By Ong Kam Siong, Data Analyst Nanodegree graduate (February 2021). Last updated: 13 October 2026 (syllabus, projects, prices and ratings re-checked on Udacity’s nd002 page that day). Editorial update by Josh Hutcheson, OnlineCourseing editor. See our review methodology.
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QUICK CONTEXT: THE DATA ANALYST NANODEGREE IN 2026
The current Data Analyst Nanodegree (nd002) is a 43-hour intermediate program of three Python courses: data analysis with pandas and NumPy, visualization with Matplotlib and Seaborn, and advanced data wrangling. It has three reviewed projects and is rated 4.8 from 1,310 reviews on Udacity’s page. SQL, A/B testing and Tableau are no longer taught in it; basic SQL and statistics are prerequisites.
Ong Kam Siong completed the earlier, five-project version in February 2021. His account follows our editorial verdict, with notes where today’s program differs.
QUICK VERDICT
Our rating: 4.2 / 5
- Best for: learners who already know basic Python and SQL and want reviewed, portfolio-ready projects in pandas, data wrangling and visualization within about two months.
- Not for: complete beginners, people who need SQL, Tableau or Power BI taught from scratch, and anyone choosing on price alone.
Bottom line: one of Udacity’s best-rated programs, with three substantial projects on real, messy data and human code review. It is shorter and narrower than it used to be, and at $249 a month it costs more than Coursera’s analyst certificates, so it suits people who already have the basics and want reviewed practice.
Check the current Nanodegree price →
In this Udacity Data Analyst Nanodegree review, Ong explains how the program helped him move from Excel-based finance work to analyzing data sets too large for spreadsheets.
The Data Analyst Nanodegree at a glance (13 October 2026)
| Detail | Current program |
|---|---|
| Program | Data Analyst Nanodegree (nd002) |
| Level | Intermediate (Udacity’s label) |
| Estimated time | 43 hours |
| Structure | 3 content courses, 17 lessons, 3 reviewed projects |
| Prerequisites | Basic Python, basic SQL, file I/O, elementary algebra, descriptive and inferential statistics |
| Tools | Python, pandas, NumPy, Matplotlib, Seaborn, Jupyter notebooks |
| Projects | Investigate a Dataset; Communicate Data Findings; Real World Data Wrangling with Python |
| Rating on Udacity | 4.8 from 1,310 reviews |
| Last updated by Udacity | August 25, 2026 |
| Price | $249/month, $846 for 4 months, or $999 one-time |
Source: Udacity’s nd002 program page, read 13 October 2026.
About me & my motivation
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In February 2021 I completed Udacity’s Data Analyst Nanodegree. I want to share some key takeaways that will help anyone who wants to become a data analyst. First, a little about my background and the self-development journey that led me to Udacity.
I was a finance analyst with eight years of professional experience at companies including IBM and HP. I held roles in finance, planning and analysis (budgeting, forecasting and analyzing business outcomes), and in audit and tax. The go-to tool for a finance analyst is Excel, and I am confident it handles many finance tasks as long as the data fits.
I ran into its limits in audit and tax. An annual audit often needs a full year of detailed transactions for one entity or a group of entities in a region, usually in CSV or XLSX files of 100 MB or more, and Excel does not perform well at that size. So I looked for alternatives that could handle financial analysis on large data sets.
Over the years I tried MOOCs on Coursera, edX and DataCamp and picked up basic SQL, Tableau, Python and R, but those courses were taught in an academic context. In 2016 I enrolled in Udacity’s Data Foundation Nanodegree and finally found a platform that teaches practical, real-world skills. After a few years of self-study in SQL, Python and R, and reading other reviews of the Data Analyst Nanodegree, I decided to give it a try.
This review answers two questions: is the Data Analyst Nanodegree worth it, and will it help you land a job?
Right price at the right time
In November 2020 I signed up at a 75% discount, about $100 a month. I chose monthly payments rather than the four-month upfront plan and graduated in three months.
Udacity courses are more expensive than most MOOCs. Coursera, for example, offers data analyst professional certificates that cover much of the same ground. I think the price is justified because Udacity gives career advice on your LinkedIn and GitHub profiles, mentors answer students’ questions, and above all it teaches practical, real-world skills through its projects.
