Programming for Data Science with Python

Nanodegree key: nd104

Version: 3.0.0

Locale: en-us

Learn programming skills needed to uncover patterns and insights in large data sets, running queries with relational databases and working with Unix shell and Git.

Content

Part 01 : Welcome to the Program

Welcome to the program! In this part, you will get an orientation into using our classroom and services. You’ll also get advice for making the best use of your time while enrolled in this program.

Part 02 : Introduction to SQL

Learn SQL language fundamentals such as building basic queries and advanced functions like Window Functions, Subqueries and Common Table Expressions.

Part 03 : Command Line Essentials

The Unix shell is a powerful tool for developers of all sorts. In this lesson, you'll get a quick introduction to the very basics of using it on your own computer.

Part 04 : Introduction to Python

Learn Python programming fundamentals such as data types and structures, variables, loops, and functions.

Part 05 : Introduction to Version Control

Learn how to use version control to save and share your projects with others.

Part 06 : Career Services

These Career Services will ensure you make meaningful connections with industry professionals to accelerate your career growth - whether looking for a job or opportunities to collaborate with your peers. Unlike your Nanodegree projects, you do not need to meet specifications on these Services to progress in your program. Submit these Career Services once, and get honest, personalized feedback and next steps from Udacity Career Coaches!

Part 07 : Congratulations and Next Steps

Congratulations on completing all projects for this Nanodegree!

Part 08 (Elective): SQL Project Additional Resources

Part 09 (Elective): Data Visualization with Tableau

Learn to apply sound design and data visualization principles to the data analysis process. Learn how to use analysis and visualizations in Tableau to tell a story with data.

Part 10 (Elective): Introduction to HTML and CSS

Introduction to HTML and CSS syntax with problem sets.