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Hundreds of education providers have emerged eager to teach those interested in learning data science and becoming the world’s leading data scientists. From self-paced learning and guided instruction to formal educational programs offered at universities, the ways in which someone can learn data science could seem daunting. Data Science Programs was created to introduce you to the education providers you may not have realized existed and help find your right path to learn data science. We’ve curated a short list of our favorite data science educational providers and resources below to help you start your research journey. We will be adding to this list in the coming months.

Our information has been collected through interviews with the education provider’s founders and administrators, faculty, alumni and current students as well as information gathered from the provider’s website and marketing materials. When possible we connect leading data science professionals [with hiring power] to ask them for their opinions on the data science education providers. Our goal is to arm anyone interested in learning data science with the information they need to make a confident and informed decision.

We strive to provide the most up-to-date information on: education costs and tuition, curriculum, admissions criteria & process, instruction & pedagogy, program rigor and required time commitment, graduate outcomes [such as starting salaries] and educational quality [including background on the institution, accreditation status, instructor profiles and investors]. Feel free to jump ahead in the table of contents to certain data science learning paths or scroll at your leisure. Again, check back soon as we will be adding to this list in the coming months.

Table of Contents

Non-degree granting Data Science Programs

IRL Data Science Programs & Bootcamps

Online Data Science Bootcamps

Online Data Science Courses

IRL Data Science Courses

Data Science Certificate Programs

Data Science Corporate training [coming soon]

Data Science Workshops [coming soon]

Data Science Conferences [coming soon]

Degree granting Data Science Programs

Undergrad Majors in Data Science [coming soon]

IRL Masters in Data Science

Online Masters in Data Science

Joint MBA / MS in Data Science [coming soon]

Data Science PhD programs [coming soon]

Self-Paced Data Science Learning

Feeling semi-motivated and want to learn data science through a self-paced pathway? We’ve a curated list of the leading data science books, apps, MOOCs, recorded lectures/videos and podcasts.

Title:

Data Smart: Using Data Science to Transform Information into Insight

Author

John w. Foreman

Est. Cost

$31.99 on Amazon

Editorial Comments

Foreman is Chief of Data Science for MailChimp.com and notable industry consultant

Title:

Practical Data Science with R

Author

Nina Zumel & John Mount

Est. Cost

$40.74 on Amazon

Editorial Comments

Both authors hold Ph.Ds from Carnegie Mellon and run a successful data science consulting firm in SF

Title:

Data Science For Business

Author

Foster Provost and Tom Fawcett

Est. Cost

$33.13 on Amazon

Editorial Comments

This book is based on the NYU Stern MBA course Provost taught on data science

Title:

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie or Die

Author

Eric Siegel

Est. Cost

$13 on Amazon

Editorial Comments

An introductory book being used by over 30 leading Universities

Class Name:

Statistical Thinking for Data Science and Analytics

4.65 (72 reviews)

Instructor

Tian Zheng

Institution

ColumbiaX

Platform

EdX

Length

5 weeks

Effort

7-10 hours per week

Price

$XXX

Level

Introductory

Enrollment

XXXX

Class Name:

The Analytics Edge

4.65 (72 reviews)

Instructor

Multiple instructors

Institution

MITx

Platform

EdX

Length

12 weeks

Effort

10-15 hours per week

Price

$XXX

Level

Intermediate

Enrollment

Open

Class Name:

Machine Learning

4.9 (72 reviews | 24,000 ratings)

Instructor

Andrew NG

Institution

Stanford

Platform

Coursera

Length

11 weeks

Effort

XXXX

Price

$XXX

Level

XXXX

Enrollment

XXXX

Class Name:

Intro to Data Science

4.65 (72 reviews)

Instructor

Dave Holtz & Cheng-Han Lee

Institution

Facebook & MongoDB

Platform

Udacity

Length

2 months

Effort

XXX

Price

$XXX

Level

Intermediate

Enrollment

XXXX

Title

CS109 Data
Science

Lectures

Multiple

Institution

Harvard University Paulson School of Engineering and Applied Sciences

Editorial Comments

Popular introduction to data science [clustering, visualization] originally taught in Fall 2014.

Title

Data Science Playlist

Lectures

Derek Kane

Institution

Independently published
on YouTube

Editorial Comments

Consultant data scientist, Derek Kane, published a series of data science lectures [complete with slide decks] on YouTube covering topics from predictive analytics to decision trees and programming in R].

Title

Hosts

Kyle, Linh Da & Yoshi

Editorial Comments

Over 130 episodes to select from. Majority of episodes run from 10 to 20 minutes. Great introductory content. Topics range from data science principles to real world application and case studies.

Title

Hosts

Enrico Bertini and Moritz Stefaner

Editorial Comments

80+ episodes dive into the latest developments and trends in data analytics, visualizations and feature guests from a wide range of experiences and practices.

Non-Degree Granting

Program name:

Est. Cost [$] & Time Commitment

Technical track: $59 for 3 months of access. $149 for 12 months of access or $349 for lifetime access.

Executive track: $349 for lifetime access.

Editorial Comments

DataSociety is a Washington DC based company which was established to help working professionals learn to build predictive models with data. No background in math or programming is required! The curriculum is targeted towards individuals who are looking to take their data analysis skills to the next level. The program is really geared to building immediately, applicable skills and is designed for the self-paced learner.

There are two tracks. A technical track which focuses on teaching R and an executive track which is designed to give managers an overview of data analytics tools, data science methods and how to build data driven teams. The curriculum was developed by in-house instructional designers & data scientists. Coursework includes: Intro to R & Visualization, Data clustering, Network analysis, Regression, Text mining and Natural language processing and Prediction and classification.

