Spring 2025: March 12 — June 25
Subject: CMSC
Course Level: 200
Number of Credits: 4 U.S. / 8 ECTS
Max Enrollment: 22
Schedule: Tue, Thu 18:00 – 19:20 CET (Berlin) | 12:00 – 1:20 PM EDT (New York)
Distribution Area:Mathematics and Computing
Language of Instruction: English
Course Prerequisites: English B2 / Equivalent or higher

This course introduces students to the fundamentals of data analysis, focusing on quantitative methods using Python. No prior knowledge of advanced mathematics is required, as the course includes a review of probability theory. Students will learn about sampling concepts and types, data types, and variables. They will also explore basic statistical measures, principles of hypothesis testing, methods for testing differences between groups, and statistical analysis of relationships. Toward the end of the course, students will be introduced to the fundamentals of regression analysis, including how to run a linear regression model and interpret its results. The course will also address the limitations of quantitative research, exploring why numbers should not always be trusted and why results from statistical tests or regressions require careful interpretation. It synthesizes computer science and social science spheres, providing students with analytical tools that can be applied to solving research problems in the social sciences.

The course has an applied focus on data analysis. Whenever possible, the material is presented in a non-technical way, using empirical examples. Theoretical concepts are supplemented with practical exercises. Practical sessions will use Python, starting with instructions on setting up the Python environment and learning basic commands. Students will explore the key libraries and commands necessary for performing basic data analysis.

The skills gained in this course are valuable for both academic careers and various professional fields where data analysis is applied, such as social analysis, business analytics, finance, UX design, journalism, etc.

Learning objectives
By the end of this course, students will be able to:
Understand the fundamental concepts and methods of data analysis.
Analyze data using statistical techniques and Python libraries.
Evaluate the advantages and limitations of quantitative research methods.
Apply statistical reasoning to solve real-world social science problems.
Able to read and interpret the results of published quantitative studies in social sciences.

Course Objectives:
Understand the basics of Python programming and its application to data analysis.
Apply Python skills to conduct statistical analyses and create data visualizations.
Develop critical thinking skills in interpreting and questioning quantitative research results.
Build confidence in applying quantitative methods to analyze social science questions.

Guidelines for the Statement of Purpose:
Craft a reflective statement of purpose explaining your interest in the Smolny Beyond Borders online course. The file should be saved with your name and course title as the filename and uploaded accordingly. Your statement’s clarity and substance will significantly influence our selection. Convey your motivations and aspirations for this course succinctly but thoroughly. Kindly write your statement in the course’s Language of Instruction.

Application Portal Instructions:
1) Use the Latin alphabet for all entries on the portal, including your name. If the Language of Instruction is Russian, you may use Cyrillic only within the Statement of Purpose file, and the title of the file should still be in English.
2) Refrain from using email addresses associated with Russian or Belarusian educational institutions.
3) While completing the “Required Information” section, ensure you fill in the “Province” field for your address.
4) Provide an address outside Russia or Belarus in both the “Required Information” and “Geographic Location Confirmation” sections of the “Online Course Application”. This ensures we can send your transcript.
5) You must press the “Sign” button twice during the application.
6) If you hold a bachelor’s degree, select “4th+” in the “Academic Year (online)” section.
7) Applicants either unaffiliated or affiliated with educational institutions in Russia and Belarus should list ‘Smolny Beyond Borders’ as their educational institution.
8) In the student ID section, enter ‘SBB’.
9) Consider drafting your motivation letter ahead of time. Save it as a separate file with this format: LastName_FirstName_CourseTitle for a smoother application process.