques
• Numerical descriptive techniques: measures of location and variability
• Correlation and Contingency
• Linear Regression
• Probability
• Introduction to estimation

Assessment:

• Participants are expected to complete all exercises and readings.
• Continuous assessment will be employed throughout the course.

Teaching:

• The course is designed with an engaging mix of lectures, tutorials, and exercises to deliver comprehensive understanding and hands-on experience.
• Participants learn in an interactive online environment under the guidance of experienced instructors.

Careers:

• Successful completion of the course, combined with the Tech & Software Master's degree in Data Science, equips graduates for diverse career paths in various industries requiring strong analytical and data interpretation skills.
• This program opens doors to promising employment opportunities within tech firms, consulting agencies, research organizations, and various other data-driven sectors.

Other:

• Participants can access the Pre-Course for Statistics online.
• It offers a flexible structure, catering to international students by delivering online-based learning.
• Individuals interested in joining the program are encouraged to learn more about the Tech & Software Master's degree in Data Science.