Statistics and Clustering in Python

Beginner Level
2 weeks to complete at 10 hours a week
Flexible Schedule

Robert Zimmer

What You’ll Learn

In this course you will engage in a variety of mathematical and programming exercises while completing a data clustering project.

Skills You’ll Gain

Matplotlib Pandas (Python Package) Statistical Analysis Probability & Statistics Unsupervised Learning Statistics Data Science Jupyter Data Manipulation NumPy Descriptive Statistics Python Programming Data Visualization Software Machine Learning Algorithms Data analysis

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There are 4 modules in this course

This week, we will delve into the core concepts of mean, variance, and other basic statistics, laying the groundwork for a solid understanding of data analysis principles. Through hands-on exercises and demonstrations in Python and Jupyter notebooks, we'll explore practical techniques for calculating and interpreting statistical measures.

This week, we will explore mathematics for multidimensional data. You will also learn how to work with multidimensional data in Python.

This week, we will explore data manipulation and visualisation with Python's Pandas library. We will dive deep into the versatile capabilities of Pandas, empowering you to efficiently manipulate, analyse, and interpret data.

This week, we will embark on a journey through the fascinating world of unsupervised learning, where patterns emerge from data without explicit guidance. You will implement the K-means algorithm to solve a real-world problem.