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Phase 2 • Data Analytics & Workflows

Phase 2 introduces the essential data science stack. Learners master NumPy, Pandas, SQL databases, APIs, statistical analysis, and visualization to build complete analytical workflows from data acquisition to insight communication.

What you will practice

  • Numerical computing with NumPy arrays and vectorized operations.
  • Data manipulation and analysis with Pandas DataFrames.
  • Cleaning and preparing messy real-world datasets.
  • Statistical analysis and hypothesis testing for business decisions.
  • Creating compelling visualizations with Matplotlib, Seaborn, and Plotly.
  • Extracting data from databases, APIs, and web scraping.
  • Building simple web applications and APIs with Flask.

Lesson sprint

Learning outcomes

By completing Phase 2, you will be able to:

  • Perform complex data transformations and aggregations with Pandas.
  • Execute statistical analyses to support business decisions.
  • Create compelling visualizations that communicate insights effectively.
  • Acquire data from multiple sources (databases, APIs, web).
  • Build end-to-end analytical workflows from data to insight.

Ready to continue? Advance to Phase 3 – Machine Learning Foundations to build predictive models.