Data Scientist Nanodegree

Nanodegree key: nd025

Version: 5.0.0

Locale: en-us

Get hands-on experience running data pipelines, designing experiments, building recommendation systems, and more.


Part 02 : Introduction to Data Science

Part 03 : Software Engineering

Software engineering skills are increasingly important for data scientists. In this course, you'll learn best practices for writing software. Then you'll work on your software skills by coding a Python package and a web data dashboard.

Part 04 : Data Engineering

In data engineering for data scientists, you will practice building ETL, NLP, and machine learning pipelines. This will prepare you for the project with our industry partner Figure 8.

Part 05 : Experimental Design & Recommendations

Learn to design experiments and analyze A/B test results. Explore approaches for building recommendation systems.

Part 06 : Data Scientist Capstone

Leverage what you’ve learned throughout the program to build your own open-ended Data Science project. This project will serve as a demonstration of your valuable abilities as a Data Scientist.

Part 07 : Congratulations

Congratulations on your completion of the Data Scientist Nanodegree!

Part 08 (Elective): [Capstone Content] Convolutional Neural Networks

Part 09 (Elective): [Capstone Content] Spark

Part 10 (Elective): Prerequisite: Python for Data Analysis

Part 11 (Elective): Prerequisite: SQL

Part 12 (Elective): Prerequisite: Data Visualization

Part 13 (Elective): Prerequisite: Command Line Essentials

Part 14 (Elective): Prerequisite: Git & Github

Part 15 (Elective): Prerequisite: Linear Algebra

Part 16 (Elective): Prerequisite: Practical Statistics