
WHY NOW?
Why Thayer School
of Engineering
at Dartmouth?
The last few years have seen unprecedented growth in
computational power, new users, new devices, new behaviors,
new networks, platforms, and new data tools. The demand
for data scientists — a 344 percent increase since 2013 alone
— far outpaces the number of skilled applicants.
3X
The Thayer School of Engineering at
Dartmouth has a reputation for rigor,
excellence, and cross-pollination
across disciplines. What makes this
program different?
Data Science jobs are
expected to grow almost
three times as fast as other
job categories in the coming
years.
One-to-one career coaching*
Individual feedback
Learning in real time
Regular live webinars*
Rigorous, graded assignments
(Professional-level certificate)
(SOURCE: BUREAU OF LABOR STATISTICS)
Assistance with career planning
Real-world application of
knowledge
Small group mentoring sessions
Your Fast Track to a Job
in Data Science
World-class faculty and thought
leadership
Learn from and network with your
colleagues through peer discussions
Ivy League education
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.
*Services provided by Emeritus, a learning
partner for this program.
The Professional Certificate in Applied Data Science online program from the Thayer School of Engineering at
Dartmouth positions professionals to take full advantage of this trend. You will gain valuable career guidance on
interview preparation, networking, crafting a strong LinkedIn profile, and increasing your visibility to potential
employers. You will also be able to learn from and network with your colleagues through peer discussions.
Start Date
Duration
Program Fees
July 30, 2020
6 months online
10-15 hours per week
$12,500
Full tuition
$12,500
Financing options
or starting at
$98/Month
Click here to learn more about
financing options starting at $98/Month.
01
Professional Certificate in Applied Data Science

LAUNCH, BUILD, SWITCH
Who Is This Program For?
Career Launchers, wanting to
enter an exciting, evolving field with a
foundation that assures flexibility as
new platforms and technologies enter
the field.
Career Builders, ready to build
upon existing skills, whether in a
technical or non-technical capacity.
PREREQUISITES:
Skill requirement: A demonstrated knowledge
of Calculus, Linear Algebra, Statistics, and
Probabilities is required.*
*Assessment: Students will be given an assessment
to test their math skills prior to commencement of
the program. You can view sample questions by
clicking here.
Career Switchers, looking for new
ways to expand opportunities, engage
in continuous learning, and increase
earning potential.
Upon completing this program, you will be ready to
launch, build, or switch careers — to take advantage
of new opportunities and be ready to face new
challenges in the field of Data Science and Analytics.
Whether it’s smart grids, predictive marketing,
automated factories, algorithmic trading, automation
using machine learning, sensor data that is analyzed
to create the internet of things, or healthcare data
that is being analyzed to create new therapies …
practically every industry, every company, and every
professional is now using data to make decisions.
You will develop a data science portfolio that will help
you join this growing community of data scientists,
develop an online reputation and presence, and show
prospective employers what you can do.
Professional Certificate in Applied Data Science
WANTED: DATA SCIENTIST
In this role you will use data and your analytical
ability to find and interpret rich data sources;
manage large amounts of data; merge data
sources; ensure consistency of datasets. You
will create visualizations to aid in understanding
data, build mathematical models using data,
and produce and present data findings.
02

NOW IS THE TIME…
…To learn the basic concepts required to become an
entry-level data scientist or analyst, including data
structuring, data visualization, basics of statistics,
linear regression models, logistic regression, and
machine learning applications.
You will be able to apply these concepts using Python
through coding demonstrations and hands-on
assignments that reinforce the learning.
High-level program takeaways include:
Understand the basics and potential of
Python coding through live coding
sessions and application-based
assignments. Create visualizations,
build linear and logistic regression
models, and apply common Machine
Learning algorithms such as K-means
clustering and random forest.
Access the career guidance and 1-on-1
counseling you need — beyond resumes
and LinkedIn profiles — to prepare for a
future career in data science.
Develop a data science portfolio to
share with prospective employers
seeking candidates for entry-level data
science and related positions.
03
SAMPLE JOB POSTING FOR
JUNIOR DATA SCIENTIST:
We are seeking a Junior Data Scientist with an
interest in predictive analytics and data
modeling that will support our build out of the
core algorithms powering our products. Your
focus will be on coding and testing code in
support of our core product algorithms. You will
work with both internal as well as external data
in order to form functioning revenue
optimization models for our clients. You’ll work
closely with our Data Scientists as you work to
improve and expand our algorithms informing
brands, owners, and developers in the hotel
industry.
Professional Certificate in Applied Data Science

