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Data Science with Python

Data Science with Python

This course equips students with the essential skills of a data scientist which include data collection, cleanup, transformation, analysis, and visualization. Students will write algorithms, tell data stories, and build statistical models using Python libraries.

Course Description

You’ll discover how Python enables you to import, clean, manipulate, and visualize data. You’ll practice using some of the most well-known Python libraries, such as pandas, NumPy, Matplotlib, and many others. The statistical and machine learning techniques you’ll need to conduct hypothesis testing and create prediction models will then be taught to you while you work with actual datasets.

Course Contents

  • Data Manipulation, Joining Data with Pandas
  • Introduction to Statistics in Python
  • Introduction to Data Visualization with Matplotlib and Seaborn
  • Introduction to NumPy
  • Intermediate Data Visualization with Seaborn
  • Introduction/Intermediate Importing Data in Python
  • Exploratory Data Analysis in Python
  • Analyzing Police Activity with Pandas
  • Introduction to Regression with statsmodels in Python
  • Sampling, Hypothesis Testing in Python
  • Supervised Learning with scikit-learn
  • Unsupervised Learning in Python

What you’ll learn

  • Python core capabilities for implementing data analysis, machine learning models
  • Understand complex computer science concepts by intuitively applying them in games
  • How to use different libraries for Data Science

Course is designed for

  • Students who wants to learn Data Science
  • Students who wants to build their career in Data Science


  • Introduction to Python