Course description

This course introduces students to the essential tools and practices of modern data and code management, with a focus on business analytics applications.
It covers a broad spectrum of programming languages and platforms — including R, Python, SQL, GitHub, Power BI, and modern AI assistants (LLMs) — to help students design reproducible, collaborative, and impactful data workflows.

Topics covered include:

  • Reproducible research: Literate programming with RMarkdown and Jupyter Notebooks.
  • Version control & collaboration: Best practices with GitHub.
  • Programming foundations: Data structures, logical operators, control structures, and functions in R and Python.
  • Databases & SQL: Querying, joining, and aggregating data, with integration into R and Python.
  • Visualization & reporting: From exploratory analysis with ggplot2 and Python’s visualization libraries to interactive dashboards in Power BI.
  • Software engineering for data science: Functions, testing, documentation, and package creation in R/Python.
  • Web & data collection: Web scraping and APIs (using Rvest, BeautifulSoup, requests, etc.).
  • Interactive applications: Development of web apps with Shiny and Streamlit.
  • Large Language Models (LLMs): Leveraging AI assistants responsibly for code generation, documentation, and analytics.
  • Communication & dissemination: Building reproducible websites, dashboards, and reports for sharing results.

Learning outcomes

By the end of the course, students will be able to:

  • Build and manage reproducible data pipelines across R, Python, and SQL.
  • Develop and share interactive applications and dashboards.
  • Apply best practices in coding, documentation, testing, and collaboration.
  • Critically integrate AI-powered tools into their analytical workflow.
  • Deliver professional, reproducible, and transparent projects from data collection to final presentation.

No prior background in IT or programming is assumed, but students should bring curiosity and motivation to acquire hands-on programming skills that will serve them in their academic and professional careers.