Data Science Methods

Vrije Universiteit Amsterdam

Course Description

  • Course Name

    Data Science Methods

  • Host University

    Vrije Universiteit Amsterdam

  • Location

    Amsterdam, The Netherlands

  • Area of Study

    Computer Programming, Statistics

  • Language Level

    Taught In English

  • Course Level Recommendations

    Upper

    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.

    Hours & Credits

  • ECTS Credits

    6
  • Recommended U.S. Semester Credits
    3
  • Recommended U.S. Quarter Units
    4
  • Overview

    COURSE OBJECTIVE
    This course introduces a number of methods and techniques devoted to the analysis of large data sets.

    With a special focus is on methodology, this course give the technical tools for performing valid and competent data analysis in the subsequent applied data science courses.

    COURSE CONTENT
    This course covers:
    (1) statistical methods for analyzing data;
    (2) machine learning techniques;
    (3) efficient numerical implementation of statistical and machine learning methods;
    (4) validity and methodological aspect of data analysis

    TEACHING METHODS
    Lectures and tutorials

    TYPE OF ASSESSMENT
    Exam and group assignment

    ENTRY REQUIREMENTS
    Basic knowledge of probability, statistics and programing.

Course Disclaimer

Courses and course hours of instruction are subject to change.

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