Nanodegree Program

Data Science Foundation

Dive into Data Science with Python, R, and statistics. Use libraries like NumPy and Pandas to explore and analyze data

7 days refund, no questions asked

  • Time
    4 months

  • Prerequisites
    No prior programming experience required
  • Classroom Opens

Why take this Nanodegree?

From advertising to healthcare, almost every industry is now adopting Data Science technology to get an edge over the businesses. Data Science has recorded six times faster growth than the average growth rate of IT industry in the past couple of years. According to the market experts, it would sustain the momentum and continue to outpace other IT sectors by a significant margin in the years to come. If you are if you are looking to make a career in one of the fastest growing IT sectors, there is no better alternative than data science.

Our Data Science Foundation Nanodegree prepares you with skills you need to establish a successful data science career. In this Nanodegree, you will learn Python fundamentals, statistics, R programming, fundamentals of hadoop and mapreduce. By the end of this Nanodegree program, you will be all set for advanced Nanodegrees like Data Analyst and Machine Learning Nanodegree Programs.

Why take this Nanodegree?

Six times faster growth than other IT industries

1000+ jobopportunities created
80+ Hiring partnersonboard
40 lac+ Highestannual CTC offered

Learn with the best

Sebastian Thrun
Sebastian Thrun


Sebastian is the co-founder of Udacity and a professor at Stanford University. He’s a prominent figure in artificial intelligence where he’s known as the godfather of automated vehicles. Sebastian spends his time flying as president of Kitty Hawk.

Mat Leonard
Mat Leonard


Mat is a former physicist, neuroscientist, and data scientist with a passion for education. Recently, he led the Deep Learning Nanodegree Foundation program covering state-of-the-art machine learning models.

Sarah Sproehnle
Sarah Sproehnle


Sarah is VP of Customer Success at Cloudera, a reference company in Big Data and Hadoop. He also specializes in MapReduce and databases such as MySQL. He loves helping people learn complex technologies.

Moira Burke
Moira Burke


Moira Burke is a Data Scientist at Facebook, where she combines her social psychology and data munging chops to understand how people perceive their audience online and how various uses of the site improve psychological well-being. She received her Ph.D. in Human-Computer Interaction from Carnegie Mellon University, and a B.A. in Computer Science from the University of Oregon.

Solomon Messing
Solomon Messing


Solomon Messing is a political scientist with Facebook's Data Science Team. His research and teaching focus on political advertising and campaigns, social influence, and design and analysis of experiments. His work has appeared in the American Political Science Review, Public Opinion Quarterly, and Communication Research. Solomon completed his Ph.D. in political communication and M.S. in Statistics at Stanford.

Dean Eckles
Dean Eckles


Dean Eckles is a social scientist, statistician, and member of the Data Science team at Facebook. His current work uses large field experiments and observational studies. His research appears in peer reviewed proceedings and journals in computer science, marketing, and statistics.

Chris Saden
Chris Saden


Chris Sedan is a Full Stack Software Engineer at Udacity. He brings his experience of teaching high school mathematics to online learning and dabbles in data visualization in his spare time.

Mike Yi
Mike Yi


Mike is a content developer with a multidisciplinary academic background, including math, statistics, physics, and psychology. Previously, he worked on Udacity's Data Analyst Nanodegree program as a support lead.

David Venturi
David Venturi


Formerly a chemical engineer and data analyst, David created a personalized data science master's program using online resources. He has studied hundreds of online courses and is excited to bring the best of the best to Udacity students as a Content Developer.

Charlie Turner
Charlie Turner

Content Developer

Charlie has worked in the UK's National Bureau of Statistics and has more than a decade of experience in data analysis and manipulation. Today, it is Course Developer and Course Manager at Udacity. He holds a PhD in Mathematics from the University of Warwick.

Philip Mallory
Philip Mallory

Content Developer

Philip has had the privilege to teach in several formats. He’s taught Game Boy Advance programming in person, coached data science and introductory computer science courses at Udacity, and now he’s developing courses too. He’s applied computer science to music composition, aerial dolphin.

What You Will Learn

Data Science Foundation

Master foundational knowledge of Data Science. You will gain fundamental knowledge of Python, real-world application of statistics, data wrangling, R programming, and big data essentials - Hadoop & Map Reduce.

See fewer details

4 months to complete

Prerequisite Knowledge
No prior programming experience required See detailed requirements.
  • Introduction to Python

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

  • 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.

  • 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..

    Analyze Experiment Results
  • Programming in R

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

    Explore and Summarize Data
  • 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.

