Project Big Data
Vrije Universiteit Amsterdam
Amsterdam, The Netherlands
Area of Study
Taught In English
Course Level Recommendations
ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.
Recommended U.S. Semester Credits3
Recommended U.S. Quarter Units4
Hours & Credits
After completing this course:
1. the student can transform and explore data with the command line
2. the student can extract data with regular expressions
3. the student can import and process static and streaming data in Python
4. the student can store and retrieve semi-structured data in and from a database
5. the student can parallelize tasks via MapReduce, threads and/or queues in Python.
6. the student can create appropriate and well formatted visualizations and tables
7. the student can address a research question and report on their findings
This course aims to integrate various aspects involved with data science and to teach the fundamentals of working with big data (including an introduction to Hadoop). Topics include visualization of data; preparing data for processing (machine learning or data mining); storing unstructured data; and scaling techniques for working with big volumes of data. Python is used throughout this hands-on course.
Lectures and Q&A sessions.
TYPE OF ASSESSMENT
Hand-in assignments, presentation and a report.
Assignment week 1: 15%
Assignment week 2: 15%
Assignment week 3: 15%
The weighted average needs to be 5.5 or higher.
Programming experience in any language
Courses and course hours of instruction are subject to change.
Some courses may require additional fees.