The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.

Courtlyn
Promotion and Events SpecialistGet the inside track to an in-demand career in data science
June 8, 2022
6 months, online
10-15 hours per week
US$7,500 or get US$500 off with a referral
Our participants tell us that taking this program together with their colleagues helps to share common language and accelerate impact.
We hope you find the same. Special pricing is available for groups.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBased on the information you provided, your team is eligible for a special discount, for Professional Certificate in Applied Data Science starting on June 8, 2022 .
We’ve sent you an email with enrollment next steps. If you’re ready to enroll now, click the button below.
Have questions? Email us at group-enrollments@emeritus.org.Limited Time Offer!
Only a few seats remain. Enroll now to be part of the next cohort and take advantage of the growth in the field.
US$12,500 US$7,500
Pay Nothing While You Learn. Financing Options Starting At US$51/Month.
Demand for data scientists crosses all industries as employers scramble to harness the power of data analytics to personalize their products, minimize risk, and expand into new markets. The Professional Certificate in Applied Data Science from the Thayer School of Engineering at Dartmouth positions professionals to take full advantage of this trend. Upon completing this program, you will be ready to take advantage of new opportunities and face new challenges in the field of Data Science.
–Peter Skomoroch, former principal data scientist at LinkedIn
Data Science jobs are expected to grow almost 3X as fast as other job categories in the coming years.
Average salary of a data scientist.
Of data science graduates have found jobs since 2011.
Prerequisites: This course requires mandatory moderate knowledge of Calculus, Linear Algebra, Statistics, and Probabilities.
–Geoffrey Parker, Professor of Engineering at Dartmouth College, Director of the Master of Engineering Management Program at Thayer School of Engineering
*Services provided by Emeritus, a learning partner for this program.
Career Coaching + Mentorship from Industry Experts + Webinars = Job-Ready Confidence
Where do you fit in the expanding universe of Data science? What is your unique skill set?
In just six months, you will become skilled in the fundamentals of data science, mastering critical concepts using Python. By receiving one-on-one support from a mentor who is an expert in the industry, you will be prepared to accelerate your career as a data scientist.
Pre-Module: 4-Week Python Coding Camp
All participants complete a month long data camp to learn or reinforce foundational Python coding skills. Live office hours and moderated discussion boards offer personalized support.
Learn to implement Python concepts; evaluate how companies leverage data to find opportunities; use a problem-solving framework; create functions and 'while' loops in Python; work with values, tuples, and lists; and explore Markdown in Jupyter Notebook.
Identify structured and unstructured data; understand continuous and categorical data; explore data structures; determine what kind of data can be expressed in vectors vs. matrices; format and analyze data; and create simple plot points in Python.
To understand confidence intervals and p-values, gain a solid base of knowledge in statistics and probability, including means and distributions; and use Python to create quantile-quantile plots and perform hypothesis tests.
Understand how to build and visualize OLS regression models, apply the problem-solving framework to create univariate and multivariate regression models; create user-friendly model outputs; and apply metrics to regression models.
Learn transformation of variables into your model; fit variable interactions; perform the Shapiro-Wilks test to assess normality and execute transformations; create multivariate models with interaction variables; evaluate model fit and complexity; share results.
Explore modeling for binary outcomes; apply the problem-solving framework to create logistic regression models that determine the odds and probability of a given outcome; clearly communicate the output of models; and apply metrics to classification models.
To effectively communicate to non-technical stakeholders, create interactive dashboards in Python; employ best practices for creating effective data visualizations; and plot different types of data using Seaborn in Python.
Use statistical tests to determine statistical significance while using visualization techniques to fully illustrate the differences between test and control; apply experimental design and targeting analysis; and perform A/B testing in Python.
Focus on modeling techniques to solve business challenges; apply machine learning techniques, such as K-means clustering, classification, and regression trees, and resampling through k-fold cross-validation; learning within the industry.
Synthesize all of the concepts, skills, and applications you have learned, develop a project that demonstrates and explains various tools and techniques explored in the course; creating a portfolio presentation to share with prospective employers.
Learn to implement Python concepts; evaluate how companies leverage data to find opportunities; use a problem-solving framework; create functions and 'while' loops in Python; work with values, tuples, and lists; and explore Markdown in Jupyter Notebook.
Explore modeling for binary outcomes; apply the problem-solving framework to create logistic regression models that determine the odds and probability of a given outcome; clearly communicate the output of models; and apply metrics to classification models.
Identify structured and unstructured data; understand continuous and categorical data; explore data structures; determine what kind of data can be expressed in vectors vs. matrices; format and analyze data; and create simple plot points in Python.
To effectively communicate to non-technical stakeholders, create interactive dashboards in Python; employ best practices for creating effective data visualizations; and plot different types of data using Seaborn in Python.
To understand confidence intervals and p-values, gain a solid base of knowledge in statistics and probability, including means and distributions; and use Python to create quantile-quantile plots and perform hypothesis tests.
