Course Overview

This course is Data Science for Social Sciences. This course will provide an understanding of the fundamental principles and applications of Data Science. A special focus of the course will be to illustrate the utility of Data Science in Social Science studies. Basic techniques for data obtaining, wrangling, curating, managing, processing, exploring, questioning, analysing, and communicating the result will be introduced. Ethical and reproducibility issues will also be discussed.

Learning Achievement

On successful completion of this course, a student will be expected to be able to:
- Understand the basic principles and theories and descriptive approaches of Data Science.
- Planning, acquisition, management, analysis, and Inference
- Practical Data Science using RStudio
- Case-based focus on real-world applications
- Hands-on approach through frequent project-based

Competence

We are living in the era of data revolution, where data become as a new currency. Data comes in many type and format, and social sciences need to understand how to use it for social research. This course will provide an understanding of the fundamental principles and applications of data science for student with social science background. This course is designed so that social science's students also have competence in data science to contribute and solve modern problems.

Course prerequisites

There is no prerequisites

Grading Philosophy

-Individual assignment on advanced level project (40%)
-Individual project presentation (40%)
-Group/individual assignment (20%)

Course schedule

Each week we will learn and discuss about data science. If we have time, we will learn and practice using R language each week
Introduction to Data Science & Process of Data Science
Data Types & Measurement Scale
Data Exploration and Preprocessing
Statistics Descriptive & Inferential
Data Visualisation & Uncertainty
Measuring Uncertainty
Type of Research Question & Types and Source of Error
Algorithm and RStudio Software Concept I (Exploratory Analysis)
Algorithm and RStudio Software Concept II (Explanatory Analysis)
Ethics, Reproducibility & Limitation of Data Science

Course type

Lectures

Online Course Requirement

Instructor

RAMDANI Fatwa

Other information

(1) Please download and install R and RStudio software prior to begin the course.
(2) Since we have practices using RStudio, always bring your own laptop to the class
(3) Don't be afraid or hesitate to ask or consult with me during the working hours (my office is 3K314)

Site for Inquiry

Link to the syllabus provided by the university