Data Analyst Nanodegree

Data Analyst Nanodegree

Nanodegree key: nd002

Version: 8.0.0

Locale: en-us

Learn to clean up messy data, uncover patterns and insights, make predictions using machine learning, and clearly communicate your findings.

Content

Part 01 : Welcome to Term 1!

Welcome to the program! In this part, you’ll 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 Python

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

Part 03 : Introduction to Data Analysis

Learn the data analysis process of questioning, wrangling, exploring, analyzing, and communicating data. Learn how to work with data in Python using libraries like NumPy and Pandas.

Part 04 : Practical Statistics

Learn how to apply inferential statistics and probability to important, real-world scenarios, such as analyzing A/B tests and building supervised learning models.

Part 05 : Congratulations and Next Steps

Part 06 : Welcome to Term 2!

Welcome to the program! In this part, you’ll 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 07 : Exploratory Data Analysis

Learn to explore data at multiple levels using appropriate visualizations, acquire statistical knowledge for summarizing data, and develop intuition around a data set.

Part 08 : Data Wrangling

Learn the data wrangling process of gathering, assessing, and cleaning data. Learn how to use Python to wrangle data programmatically and prepare it for deeper analysis.

Part 09 : Data Story Telling

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

Part 10 : Congratulations and Next Steps

Part 11 (Elective): How to use Git and GitHub

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

Part 12 (Career): Career: GitHub Profile Review

Technical recruiters commonly use GitHub as a recruiting platform. They are looking for activity, consistency, and communication in addition to your overall projects. Look at your GitHub profile through the lens of a recruiter or hiring manager, focusing on how your profile, projects, and code represent you as a potential candidate for a company or collaborator on a project.

Part 13 (Career): Career: Networking

Networking is a very important component to a successful job search. In the following lesson, you will learn how tell your unique story to recruiters in a succinct and professional but relatable way.

Part 14 (Career): Career: Job Search Strategies

Opportunity can come when you least expect it, so when your dream job comes along, you want to be ready.

Part 15 (Career): Career: Data Analyst Interview Practice

Now that you've practiced your skills through your project work, learn how you can present your knowledge in an interview.

Part 16 (Elective): Intro to Machine Learning

Part 17 (Elective): Matrix Math and Numpy Refresher

Part 18 (Elective): [New] Introduction to Python

Part 19 (Elective): Introduction to Python

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