Statistics & Probability for Data Analysis — core math for analytics

Categories: CSE, Data Science
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About Course

The Statistics & Probability for Data Analysis course builds the mathematical foundation required for analytics, machine learning, and AI.
You’ll learn how to interpret data, understand uncertainty, and make predictions through statistical reasoning and probability theory.

This course simplifies core mathematical concepts — focusing on how they’re applied in data analysis, forecasting, and decision-making using Python and real datasets.

By the end, you’ll confidently apply statistical inference, probability distributions, and hypothesis testing to draw meaningful conclusions from data — preparing you for higher-level courses like Machine Learning, Data Analytics, and AI.

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What Will You Learn?

  • Understand descriptive and inferential statistics fundamentals.
  • Work with data distributions, central tendency, and variability.
  • Apply probability theory to real-world analytics problems.
  • Learn random variables, Bayes’ theorem, and conditional probability.
  • Use sampling techniques and estimation methods.
  • Conduct hypothesis testing and regression analysis.
  • Apply Python for statistical computations and visualization.
  • Translate numbers into actionable data insights.

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