About this Course

The Introduction to Data Science class will survey the foundational topics in data science, namely:

  • Data Manipulation
  • Data Analysis with Statistics and Machine Learning
  • Data Communication with Information Visualization
  • Data at Scale -- Working with Big Data

The class will focus on breadth and present the topics briefly instead of focusing on a single topic in depth. This will give you the opportunity to sample and apply the basic techniques of data science.

This course is also a part of our Data Analyst Nanodegree.

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Course Cost
Free
Timeline
Approx. 2 months
Skill Level
Udacity
Intermediate
Included in Course
  • Icon cop 01 Rich Learning Content

  • Icon cop 02 Interactive Quizzes

  • Icon cop 03 Taught by Industry Pros

  • Icon cop 04 Self-Paced Learning

  • Icon cop 05 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 Science

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

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Course Leads

  • Dave Holtz
    Dave Holtz

    Instructor

  • Cheng-Han Lee
    Cheng-Han Lee

    Instructor

What You Will Learn

Lesson 1

Introduction to Data Science

  • Pi-Chaun (Data Scientist @ Google): What is Data Science?
  • Gabor (Data Scientist @ Twitter): What is Data Science?
  • Problems solved by data science.
Lesson 1

Introduction to Data Science

  • Pi-Chaun (Data Scientist @ Google): What is Data Science?
  • Gabor (Data Scientist @ Twitter): What is Data Science?
  • Problems solved by data science.
Lesson 2

Data Wrangling

  • What is Data Wrangling?
  • Acquiring data.
  • Common data formats.
Lesson 2

Data Wrangling

  • What is Data Wrangling?
  • Acquiring data.
  • Common data formats.
Lesson 3

Data Analysis

  • Statistical rigor.
  • Kurt (Data Scientist @ Twitter) - Why is Stats Useful?
  • Introduction to normal distribution.
Lesson 3

Data Analysis

  • Statistical rigor.
  • Kurt (Data Scientist @ Twitter) - Why is Stats Useful?
  • Introduction to normal distribution.
Lesson 4

Data Visualization

  • Effective information visualization.
  • An analysis of Napoleon's invasion of Russia!
  • Don (Principal Data Scientist @ AT&T): Communicating Findings.
Lesson 4

Data Visualization

  • Effective information visualization.
  • An analysis of Napoleon's invasion of Russia!
  • Don (Principal Data Scientist @ AT&T): Communicating Findings.
Lesson 5

MapReduce

  • Introduction to Big Data and MapReduce.
  • Learn the basics of MapReduce.
  • Mapper.
Lesson 5

MapReduce

  • Introduction to Big Data and MapReduce.
  • Learn the basics of MapReduce.
  • Mapper.

Prerequisites and Requirements

The ideal students for this class are prepared individuals who have:

  • Strong interest in data science
  • Background in intro level statistics
  • Python programming experience
  • Or understanding of programming concepts such as variables, functions, loops, and basic python data structures like lists and dictionaries

If you need to brush up on your programming, we highly recommend Introduction to Computer Science: Building a Search Engine. If you need a refresher on statistics, enroll in Intro to Descriptive Statistics and Intro to Inferential Statisitics. All three are on Udacity!

See the Technology Requirements for using Udacity.

Why Take This Course

You will have an opportunity to work through a data science project end to end, from analyzing a dataset to visualizing and communicating your data analysis.

Through working on the class project, you will be exposed to and understand the skills that are needed to become a data scientist yourself.

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