Statistics with Python Using NumPy, Pandas, and SciPy

Coursera MOOC / Non-credit USD 49
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Statistics with Python Using NumPy, Pandas, and SciPy

About this course

“Statistics with Python Using NumPy, Pandas, and SciPy” explores how to apply statistical and mathematical techniques to data science problems. Throughout the first half of the course, you’ll work on reviewing vector dot products, interpreting text as vectors, and matrix multiplication. You’ll also explore the basics of probability, laying the groundwork for statistical analysis. In the second half, you’ll cover how to interpret data distributions, reason about probability, explore the special properties of normal distributions, understand linear relationships in data, and the connection between probability and uncertainty. This is the third course in the four-course series “Data-Oriented Python Programming and Debugging,” where you’ll work to strengthen your programming capabilities and enhance your problem-solving skills.

What you'll learn

  • understanding vector dot products
  • performing matrix multiplication
  • applying basic probability concepts
  • interpreting data distributions
  • analyzing normal distributions
  • exploring linear relationships in data
  • connecting probability with uncertainty

Course objectives

  • strengthen programming and problem-solving skills
  • apply statistical techniques to Data Science problems

Skills you'll gain

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