    Wrangle and Analyze Data
  • Hadoop & Map reduction

    Learn the basics of Hadoop, the leading tool for big data processing in the world. Practice MapReduce

Start Learning
Data Science Foundation

Introductory Price

7 days refund; no questions asked

Total Seats: 300
Time to Complete: 4 months
Full Fee: ₹17,700*

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Payment Options

We support multiple payment options for your convenience. Choose an option that suits you the most

Credit/Debit Card

Accepting payments through Credit/Debit cards from all major banks.

EMI on Credit Card

Split the payment of the course fee across 3 or more months. Option is available for all plans. Instalment information available on the payment page.

Internet Banking
Internet Banking

Seamless payment though Internet banking accepting payments from over 59 banks.

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    About the course
  • Why do I take up this Nanodegree?
    Our Data Science Foundation Nanodegree prepares you with skills you need to establish a successful data science career. In this Nanodegree, you will learn Python fundamentals, statistics, R programming fundamentals of hadoop and mapreduce. By the end of this Nanodegree program, you will be all set for advanced Nanodegrees like Data Analyst and Machine Learning Nanodegree Programs.
  • What are prerequisites for this Nanodegree?
    You do not require prior programming experience to take up this Nanodegree.
  • How is the Nanodegree Program Structured?
    This Nanodegree is of 4 months, which needs to be completed in the given time period. Your 4 months will start from the date you get access to your classroom.
  • Do you offer the opportunity for students to pause their studies for this program?
    No. The fixed-term nature of this Nanodegree program, and the need for maintaining a consistent and stable student body throughout, doesn't allow for offering the option to pause your studies.
  • Is this program self-paced?
    No. The start and end dates of this Nanodegree is fixed, and you must complete all assigned projects by the end dates. However, projects may be submitted at any time during the Nanodegree, and individual project deadlines are recommendations, not requirements. So within the Nanodegree, there is some opportunity to work at your own pace. You should plan to follow our recommended timeline, as this will best enable you to keep pace with your peers, and complete the program on time.
  • What kind of weekly time commitment should I expect?
    On average, we find students spending 10 hours per week throughout the entire Nanodegree, to complete this Nanodegree on time. This is an average so that some students may require more than the allotted time frame, or less.
  • Are deferments an option if I'm enrolled, but not ready to start yet?
    No, deferments are not an option. We ask that you, please make sure to only enroll for the Nanodegree if you can commit to the entire time frame.
  • Do I lose access to this Nanodegree once I graduate?
    No, you will not lose access to the content of this Nanodegree once you graduate. Your access will be there for the lifetime.
  • Does this Nanodegree provide Mentorship?
    Yes, you will be provided mentors to guide you throughout the Nanodegree.
  • Does this Nanodegree offer any trial period?
    No, this Nanodegree does not contain any trial period. We do have seven days no questions asked refund policy. You can pay for your Nanodegree and ask for a refund within seven days from the date you get access to your classroom.
  • Do you provide Scholarship for this Nanodegree?
    No, Currently there is no scholarship available for this Nanodegree. We will let you know when we come up with a scholarship for this Nanodegree. For more information on scholarships, please write to
    Career Services
  • What career services we provide?
    This is a basic level course which does not make you Job-Ready.
    Student Support
  • What is the kind of student support I will get during this program?
    Project Reviews: The Project reviews provide deep analysis of a student's code and project. Reviewers are trained professionals that provide feedback on coding styles, industry guidelines, optimization of the code and reference links for improving the project.

    Mentorship: Mentors are appointed to students that have one on one chats with them. They keep track of the progress in the course, Help them in time management and keep them motivated throughout the course.
  • How can I get in touch with Udacity for any support?
    Please write to for faster response
    Payments & Refunds
  • Do we get 50% refund for this Nanodegree?
    No, We do not provide 50% refund on this Nanodegree.
  • Does this Nanodegree follow seven days No Questions Asked refund policy?
    Yes, this Nanodegree follows seven days no questions asked refund policy. Seven days are counted from the date you get access to your classroom.
  • If the refund is provided for this Nanodegree, How much time does the refund process take?
    The refund process takes up to 2-3 weeks of time. The amount will be refunded back to the bank account you paid from. If you would like to get the refund in a different bank account, please mention the same to while requesting for a refund.
  • How do I get my invoice?
    Please write to, It can take maximum upto 7 days for us to issue your invoice.
  • What if I do not receive my refund in 15-20 days?
    If you do not receive your refund within 15-20 days, please reach out to

Data Science Foundation

Dive into Data Science with Python, R, and statistics. Use libraries like NumPy and Pandas to explore and analyze data

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