Editor’s note: what the price looks like now
The 75% discount Ong used was a 2020 promotion. On 13 October 2026 Udacity’s page listed $249 a month, $846 for a four-month bundle or $999 one-time, and Udacity shows personalized new-user offers at times. The full cost breakdown is in the cost section below.
Course structure & projects of Udacity’s Data Analyst Nanodegree
The current structure (editorial update, 13 October 2026)
| Course | Hours | Lessons | Project |
|---|---|---|---|
| Introduction to Data Analysis with Pandas and NumPy | 14.0 | The data analysis process; Jupyter notebooks; exploring and inspecting data; manipulating data with pandas and NumPy; communicating results | Investigate a Dataset |
| Data Visualization with Matplotlib and Seaborn | 14.5 | Visualization in data analysis; design of visualizations; univariate, bivariate and multivariate exploration; explanatory visualizations | Communicate Data Findings |
| Advanced Data Wrangling | 14.5 | Introduction to data wrangling; gathering data; assessing data; cleaning data | Real World Data Wrangling with Python |
The instructors are Josh Magee (Senior Data Scientist), Ria Cheruvu (AI Software Architect) and Matt Maybeno (Senior Applied ML Engineer). Compared with Ong’s 2021 version, the SQL project and the practical statistics course with its A/B test project are gone, and the program starts directly with pandas. A July 2026 reviewer on Udacity’s page praised exactly that structure: every course ends with a project on real, messy data handled end to end.
Ong’s 2021 program, course by course
Welcome to the Data Analyst Nanodegree
An orientation for students and an introduction to SQL. The very first project was Explore Weather Trends: extract data from Udacity’s database with SQL and present findings in a report.
This project gave students freedom to use any SQL they knew to get the data. I learned about subqueries, temporary tables, joins, extracting substrings and more, and was tested with multiple-choice questions that I sometimes misunderstood. After gathering the data I could analyze and present it in any tool, including Excel or Google Sheets. I chose R, my most comfortable language. This flexibility, implementation over information, is what I liked most about Udacity.
Introduction to Data Analysis
This lesson introduced Anaconda, Jupyter Notebook and Python tools, and the real challenge started here.
Project: Investigate a Dataset
I chose a predefined data set from a real business or from Kaggle to investigate. One thing separates Udacity from other MOOCs: most MOOCs test technical skills with fill-in-the-blank multiple choice, while every Data Analyst Nanodegree project had to meet industry standards such as PEP 8 coding style, sensible variable names and proper use of functions, on top of presenting the findings.
Practical Statistics
This course introduced descriptive statistics, probability, distributions, hypothesis testing, A/B tests and regression, with hands-on calculations in NumPy rather than theory alone. It was challenging for me because I had been out of school for ten years and my finance work was not centered on statistics. I was glad to refresh it without an advanced textbook. The course ended with an A/B test analysis of an e-commerce landing page, which I passed after a few days of practice.
Data Wrangling
Another challenging course: the data wrangling workflow of gathering, assessing, cleaning, analyzing and presenting data with visualizations.
Project: Wrangle and Analyze Data
I expected this to be the easiest project because I had been learning Python and R for a while, and I was wrong. The data came from a popular social media account in pieces: a CSV file, a TSV file downloaded programmatically from a URL, data pulled through the platform’s Python API, and an image-prediction file. I spent days just getting data in different formats from different sources into shape and merging it. I also had to judge which parts were useful, and there was no single right answer.
The data set was about user comments, ratings and image predictions, so I extracted words from comments and analyzed ratings. It showed me how hard it is to pull keywords from real comments, and why data scientists are said to spend most of their time cleaning data.
Data Visualization
The final course covered visualization in Python with Matplotlib and Seaborn. Real-world problems are never easy, and visualization gets harder with large data sets.
Project: Communicate Data Findings
I analyzed US bike-sharing data, combining 2019’s monthly files into a full-year data set of more than 1 GB and 20 million observations. Exploratory analysis and visualization at that size required a major upgrade of my Python skills. I learned to import large data sets in chunks, use NumPy and pandas to cut processing time, and improve my Matplotlib and Seaborn work, especially Matplotlib’s object-oriented interface.
See the current Data Analyst syllabus →
How is Udacity Data Analyst Nanodegree?
Beyond the challenging projects, a few points are worth mentioning.