Use statistical tests to determine statistical significance while using visualization techniques to fully illustrate the differences between test and control; apply experimental design and targeting analysis; and perform A/B testing in Python.
Understand how to build and visualize OLS regression models, apply the problem-solving framework to create univariate and multivariate regression models; create user-friendly model outputs; and apply metrics to regression models.
Focus on modeling techniques to solve business challenges; apply machine learning techniques, such as K-means clustering, classification, and regression trees, and resampling through k-fold cross-validation; learning within the industry.
Learn transformation of variables into your model; fit variable interactions; perform the Shapiro-Wilks test to assess normality and execute transformations; create multivariate models with interaction variables; evaluate model fit and complexity; share results.
Synthesize all of the concepts, skills, and applications you have learned, develop a project that demonstrates and explains various tools and techniques explored in the course; creating a portfolio presentation to share with prospective employers.
For full details of the curriculum, please download the brochure.
Download BrochureThe goal of this project was to accurately predict whether a traffic accident could result in injury or death and assist in the deployment of officers.
Machine learning algorithms and NLP techniques were used to understand and determine the influence of Twitter and Facebook conversations on stocks. Together with financial data, the student calculated rules for investing and predicting the price of various stocks.
In this project, a model was created to accurately and consistently predict whether a contract will be renewed in an energy company, identifying variables important to creating better plans for the future to enable more efficiency and productivity.
The United States Air Force, which includes the Space Force, tracks the telemetry of thousands of near-Earth objects, also known as satellites. As additional satellites are launched and traffic above Earth's atmosphere increases, older satellites have a greater chance of falling from orbit. Students used machine learning to help predict satellite decay, or the point at which a satellite loses orbit and re-enters the atmosphere. The final model, deployed live, is currently in use by the Space Force.
This is a rigorous, fully graded, skill-based program. The Professional Certificate in Applied Data Science from Thayer School of Engineering at Dartmouth shows prospective employers that you are ready to take on a challenging role in data science, from concept to code.
Download BrochureYour verified digital certificate will be issued in your legal name and emailed to you, at no additional cost, upon completion of the program, as per the stipulated requirements. All certificate images are for illustrative purposes only and may be subject to change at the discretion of the Thayer School of Engineering.
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Geoffrey Parker
Professor of Engineering at Dartmouth College, Director of the Master of Engineering Management Program at Thayer School of Engineering
Geoffrey Parker is Professor of Engineering at Dartmouth College, where he also serves as Director of the Master of Engineering Management Program. Parker also teaches regularly in the Dartmouth Tuck School of Business executive education program. In addition, he is a research fellow at MIT’s Initiative for the Digital Economy where he leads platform industry research studies and co-chairs the annual MIT Platform Strategy Summit. Prior to joining the Dartmouth faculty, he was Professor of Management Science at the Tulane University A. B. Freeman School of Business. He received a B.S.E. from Princeton and M.S. and Ph.D. from MIT.
Parker has made significant contributions to the field of network economics and strategy as co-developer of the theory of “two-sided” markets. He is co-author of the book Platform Revolution. His current research includes studies of platform business strategy and economics, data governance and regulation with application in areas such as finance, logistics, energy, and healthcare. Parker is a frequent keynote speaker and advises senior leaders on their organizations’ platform strategies. Before attending MIT, he held positions in engineering and finance at GE Semiconductor and GE Healthcare.
As one of the first engineering schools in the US, the Thayer School of Engineering at Dartmouth aims to elevate problem-solving through engineering thinking, research, and innovation to create a human-centered impact. Our programs offer a hands-on systems-based approach, with a heavy emphasis on research and a steadfast belief in entrepreneurship. Other words that describe us? Boundaryless. Collaborative. Compassionate. Flexible. Impactful. Our certificate programs are an extension of the educational opportunities we have provided for engineers since our inception in 1867. At Dartmouth, an Ivy League institution, we foster a community of learners whose goal is to make a difference in the world.
We offer flexible and transparent payment options through our partner Ascent Funding.
US Residents
Monthly payments starting US$51.
Immediate repayment, interest-only repayment, and deferred payment options available. Click here to know more.
Flexible Payment Options For All
Monthly payments as low as US$1,260. Click here to know more.
You can opt for any one of the financing options to cover up to the full cost of the program tuition. If you are considering financing your program through one of our partners, the enrollment process can only be completed with the assistance of your program advisor or by calling +315-538-6867.
Please note that loan applications should be submitted no later than four business days prior to the enrollment deadline due to processing time.
Demand for individuals with skills in data science has grown faster than supply, creating opportunities for those with quantitative abilities to launch into this career field. This online Professional Certificate in Applied Data Science is based on portions of the Master of Engineering Management program curriculum taught at the Thayer School of Engineering at Dartmouth by Professor Geoffrey Parker. It is organized around the skills that technology giants such as Amazon, Google, Facebook, Apple, and McKinsey value in data science professionals. Numerous participants in the on-campus version of the program have leveraged the skills acquired at Dartmouth to obtain positions in data analytics-oriented roles across a variety of industries.
