Udacity: Data Analysis with Python and SQL

(3 customer reviews)

Use Python, SQL, and statistics to uncover insights, communicate critical findings, and create data-driven solutions. Advance your programming skills and refine your ability to work with messy, complex datasets. You’ll learn to manipulate and prepare data for analysis, and create visualizations for data exploration. Finally, you’ll learn to use your data skills to tell a story with data.

Who is this course for?

If you're someone who wants to make data-driven decisions or work with various types of data to conduct analyses, or is interested in becoming a data analyst, this program is ideal for you because you'll learn applied statistics, data wrangling with Python, and data visualization with Matplotlib, which will enable you to work with any data set and find and showcase meaningful insights. This will qualify you for roles such as a Data Analyst and Analytics Consultant. You'll need to have some experience with python and pandas to succeed in this program.

Course Syllabus

Introduction to Data Analysis

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

Explore Weather Trends

In this project, you'll get familiar with SQL, and learn how to download data from a database. You’ll analyze local and global temperature data and compare the temperature trends where you live to overall global temperature trends.

Investigate A Dataset

You will choose one of Udacity's curated datasets and investigate it using NumPy and Pandas. Go through the entire data analysis process, starting by posing a question and finishing by sharing your findings.

Practical Statistics

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

Analyze Experiment Results

You will be provided a dataset reflecting data collected from an experiment. Use statistical techniques to answer questions about the data and report your conclusions and recommendations in a report.

Data Wrangling

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

Wrangle & Analyze Data

Real-world data rarely come clean. Using Python, you'll gather data from a variety of sources, assess its quality and tidiness, then clean it. You'll document your wrangling efforts in a Jupyter Notebook, plus showcase them through analyses and visualizations using Python and SQL.

Data Visualization with Python

Learn to apply visualization principles to the data analysis process. Explore data visually at multiple levels to find insights and create a compelling story.

Communicate Data Findings

You will use Python’s data visualization tools to systematically explore a selected dataset for its properties and relationships between variables. Then, you will create a presentation that communicates your findings to others.

Enrollment Inclusions

Real-world projects from industry experts

With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.

Technical mentor support

Our knowledgeable mentors guide your learning and are focused on answering your questions, motivating you, and keeping you on track.

Career services

You’ll have access to resume support, Github portfolio review, and LinkedIn profile optimization to help you advance your career and land a high-paying role.

Flexible learning program

Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.


Additional information

Course Page


Program Length

Estimated time of 4 Months At 10 hrs per week


Josh Bernhard, Sebastian Thrun, Derek Steer, Juno Lee, Mike Yi, David Venturi, Sam Nelson

Scheduled Class Batches?


Program Format

Self-paced Online Classes

Techinical or Skill Pre-requisites

In order to succeed in this program, we recommend having experience working with data in Python (specifically NumPy and Pandas) and SQL. This includes:

1. Python standard libraries
2. Working with data with Pandas and NumPy

System Requirements

For this Nanodegree program, you will need access to the Internet, and a 64-bit computer.

Additional software such as Python and its common data analysis libraries (e.g., NumPy and Pandas) will be required, but the program will guide students on how to download these once the course has begun.


Monthly Access – Pay as you go: $399 per month
– Learn at your own pace
– Cancel anytime
4-Month Access – Pay upfront and save an extra 15%: $1356
– Switch to the monthly price after if more time is needed.
– Cancel anytime.

Financing Options


Scholarship Programs


3 reviews for Udacity: Data Analysis with Python and SQL

  1. Tony Zhang

    This nanodegree is very focused on writing code while lectures are kept short and sweet. It is a beginner level course for data science, however, some experience in python is definitely required. You’ll learn strategies in data gathering, assessment, cleaning, analysis and communication, while completing really challenging and “resume worthy” projects. There are additional resources to improve your GitHub and LinkedIn profiles. I was able to complete this nanodegree in 24 days and within the free month so I didn’t have to pay. All things considered, I had a lot of fun completing this nanodegree, was able to complete two really strong projects for my personal portfolio, and my greatly improve my competency in both python and data analysis.

  2. Ong Kam Siong

    Mentors are here to review each project. From my experience, some mentors are kind enough to recommend valuable resources for data wrangling or visualization. This is very different from Coursera. Students who are as good/worst as me reviewed my projects. Sometimes, there isn’t anyone to review my project because nobody is interested in the course. Can you imagine I paid for a course and end up dropping out just because of this reason? GitHub/LinkedIn profile review and career services might be helpful, but I never use such a service. The reason being, I’m not ready for a career transition at this point. I want to build strong fundamentals in Python & R and learn more about Cloud Analytics (GCP/AWS) for data science.

    I wish Udacity would offer more courses for R programming in the future. I understand that Udacity offers courses based on industry trends that favor Python; however, some students, including myself, prefer R over Python.

  3. Aqsa Z.

    Udacity Data Analyst Nanodegree is good for those who have prior knowledge of Python (specifically NumPy and Pandas) and SQL and want to advance their skills in Data Analysis. Udacity Data Analyst Nanodegree is combined with various Real-World projects and provides One-to-One Mentorship. If you are a beginner with no Python knowledge, I would not recommend this Udacity Data Analyst Nanodegree. Udacity Nanodegree program is expensive as compared to other MOOCs platforms. After completing the Nanodegree program, you can’t access the course material. Maybe Udacity does this to avoid misuse. Udacity doesn’t have any IOS and android app. So, you can’t study on your smartphones and outside the house.

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