- Mentors review each project. In my experience some reviewers recommended valuable resources for data wrangling and visualization. This is very different from Coursera, where students as good or as weak as me reviewed my projects, and sometimes nobody reviewed them at all because nobody else was taking the course. Imagine paying for a course and dropping out for that reason.
- GitHub and LinkedIn profile reviews and career services may be helpful, but I did not use them because I was not ready for a career move. I wanted to build strong Python and R fundamentals and learn cloud analytics on GCP and AWS.
- Following from that, I wish Udacity offered more R. I understand it follows industry trends that favor Python, but some students, including me, prefer R.
What other learners say (editorial update)
Udacity’s page shows 4.8 from 1,310 reviews, and the most recent ones (June to September 2026) are five-star, praising clear requirements and project resources. Udacity as a company is rated 4.5 from 3,406 reviews on Trustpilot. In the 60 newest reviews (29 August to 12 October 2026), 43 were five-star and praised the projects and code reviews; the few low-star reviews complained about slow project reviews and support tickets, broken workspace terminals, and errors in newer courses. On Reddit, a 2020 r/Udacity thread asking whether Nanodegrees are useful drew a reply from a business analyst consultant who said the Data Analyst Nanodegree changed how he works with data and that clients noticed the difference in his reports. Other commenters made the point graduates repeat everywhere: put the projects on your resume, not the certificate. A 2018 thread also records that Udacity has restructured this program before, so expect the syllabus to keep changing.
Explore More Courses
Looking for more options? Browse our Best Data Analysis Courses and Best Data Science Courses roundups to compare courses across platforms. If you would rather learn SQL and Tableau than Python, Udacity’s Business Analytics Nanodegree (40 hours, no prerequisites) or Power BI Nanodegree are closer fits.
How much does the Udacity Data Analyst Nanodegree cost?
Udacity sells the Data Analyst Nanodegree by subscription rather than one upfront fee, so your total depends on how fast you finish. On 13 October 2026 its program page listed:
| Plan | Price | Likely total for 43 hours |
|---|---|---|
| Monthly | $249 a month, cancel any time | $498 if you finish in two months |
| 4-month bundle | $846 (about $212 a month) | $846; worth it only if you add another program |
| One-time purchase | $999 for this program | Rarely the best value for a 43-hour program |
The earlier figures on this page ($125 a month, about $423 for four months) came from older promotions and are out of date. Udacity’s Terms of Use give seven days from your first purchase to cancel for a full refund. For comparison, the Google Data Analytics Professional Certificate is 9 courses estimated at six months, and the IBM Data Analyst Professional Certificate is 11 courses estimated at four months at 10 hours a week, both on a Coursera subscription.
| Your pace | Time to finish | Likely cost |
|---|---|---|
| 15 hours a week | About 4 to 5 weeks | $249 to $498 |
| 10 hours a week | About 2 months | $498 |
| 5 hours a week | 3 to 4 months | $846 (bundle) |
Data analyst pay: what the official data says
The US Bureau of Labor Statistics does not track data analysts as a separate occupation. The closest occupations it reports are operations research analysts, with a median of $88,940 in May 2025, management analysts at $101,860, and data scientists at $120,230 with 35% projected growth from 2025 to 2035. Entry-level analyst pay is usually below these medians.
Data Analyst vs Data Scientist Nanodegree: which should you pick?
These two Udacity programs are often confused. The Data Analyst Nanodegree (this review) focuses on wrangling, analyzing and communicating data in Python, which is the daily work of an analyst. The Data Scientist Nanodegree goes further into machine learning, modeling and software practice, and assumes more programming and statistics. If you are aiming for an analyst role, start here. If you already analyze data and want to move into modeling, read our Udacity Data Scientist Nanodegree review instead.
| Data Analyst (nd002) | Data Scientist (nd025) | Business Analytics (nd098) | |
|---|---|---|---|
| Level | Intermediate | Advanced | Beginner |
| Main tools | Python, pandas, Matplotlib, Seaborn | Python, machine learning, software engineering | Spreadsheets, SQL, Tableau |
| Rating on Udacity | 4.8 (1,310) | 4.8 (814) | 4.8 (1,256) |
| Best for | Analyst roles using Python | Moving into modeling | Non-coders and managers |
Conclusion: Do I Recommend Udacity’s Data Analyst Nanodegree?
I recommend the Data Analyst Nanodegree to anyone who wants to become a data analyst, provided you already know programming basics and are comfortable with math and statistics. Self-discipline and persistence matter just as much.