A global and experienced peer group is one of the key elements of the program. The typical class will have early stage, mid-level, as well as senior professionals looking to create a new career pathway in data science. A large majority of participants come from the US but we attract many participants from the wider English-speaking markets like Australia, UK etc. Finally, your class will have professionals from various sectors of the economy, with high representation from Banking and Financial Services, Healthcare, E-commerce, Energy and IT Services.
In order to fully understand the real business problems that data science can help solve, you need to understand how the algorithms work. Take for example machine learning, an approach that is being applied across every industry. Math is a fundamental aspect of understanding what machine learning is about. As you proceed through your career and develop new skills, you will need to leverage this mathematical understanding to engage with and comprehend new literature and peer-reviewed journals on Machine Learning approaches.
This is a graded program. You will be required to complete a combination of individual assignments, quizzes, and a final project. Each component carries a certain number of points and a cumulative score of 75% is required to pass and obtain your Professional certificate.
The program will give you the skills you need to be prepared for a job in this field, however a job placement is not guaranteed. Our program team includes data science mentors and career coaches to help you prepare for your job search. Employment offers will depend on many factors, including your prior experience, education, and target job market.
This is a rigorous program that will require 10-15 hours per week. Python Coding Camp, which takes place during the first four weeks of the program, may be more time intensive.
This program offers a mix of individual learning, small group sessions, and larger group webinars on topics to accelerate your career. You will divide your time among recorded video lectures, coding video demos, assignments, attending office hours, group webinars, and meetings with your dedicated career coach and mentor.
It’s interactive, flexible, rigorous, and designed to include a lot of personal attention so that you can reach your learning goals more effectively. You will join a community of learners who are excited to expand and share their knowledge. Here are a few elements that set this program apart:
The Thayer School of Engineering at Dartmouth College is collaborating with Emeritus to create and deliver this program. The certificate is issued by the Thayer School of Engineering at Dartmouth College. Emeritus provides technology and student support throughout the experience.
Emeritus is based in Singapore, with offices located in Boston, Mexico, Dubai, and Mumbai. More than 30,000 professionals from over 150 countries have taken programs with Emeritus to date.
Because participants join from all over the world, we strive to schedule the live sessions at times when the majority of participants can join. Typically, that will be between 12 pm and 4 pm UTC. All sessions are recorded with recordings available 24 hours after the session. Moderated discussion boards supplement the live sessions.
Peer learning adds substantially to the overall learning experience and is an important part of the program. You can connect and communicate with other participants through our learning platform. You will also be part of a small learning group who you will work with throughout the entire duration of the program, along with your dedicated mentor.
Upon successful completion of the program, you will receive a certificate from The Thayer School of Engineering at Dartmouth College. The digital certificate will be sent approximately two weeks after the program, once grading is complete.
No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, Twitter, etc.
No, there is no alumni status granted for this program.
You will have access to the online learning platform and all the videos and program materials for 1 full year following the program start date. Access to the learning platform is restricted to registered participants per the terms of agreement.
Participants would also need the latest version of their preferred browser to access the learning platform. In addition, Microsoft Office and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts.
Yes, the learning platform is accessed via the internet and video content is not available for download. You can download files of video transcripts, assignment templates, readings, etc. Video lectures must be streamed via the internet and webinars and small group sessions will require an internet connection.
Yes, you can do the bank remittance in USD via wire transfer. Please contact your Program Advisor for more details.
We offer flexible payment options through our partner Ascent Funding. We partner with Ascent Funding to offer you flexible and transparent loan options.
Click here to learn more
There are also installment payment options available - you can find them at the top of this page
Yes, the program fee is inclusive of any taxes with the exception of GST for Singapore residents
Participants are eligible for a full refund if they cancel their enrollment before or during their trial period. The trial period for all programs is 21 calendar days (excluding course holidays) from and including the first day of class, which is the participant’s scheduled start date.
Participants may request a prorated refund after the trial period has passed up until they have completed 60% of their time in the program. Refunds are determined through proration of tuition, based on the number of days that have elapsed from the scheduled start date through the date that the Withdrawal Request Form is completed. Refunds will not be granted once 60% of a participant’s scheduled program time has passed, regardless of the amount of work a participant has submitted or sessions a participant has attended.
After a participant is withdrawn, they will no longer be able to attend office hour or 1:1 sessions with Course Leaders, Mentors, or Career Coaches, submit work for review, or access their program dashboard or curriculum.
Participants have the option to request a deferral to a future cohort within the first 30 days from their Program Start Date. Cohort changes may be made only once per enrollment and are subject to the availability of cohorts scheduled at the discretion of Emeritus. Participants requesting a deferral must be in good academic standing. Participants who would like to defer their enrollment should email ProgramSupport@Emeritus.org or use the “Support” tab in their learning platform in order to receive the Deferral Request Form.
Registration for this program is done through Emeritus. You can contact us at dartmouth@emeritus.org or schedule a call with an advisor.
Flexible payment options available.