From advertising to healthcare, almost every industry is now adopting Data Science technology to get an edge over other 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, the industry will soar 28% by 2020. 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 Scientist Nanodegree prepares you with skills you need to become a successful data scientist. In this Nanodegree, you will learn Python fundamentals, statistics, R programming fundamentals of hadoop and mapreduce, and Machine Learning Basics. By the end of this Nanodegree program, you will master programming languages and will be all set for advanced Nanodegrees like Data Analyst and Machine Learning Engineer Nanodegree Programs.
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 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 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 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 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 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 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 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.
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 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 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.
See fewer details
No programming experience required See detailed requirements.
Learn Python programming fundamentals such as data types and structures, variables, loops, and functions.
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 PandasExplore Bikeshare Data
Learn how to apply inferential statistics and probability to important, real-world scenarios, such as analyzing A/B tests and building supervised learning models.
Learn to explore data at multiple levels using appropriate visualizations, acquire statistical knowledge for summarizing data, and develop intuition around a data set.
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
Learn the basics of Hadoop, the leading tool for big data processing in the world. Practice MapReduce
Learn how supervised learning models, such as decision trees, SVMs, and others, are trained to model and predict labeled data. In unsupervised learning, learn to find patterns and structures in unrecorded data, perform resource transformations, and improve the predictive performance of your modelsPredict Housing PricesCreate Customer Segments
7 days refund; no questions asked
Total Seats: 300
Time to Complete: 4 months
Prerequisite: No prior programming experience required
Admissions Closes: 07 May
* Price exclusive of taxes. GST of 18% gets applied on checkout. Option to convert your payment into EMI available on checkout page.
All the above payment plans include the costs of Unlimited project reviews (by Udacity's global reviewer network), in-classroom mentorship support through chat with industry experts and Access to global community of Udacity students pursuing the same Nanodegree.
We support multiple payment options for your convenience. Choose an option that suits you the most
Accepting payments through Credit/Debit cards from all major banks.
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.
Seamless payment though Internet banking accepting payments from over 59 banks.
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.