Our 2026 verdict (editorial update)
We rate the current program 4.2 out of 5. It is narrower than the version Ong took (three projects instead of five, and no SQL or A/B testing), but what remains is strong: three end-to-end Python projects with human review, and one of the highest ratings in Udacity’s catalog. It is worth it for learners who already know basic Python and SQL and want reviewed portfolio work. Beginners should start with the Google or IBM certificates and come back for the projects.
A two-month plan
| Weeks | Course | Goal |
|---|---|---|
| 1 to 2 | Data Analysis with Pandas and NumPy | Submit Investigate a Dataset |
| 3 to 5 | Data Visualization with Matplotlib and Seaborn | Submit Communicate Data Findings |
| 6 to 8 | Advanced Data Wrangling | Submit Real World Data Wrangling, then cancel before renewal |
Start the Data Analyst Nanodegree →
Ong Kam Siong was a finance analyst with eight years of professional experience. He now works on projects that apply data science to accounting and finance. Read Ong’s story.
Comparing programs? Our ranked guide to the best Udacity Nanodegrees in 2026 re-checks the hours, projects and prerequisites of 10 programs on their live Udacity pages.
FAQs
Is Udacity’s Data Analyst Nanodegree worth it?
It is worth it if you already know basic Python and SQL and want three reviewed, portfolio-ready Python projects in about two months. It is one of Udacity’s highest-rated programs (4.8 from 1,310 reviews). Ong, who wrote this review, used it to move from finance work toward data analysis. It is poor value as a first course: beginners get more for less from the Google or IBM data analyst certificates on Coursera.
Can I complete the Data Analyst Nanodegree in a month?
It is possible if you already have intermediate data analysis skills: Udacity estimates 43 hours. Ong does not recommend rushing; take the time to do the projects properly, since they are what employers look at.
How much does the Udacity Data Analyst Nanodegree cost?
On 13 October 2026 Udacity listed $249 a month, $846 for four months (about $212 a month), or $999 to buy the program outright. At 10 hours a week most learners finish in about two months, so a realistic budget is about $500. Udacity shows a personalized new-user discount at times; check the price at checkout.
Does the current program teach SQL, Tableau or A/B testing?
No. The current version (nd002, updated August 2026) is three Python courses: data analysis with pandas and NumPy, visualization with Matplotlib and Seaborn, and advanced data wrangling. Basic SQL and inferential statistics are now listed as prerequisites. The SQL and A/B testing projects Ong describes were part of the earlier version.
What are the prerequisites?
Udacity lists basic Python, basic SQL, file input and output, elementary algebra, and basic descriptive and inferential statistics. If you are not there yet, Udacity’s Programming for Data Science with Python Nanodegree or its free SQL for Data Analysis course are the usual first steps.
Will I get a certificate after completing this Nanodegree?
Yes. You receive a Udacity Nanodegree certificate when all three projects pass review. It is not a college degree or academic credit.
What is a Udacity Nanodegree?
A Nanodegree is Udacity’s name for a multi-course program built around projects that a human reviewer grades against a rubric. You earn a certificate when every project passes.
Udacity Data Analyst Nanodegree or the Google Data Analytics Certificate?
Google’s certificate (9 courses, about six months at under 10 hours a week) is the better first step for beginners and covers spreadsheets, SQL, Tableau and Python. Udacity’s program is shorter, assumes Python and SQL already, and adds human review of three larger projects.
Is there a free version of the Data Analyst Nanodegree?
No. The Nanodegree and its project reviews are paid. Free ways to prepare include Udacity’s SQL for Data Analysis course and the free audit options on many Coursera courses. Avoid sites offering free downloads of paid course material.
What jobs does it prepare you for?
Entry-level data analyst, reporting analyst and business intelligence roles that use Python. The US Bureau of Labor Statistics has no separate data analyst occupation; related occupations include operations research analysts (median $88,940 in May 2025) and data scientists ($120,230).
Related Udacity guides: Every Udacity Nanodegree in 2026 (Hub) | Business Analytics Nanodegree | Power BI Nanodegree | SQL Nanodegree | Generative AI Nanodegree | Agentic AI Nanodegree | AWS ML Engineer | Intro to Machine Learning with PyTorch
For the full Udacity breakdown, read our Udacity Nanodegree review (2026). Hub: Udacity.