About this Course

This course will introduce you to the world of data analysis. You'll learn how to go through the entire data analysis process, which includes:

  • Posing a question
  • Wrangling your data into a format you can use and fixing any problems with it
  • Exploring the data, finding patterns in it, and building your intuition about it
  • Drawing conclusions and/or making predictions
  • Communicating your findings

You'll also learn how to use the Python libraries NumPy, Pandas, and Matplotlib to write code that's cleaner, more concise, and runs faster.

This course is part of the Data Analyst Nanodegree.

Course Cost
Free
Timeline
Approx. 6 weeks
Skill Level
Beginner
Included in Course
  • Icon course 01 3edf6b45629a2e8f1b490e1fb1516899e98b3b30db721466e83b1a1c16e237b1 Rich Learning Content

  • Icon course 04 2edd94a12ef9e5f0ebe04f6c9f6ae2c89e5efba5fd0b703c60f65837f8b54430 Interactive Quizzes

  • Icon course 02 2d90171a3a467a7d4613c7c615f15093d7402c66f2cf9a5ab4bcf11a4958aa33 Taught by Industry Pros

  • Icon course 05 237542f88ede3178ac4845d4bebf431ddd36d9c3c35aedfbd92e148c1c7361c6 Self-Paced Learning

  • Icon course 03 142f0532acf4fa030d680f5cb3babed8007e9ac853d0a3bf731fa30a7869db3a Student Support Community

Join the Path to Greatness

This free course is your first step towards a new career with the Data Analyst Nanodegree Program.

Free Course

Intro to Data Analysis

Enhance your skill set and boost your hirability through innovative, independent learning.

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Course Leads

  • Caroline Buckey
    Caroline Buckey

    Instructor

What You Will Learn

Lesson 1

Data Analysis Process

  • Learn about the data analysis process.
  • Pose a question, wrangle your data, draw conclusions and/or make predictions.
  • Complete an analysis of Udacity student data using pure Python, with few additional libraries.
Lesson 1

Data Analysis Process

  • Learn about the data analysis process.
  • Pose a question, wrangle your data, draw conclusions and/or make predictions.
  • Complete an analysis of Udacity student data using pure Python, with few additional libraries.
Lesson 2

NumPy and Pandas for 1D Data

  • Start learning to use NumPy and Pandas to make the data analysis process easier.
  • Features that apply to one-dimensional data.
  • Learn to use NumPy arrays, Pandas Series, and vectorized operations.
Lesson 2

NumPy and Pandas for 1D Data

  • Start learning to use NumPy and Pandas to make the data analysis process easier.
  • Features that apply to one-dimensional data.
  • Learn to use NumPy arrays, Pandas Series, and vectorized operations.
Lesson 3

NumPy and Pandas for 2D Data

  • Continue learning about NumPy and Pandas, this time focusing on two-dimensional data.
  • Learn to use two-dimensional NumPy arrays and Pandas DataFrames.
  • Group your data and to combine data from multiple files.
Lesson 3

NumPy and Pandas for 2D Data

  • Continue learning about NumPy and Pandas, this time focusing on two-dimensional data.
  • Learn to use two-dimensional NumPy arrays and Pandas DataFrames.
  • Group your data and to combine data from multiple files.
Lesson 4

Investigate a Dataset

  • Use NumPy and Pandas to go through the data analysis process on one of a list of recommended datasets.
Lesson 4

Investigate a Dataset

  • Use NumPy and Pandas to go through the data analysis process on one of a list of recommended datasets.

Prerequisites and Requirements

To take this course, you need to be comfortable programming in Python.

  • You should be familiar with if statements, loops, functions, lists, sets, and dictionaries. To learn about any of these topics, take the course Intro to Computer Science.
  • You should also be familiar with classes, objects, and modules. To learn about these topics, take the course Programming Foundations with Python.

See the Technology Requirements for using Udacity.

Why Take This Course

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. After taking this course, you will be better positioned to succeed in other courses in the Data Analyst Nanodegree program. For example, a student who started with Data Analysis with R, which covers the exploratory data analysis phase, might not understand at that point the difference between data exploration and data wrangling. By taking this course first, you will learn what each phase accomplishes and how it fits into the larger process.

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!

What do I get?
  • Instructor videos
  • Learn by doing exercises
  • Taught by industry professionals

Thanks for your interest!

We'll be in touch soon.

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