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Data Analysis and Visualization Pathway

With over 400 billion gigabytes of data out there and more every day, companies are paying top dollar to those who can leverage it. Strong data skills are becoming increasingly valuable - even if you choose not to become a professional data scientist. This path will help you master the skills to extract insights from data using a powerful (and easy to use) assortment of popular Python libraries.

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Learning Objectives

Learn how to extract and represent data using Python data structures, descriptive statistics, and reading from and exporting data to different types of files.

Learn how to represent data in Numpy and various vectorization operations that can be performed on code.

Learn how to use Python libraries such as Numpy and Pandas for data extraction, cleaning, and processing purposes.

Learn how to use Python libraries such as Matplotlib for data visualization after it has been cleaned and processed.

Hands-On Programs

Data Analysis and Visualization

Get started with the basics of analytics in Python, the language of choice for data science.

Data Analysis & Processing with Pandas

Learn to structure your data more effectively and do some basic analysis: group, apply functions, and more.

From Python to Numpy

Dive into NumPy! Start organizing, rearranging, and sampling your data.

Visualization using Matplotlib for Python

Explore and practice the different types of plots that are instrumental in visualizing your data.

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