Data Analyst

Become a Data Analyst

64 student reviews.
  • Overview Learn how to find insights from data and prepare for a career in data science.
  • Type Nanodegree
  • Provider Udacity
  • Institution Facebook
  • Cost $1200
  • Effort Minimum 10hrs/week
  • Duration 6 months

Earn a Certificate

  • Nanodegree via Udacity and Facebook
  • $1200 for 6 months
  • 1:1 feedback - Rigorous, timely project and code reviews

Overview

Best-in-class curriculum, personalized instruction, close mentoring, a peerless review model, and career guidance combine to equip students of this program with the skills necessary to obtain rewarding employment as a Data Analyst.

Take the Readiness Assessment to find out if you're ready to get started.

Learn to:

  • Wrangle, extract, transform, and load data from various databases, formats, and data sources
  • Use exploratory data analysis techniques to identify meaningful relationships, patterns, or trends from complex data sets
  • Classify unlabeled data or predict into the future with applied statistics and machine learning algorithms
  • Communicate data analysis and findings through effective data visualizations

We have designed this program by working closely with expert data analysts and scientists at leading technology companies, and in partnership with their hiring managers to ensure you emerge from your degree program with the skills and talents these companies are seeking.

Why Take This Nanodegree?

This Data Analyst Nanodegree is designed to prepare you for a career in Data Science, which is quickly becoming a top priority for organizations. This program’s curriculum was developed with leading industry partners to ensure students master the most cutting-edge skills. Graduates will emerge fully prepared for this amazing career.

Required Knowledge

This program is comprised of two Terms. Depending on your existing skills and experience, you'll begin the program in either Term 1 or Term 2. To enter at Term 2, you must have:

  • Strong Python programming skills
  • Solid understanding of inferential statistics and its applications

Otherwise, you'll begin in Term 1. All students must successfully complete Term 2 to graduate.

Term 1: Data Analysis with Python and SQL

Understanding of Descriptive Statistics

  • Measures of Center
  • Measures of Spread
  • Histograms and Boxplots
  • Probability distributions

Basic Data Skills

  • Ability to work with data in a spreadsheet
  • SQL knowledge a plus

Term 2: Advanced Data Analysis

Experience programming in Python

  • Python standard libraries
  • Working with data in Pandas

Understanding of inferential statistics and probability and their applications

  • Sampling distributions
  • Standardizing data
  • A/B tests
  • Linear regression

Syllabus

Reviews for Data Analyst
Based on 64 reviews

Did you take this credential? Share your experience with other students.

Write a Review
Pravin Mhaske
Overall Rating
This was the first course I took since I started thinking about analytics and R. A fellow Data Scientist recommended it to me. I was bit surprised when I saw the level as Intermediate still decided to pursue. Duration of the course is 2 months and t…

Topic coverage

Job readiness

Community/staff support

Bruno Assis
Overall Rating
This program provided me knowledge over a lot of very important subjects related to the field (Statistics, Data Wrangling, Exploratory Data Analysis, Machine Learning, Data Visualization, and others) by going through each of them in a very good pace,…

Topic coverage

Job readiness

Community/staff support

Joe Foley
Overall Rating
I was skeptical when I enrolled in UDACITY's Data Analysis Nano Degree Program but not only have they provided the experience they said they would they have steadily made improvements since I enrolled. How many times in your life have you had that…

Topic coverage

Job readiness

Community/staff support

Class Central

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free

Never stop learning Never Stop Learning!

Get personalized course recommendations, track subjects and courses with reminders, and more.

Sign up for free