The information available today exceeds all limits. Access to this abundance of data is only possible via search engines and sophisticated information processing applications. To enable the transition from raw data to well-structured knowledge, technologies such as natural language processing, information retrieval, data and knowledge mining must be applied. In the course of this transition, unstructured data such as natural language text, is analyzed based on statistical language models and machine learning, to represent the contained information with the help of formal knowledge representations. In general, “Information Service Engineering” covers the conceptualization, development, and maintenance of long-term operation of services for the exploitation, processing, and dissemination of information. In this lecture, students will learn the fundamentals of natural language processing, knowledge mining, machine learning, linked data engineering, as well as information retrieval required for the development of information services.

Join openHPI's official Twitter Feed: @openHPI

General Course Information:

• Course language: English
• Weekly workload: 3 - 4 hours (Depending on your level of knowledge, this time may vary)
• Course duration: 6 weeks from April 16 to May 28, 2018
• Course Participants have two weeks after the course is completed to submit the Final Exam
• Deadline for the Final Exam: June 11, 2018

Requirements for this course:

• a basic understanding of web technologies, such as URL and HTTP
• a basic understanding of mathematics, esp. statistics and probability theory
• a basic knowledge of database technology such as relational databases and SQL query language

Intended Audience

• students of computer science or related subjects on the bachelor or master level
• researchers and scientists interested in natural language processing, linked data engineering, and machine learning
• young professionals, esp. knowledge engineers, data & web scientists