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Big Data in Biomedical Sciences - Period 5
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Computer Sciences
Instruction in: English
Course Code: AB_1256
Transcript Source: Partner Institution
Course Details: Level 200
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
This elective addresses important concepts in bioinformatics and big data mining, with powerful applications in biomedical sciences. Lectures and practical assignments provide theory and hands-on experience in fast moving fields of personalized medicine, genetics, neuroscience, connectomics and metagenomics.
This course is a course on Data Analytics and Big Data. The course consist for 50% about computer assignments, which involve computer programming. The programming language during the course will be MATLAB. These computer practicals assume previous basic experience with programming (knowledge about MATLAB and general programming and/other languages (Python, C++, Java) is highly recommended). Students should otherwise have a high affinity with programming, and willing and be highly motivated to invest (a number of) extra hours before and in the first weeks of the course to come up to speed with MATLAB and general programming. To help the student, BEFORE the course the course guide will provide links for online tutorials of MATLAB as well as two computer practicals to practice before the course (practicals will be discussed in detail in the first weeks) and test the skill levels.
Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
This course is a course on Data Analytics and Big Data. The course consist for 50% about computer assignments, which involve computer programming. The programming language during the course will be MATLAB. These computer practicals assume previous basic experience with programming (knowledge about MATLAB and general programming and/other languages (Python, C++, Java) is highly recommended). Students should otherwise have a high affinity with programming, and willing and be highly motivated to invest (a number of) extra hours before and in the first weeks of the course to come up to speed with MATLAB and general programming. To help the student, BEFORE the course the course guide will provide links for online tutorials of MATLAB as well as two computer practicals to practice before the course (practicals will be discussed in detail in the first weeks) and test the skill levels.
Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA's recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
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