Data Science is revolutionizing the way we interact with information. Businesses, governments and individuals are collecting more data than ever before - unlocking a wealth of knowledge that has the potential to dramatically improve our lives. Data analysis technology can be used to predict customer behavior be it in relation to movies, clothes or food. It can detect diseases earlier on in their progression before they become visible to the human eye and also help police anticipate where future crimes may occur. As this field grows so does its power; allowing us deeper insight into how things work from every angle – both inside and out!

The Data Science Minor at Inholland Diemen provides students with a comprehensive exploration into the world of Data Science. Through theoretical instruction and practical application, students gain an understanding of both the mathematical workings as well as various technologies like scikit-learn, MongoDB, Azure and more. The program culminates in an interdisciplinary group project where participants collaborate to resolve real life client company issues through their skills & knowledge acquired throughout. Join us as we explore the exciting possibilities of making data science part of your education!

The Minor in Machine Learning is an exciting and comprehensive program; students are exposed to a wide range of cutting-edge topics. Students are guided through key topics like major ML techniques from NoSQL databases, GIS systems for location analysis and NLP applications so the course provides ample opportunities to explore. With attention on ethical and legal considerations when dealing with data – this minor offers you not just knowledge but insight into responsible decision making as well! And once completed – learners will be assessed through exams, assignments and collaborative projects demonstrating their newfound skillset across disciplines.

After completing the minor the student is able to:

• Train Machine Learning models for real-world tasks.
• Use NoSQL databases to store and retrieve unstructured and semi-structured data.
• Parallelize algorithms and run them in the cloud.
• Use Natural Language Processing to analyze text documents.
• Use Geographical Information Systems to analyze geospatial data.
• Set-up and conduct literature review.
• Identify ethical and legal aspects of data science projects.

The minor is open for 3rd and 4th year bachelor students. The following skills are required:

• Python programming
• Basic statistics
• Basic algebra
• Databases/SQL

If you are unsure if the minor fits your skills or ambitions, you can contact the program at Vanessa.Fernand@inholland.nl.

The Data Science minor spans over a period of 20 weeks.

Contact hours: maximum 3 days per week at school

Term 1: Data Science Building Blocks

This course provides an in-depth introduction to Machine Learning which is an essential tool for data analysis. It introduces students to its fundamental techniques such as pre-processing, regression analysis and clustering and giving them a comprehensive overview of the field.

Data Engineering and Cloud Computing takes it one step further by exposing students to data sets that are too large for any single machine – teaching how best store and process such information using NoSQL databases as well as distribution through cloud computing solutions. Our curriculum promises an overview on all aspects of computer-assisted learning combined with opportunities for hands-on experience!

Whenever we deal with private and sensitive data, ethical issues arise. The course Professional Skills: Data Science Ethics discusses ethical and legal aspects of data science,  so that students become aware of their responsibilities as a data scientist.

Courses:

• Machine Learning (6 EC)
• Data Engineering and Cloud Computing (5 EC)
• Professional Skills: Data Science Ethics (3 EC)

Term 2: Applications of Data Science

Data Science provides a powerful way to explore and solve real-world problems. In the second term of our Minor, we're offering courses that give students an opportunity to analyse location data using Geographical Information Systems (GIS) and text with Natural Language Processing - equipping them for creative problem solving at scale! Students will get hands-on experience in their Project Data Science, working in interdisciplinary teams, applying theory directly by tackling relevant issues facing industry today. The project will be followed by a Learning Challenge.

• Geographic Information Systems (4 EC)

• Natural Language Processing (4 EC)
• Project Data Science (5 EC)
• Learning Challenge (1 EC)
• Research: literature review (2 EC)