Understand the foundations of Data Analytics
  • Explore the role of Data Analytics in solving practical problems and supporting decisions
  • Learn about key data types, quality issues, and typical steps in analysis workflows
  • Recognize common challenges and methods used in analytical thinking


Master data cleaning and preparation techniques
  • Identify and address missing data, duplicates, and formatting issues using pandas
  • Structure and transform raw data to enable effective analysis
  • Build consistent workflows for preparing data using Python-based tools


Apply core analytical thinking to real-world problems
  • Define data-driven questions and apply techniques such as aggregation and visualization
  • Explore trends, patterns, and relationships using tools like matplotlib and SQL
  • Translate data insights into organized outputs for further interpretation


Build a skillset that supports ongoing work in Data Analytics
  • Gain hands-on experience through practice-based projects
  • Strengthen confidence in cleaning, analyzing, and visualizing real datasets
  • Establish a solid foundation for more advanced work in the Data Analytics field