Getting Started with Data Analysis

The following content is broken into two core pieces:

Introduction To Dictionaries

Before you dive into the full Intro to Data Analysis course, you'll need a solid understanding of dictionaries. If you decide to enroll in the Data Analyst Nanodegree program, you will need this as a prerequisite as well. The following content on dictionaries comes from the same course as much of the concepts you covered in Code Your Own Quiz.

Intro to Data Analysis

You will be taking Intro to Data Analysis with Caroline. This course is a good first step towards understanding the data analysis process as a whole. Before delving into each individual phase, it is important to learn the difference between all phases of the process and how they relate to each other. This course also covers the Python libraries: NumPy, Pandas, and Matplotlib, which are indispensable tools for doing data analysis in Python. Their many convenient functions and high performance make writing data analysis code a lot easier!

This course will require that you search and utilize documentation. Don’t hesitate to search through the documentation that exists for the Python libraries covered in this course:

The next two lessons will direct you to set up your computer by installing the Anaconda distribution and Jupyter Notebook -- two very useful tools for data analysts.

As you make your way through these installation instructions, you'll see that students in the Data Analyst Nanodegree are encouraged to set up a Python 3 environment. We recommend setting up a Python 3 environment and a Python 2 environment, as both will be useful for the content that follows.

Also, note that the forum links provided in the following course material is only accessible to students enrolled in the Data Analyst Nanodegree. For questions, visit the IPND forums.

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