Every DataSociety membership includes: practical exercises, reusable coding templates, downloadable reference guides and access to the program’s end-to-end online curriculum.

Program name:

Est. Cost [$] & Time Commitment

Get unlimited access to all DataCamp courses with a monthly account for $29 or pay annually for $300.

Free courses are provided to those who want to test it out (no credit card required)

Editorial Comments

DataCamp (Cambridge, MA) believes in learning by doing and has developed a curriculum track based on a Data Scientist’s typical workflow. The company has raised $2.34M in venture funding from TechStars and other investors. DataCamp’s flipped model approach aims to teach its students the syntax and language of R & Python. Students spend 45 minutes on exercises and 15 minutes on instruction through an interactive, online learning platform.

Students should expect to learn:

  • how to import and clean data
  • how to manipulate data for analysis
  • how to visualize data
  • how to use R & Python for regression and machine learning
  • how to report on findings


The majority of DataCamp’s students are working professionals (marketing, analytics, finance) who possess an interest in becoming more data savvy (for example, someone working in Finance moving away from Excel and into R & programming). Unlike MOOCs, DataCamp reports 50 to 70% course completion rates which they attribute to the interactive nature of the classes.

Program name:

Est. Cost [$] & Time Commitment

$99 for 2 months access to the platform

Editorial Comments

Owned and operated by Kaplan, Inc., Metis: Explore Data Science (by Booz Allen) provides a self-paced, online data science learning program. A teaching assistant [for content related questions] and technical support is included in the subscription cost. This program is for students seeking a foundational or introductory understanding to the principles of data science. Expect to have a grasp on basic techniques upon completion. Knowledge and experience with Python and statistics is recommended for those who enroll.

No job placement services are offered.

Program name:

Est. Cost [$] & Time Commitment

Cost depends on the city but average cost is $3,950 [financing available through Climb & Pave].

Editorial Comments

General Assembly (GA) provides a 3 unit curriculum designed to provide an overview in: research design & exploratory data analysis, data modeling and data science application the “real world.” Instructors of the curriculum are data science practitioners hired by General Assembly for each immersive program.

It is recommended that General Assembly Data Science course students have a basic understanding of statistics and Python prior to enrollment. Graduates interested in master’s programs may have the opportunity to receive reduced tuition to the following online data science master’s programs datascience@berkeley and DataScience@SMU (both of which are powered by 2U).

Program name:

Est. Cost [$] & Time Commitment

$14,950, Part-time = 24 weeks and Full-time = 12 weeks [Merit based scholarships and Financial Aid is available]

Editorial Comments

ByteAcademy, a NYC based company has raised $2.67m in venture funding from Tri5 Ventures and began operations in August 2016. ByteAcademy’s Data Science course focuses on producing data analysts, data engineers and data architects. Python is at the core of ByteAcademy’s teachings. The curriculum covers data acquisition, analysis, Pandas, prediction, machine learning, statistical modeling, Hadoop, SQL and NoSQL. Instructors are leading data science professionals and the program features prominent guest speakers. Classes average between 5 to 15 students.

ByteAcademy boldly claims that graduates will receive a job within 6 months of graduation or tuition will be refunded (13 stipulations must be met in order to receive the tuition reimbursement) . Recent hiring companies include: IBM, JP Morgan, Goldman Sachs, Google, CodeAcademy and BuzzFeed.

Program Name

EST. COST [$] & TIME COMMITMENT

$10,200 ($2,550/course).

4 data science courses required for receipt of the Data Science Certificate from Harvard Extension School.

Program typically requires 1.5 years but you have up to 3 years to complete.

Program Name

EST. COST [$] & TIME COMMITMENT

$12,072 ($2,898/course).

4 data science courses required for certificate completion.

Designed to take 20 weeks to complete.

Degree Granting

Program name:

Est. Cost [$] & Time Commitment

144 Units are required for graduation.

$35,000 – $42,000 depending on semester start date. All students must take a 6 unit summer semester.

16-month is the standard commitment. Students take 48 Units per semester.

20-month extended timing is available. Students take 30 Units per semester.

12-month accelerated timing is also available.

Editorial Comments

CMU offers a highly competitive Master of Computational Data Science program on-campus. Acceptance rates are reportedly < 10%. Qualified admits typically [not required] have a background in Computer Science or Mathematics though work experience is not required. Applicants must submit a Statement of Purpose and Letters of Recommendation.

Students enrolled in the program are required to complete an internship. Companies come to CMU to hire their students as interns. Example companies include: Apple, Booz Allen, Google, Intel, Microsoft and Amazon.

Curriculum consists of Core Curriculum plus Behavioral Research Methods, HCI, Data Science Seminar & Analytics Capstone and 2 600 level electives in the School of Computer Science.

Upon graduation, according to CMU, most students are receiving more than one job offer at $100,000+/year plus a signing bonus.

Program name:

Est. Cost [$] & Time Commitment

45 Units are required for graduation.

Editorial Comments

Stanford University’s MS in Data Science track helps students develop their mathematical, statistical, computational and programming skills. Students from outside of Stanford University must apply through the Graduate Admissions before applying to the MS in Data Science.

Curriculum is split into Foundational Skills (Numerical Linear Algebra, Discrete Mathematics & Algorithms, Data Optimization, Stochastic Methods in Engineering or Randomized Algorithms and Probabilistic Analysis). Then 12 Units in Data Science Electives are required (Intro to Statistical Inference, Intro to Regression & Variance, Intro to Statistical Modeling, Machine Learning & Data Mining). 9 Units of specialized electives are required (ranging from Geostatistics and Business Intelligence from Big Data to Human Neuroimaging Methods). Finally, 6 Units of Advanced Scientific Programming and High Performance Computing Core are required.

There is in addition to the above, a practicum component however a thesis is not required for graduation.