At 10 hrs/week
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We recommend students are familiar with machine learning concepts, like those in the Intro to Machine Learning Nanodegree Program. In addition, students should be familiar with Python programming, probability, and statistics. See detailed requirements.
Learn the data science process, including how to build effective data visualizations, and how to communicate with various stakeholders.Write a Data Science Blog Post
Develop software engineering skills that are essential for data scientists, such as creating unit tests and building classes.
Learn to work with data through the entire data science process, from running pipelines, transforming data, building models, and deploying solutions to the cloud.Build Disaster Response Pipelines with Figure Eight
Learn to design experiments and analyze A/B test results. Explore approaches for building recommendation systems.Design a Recommendation Engine with IBM
Leverage what you’ve learned throughout the program to build your own open-ended Data Science project. This project will serve as a demonstration of your valuable abilities as a Data Scientist.Data Science Capstone Project
from industry experts
Personal career coach and
Data Scientist at Nerd Wallet
Josh has been sharing his passion for data for nearly a decade at all levels of university, and as Lead Data Science Instructor at Galvanize. He's used data science for work ranging from cancer research to process automation.
Data Science Instructor
As a data scientist, Juno built a recommendation engine to personalize online shopping experiences, computer vision and natural language processing models to analyze product data, and tools to generate insight into user behavior.
Luis was formerly a Machine Learning Engineer at Google. He holds a PhD in mathematics from the University of Michigan, and a Postdoctoral Fellowship at the University of Quebec at Montreal.
Andrew has an engineering degree from Yale, and has used his data science skills to build a jewelry business from the ground up. He has additionally created courses for Udacity’s Self-Driving Car Engineer Nanodegree program.
Data Analyst Instructor
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.
VP of Engineering at Insight
David is VP of Engineering at Insight where he enjoys breaking down difficult concepts and helping others learn data engineering. David has a PhD in Physics from UC Riverside.
Senior Data Engineer at Netflix
Currently, Judit is a Senior Data Engineer at Netflix. Formerly a Data Engineer at Split, where she worked on the statistical engine of their full-stack experimentation platform, she has also been an instructor at Insight Data Science, helping software engineers and academic coders transition to DE roles.
The program is great for self-motivated people who want to research and learn on their own. The videos are well organized and provide fair amount of information to complete the assignments and challenges. The only thing I felt tasking was the fee associated with this degree. I think it can be lowered a lot given the fact that students are mostly on their own with time management and assignment completion. Overall I would say, I am enjoying this learning journey and hope to complete it in the coming weeks.
I'm trying my best to make a balance between my job and this valuable nanodegree. I already know I'm behind the schedule but I'm really happy since I am learning very useful stuff here and can apply my new skills to my job. Later on after graduation from this nanodegree I will pursue a better job which will be more in-depth about data science and machine learning. I will also look for other exciting nanodegrees in Udacity such as Deep Learning, Deep Reinforced Learning, and NLP.
Good syllabus and having a hands-on is an added advantage. It's very beneficial to my learning. Have come across lot of trainings and courses throughout my 10 years of experience. This course distinguishes from others by having clarity on the topics that were explained. As we know, a picture portrays 1000 words, creating a video series to explain everything plays a vital role in making the concepts clear to all learners. Thank you for all the creators of this course.
OMG! THIS PROGRAMME IS INSANE! You have such a strong learning path! You start with FUNDAMENTAL behind the algorythm(math) before you implement it, and then use tools such as SKlearn. This makes you understand properly what those algorythms do! Im soooooo in love with this programme, ANYONE out there with any moocs taken that teaches them python + some statistics and dont know where to go next for their Data Science Path = THIS IS YOUR ANSWER!
Cool, it takes a little bit more than expected to accomplish the core curriculum (those Jupyter Notebooks alone takes ~1h while whole lesson is set to 1h). Slack is a little bit silent in comparison to other Nanodegrees. I heard there will be GitHub review/mock job Interviews but I didn't see any.
It is friendly with new machine learning learner. Most coding exercises have appropriate comments and assistant codes. I'm fascinated with the math part of the algorithm which illustrates the process in detailed. I hope Udacity can add more related lessons about each algorithm in related lessons.
Numbers don't lie. See what difference it makes in career searches.*
Career-seeking and job-ready graduates found a new, better job within six months of graduation.
Average salary increase for graduates who found a new, better job within six months of graduation.
The data science field is expected to continue growing rapidly over the next several years, and there’s huge demand for data scientists across industries. Data scientist is consistently rated as a top career.
Udacity has collaborated with industry leaders to offer a world-class learning experience so you can advance your data science career. You’ll get hands-on experience running data pipelines, designing experiments, building recommendation systems, and more. You’ll have personalized support as you master in-demand skills that qualify you for high-value jobs in the data science field.
By the end of the program, you’ll have an impressive portfolio of real-world projects, and valuable hands-on experience. You’ll also receive career support via profile and portfolios reviews to help make sure you’re ready to establish a successful data science career, and land a job you love.
Obtaining the skills required to be a Data Scientist will make you extremely valuable across many industries, and in many roles. Data Scientists work as Analysts, Statisticians, Engineers, and more. Some become Data and Analytics Managers, while others specialize as Database Administrators. As a graduate of this program, you’ll be prepared to seek out roles that run the gamut from generalist to specialist, and all points in between.
This program offers an ideal path for experienced programmers and data analysts to advance their data science careers. If you’re interested in deepening your expertise in the fields of analytics, machine learning, data engineering, and/or data science, this is a great way to get hands on practice with a variety of techniques and learn to build end to end data science solutions.
The Data Analyst program is designed for people with some data analysis experience and little-to-no programming experience. Students will learn to analyze data using Python and SQL, to wrangle and clean messy data, to use applied statistics to test hypotheses, and to create data visualizations. Graduates of this program will be prepared for data analyst positions.
The Data Scientist Nanodegree program is designed for students with strong programming and data analysis skills, as it is the next step for graduates of the Data Analyst Nanodegree program. Students will learn to build machine learning models, run data pipelines, design experiments and recommendation engines, communicate effectively, and to deploy data applications. Graduates of this program will be prepared for data scientist positions.
The Machine Learning Engineer Nanodegree program prepares students for machine learning engineering careers. As both data scientist and machine learning jobs require machine learning knowledge, each of these two programs begins with a focus on machine learning. The curriculum diverges in later sections as you begin to focus on more job-specific tools, skills, and techniques.
No. This Nanodegree program accepts all applicants regardless of experience and specific background.
The Data Scientist Nanodegree program is designed for students with programming and data analysis experience. Students should have a high comfort level with a variety of topics before starting the program. In order to successfully complete this program, you should meet the following prerequisites:
Udacity’s Data Analyst Nanodegree program is great preparation for the Data Scientist Nanodegree program. You’ll learn programming with Python and SQL, applied statistics, data wrangling, and data visualization.
You can also prepare by taking a number of Udacity’s free courses, such as:
The Data Scientist Nanodegree program is comprised of content and curriculum to support four (4) projects. We estimate that students can complete the program in four (4) months working 10 hours per week.
Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.
To successfully complete this Nanodegree program, you’ll need to be able to download and run Python 3.7.