MEET YOUR PERSONAL CAREER
SUCCESS TEAM
Career Coaching + Mentorship from Industry Experts + Webinars = Job-Ready Confidence
1:1
Career
Coaching
Your team will help you to:
Identify your abilities and preferences
Craft a strong Linkedin profile
Small Group
Mentoring
Sessions
Live
Webinars
Where do you fit in the expanding universe of Data
science? What is your unique skill set?
One-to-one sessions with your Career Coach will help you
develop your value proposition to employers.
Mentors will help you navigate the challenges specific to
data science careers in small group sessions.
Regular Webinars will improve your networking and job
search skills. You’ll use these Webinars to develop and
practice delivering your elevator pitch for different
audiences, identify interview goals, and practice
developing a rapport with prospective employers.
Pledge of Support and Disclaimer
Our program support team includes data science mentors, career
coaches, and course leaders to help you reach your goals. It is our
primary goal to give you the skills needed to be prepared for a job in
this field. We do not, however, guarantee you a job placement.
Employment offers will depend on many factors, including your prior
experience, education, and target job market.
Professional Certificate in Applied Data Science
Increase your visibility to prospective
employers
Prepare for job interviews in the field of
data science
Develop a portfolio to share with
prospective employers that showcases
your abilities and interests
Network with peers, mentors, career
coach, and the broader programming
community
Regular office hours, coaching sessions,
and live instructor sessions ensure that
you 'get it'.
Graded assignments allow you to get
the feedback you need to deepen your
understanding of core concepts.
Having a portfolio will allow you to hit
the ground running.
04

PROGRAM HIGHLIGHTS
This curriculum is based on portions of the Masters of
Engineering Management Program taught at
Dartmouth College 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.
Target Job Functions Include:
Data
Visualization
Program Learning Outcomes:
Explore key concepts, tools, and
techniques used in data science
Explore examples of data science
applications in the industry as a result of a
dramatic growth in available data
Machine
Learning
Learn or improve your coding in Python
Apply the coding and data science
knowledge acquired to real-world business
challenges
Risk
Management
Experiment with data science tools and
techniques
Gain valuable career guidance in data
science
05
Predictive
Capabilities
Professional Certificate in Applied Data Science

LEARNING JOURNEY
Over the course of six months, you will develop a competency in data science fundamentals. By working directly
with and recieving support from industry-expert mentors, you will be prepared for a shift into a career in data
science.
EARLY PROGRAM SESSION: 4-WEEK PYTHON CODING CAMP
All students will participate in a four-week Python coding camp to prepare you to tackle the fundamentals of
data science. Live office hours and moderated discussions boards offer personalized support.
Module 1:
Practical
Applications
of Analytics
Module 6:
Logistic Regression
and Applying
GLMs
Module 2:
Data Structures
and Plotting
Module 7:
Data Visualization
Strategies
Module 8:
Experimental Design,
Causal Research,
and Targeting Analysis
Module 3:
Introduction to
Statistics and
Probability
Module 4:
Linear Models –
Ordinary Least
Squares
Module 9:
Machine Learning
Module 5:
Linear Regression:
Interactions and
Transformations
Module 10:
Final Project to Your
Job-Ready Portfolio
Your Portfolio
Professional Certificate in Applied Data Science
06

PROGRAM MODULES
Modules and assignments focus on real-world application of concepts. You will have constant support from data
science mentors in terms of learning to use and apply these concepts, as well as planning your career moves by
helping to build a job-ready portfolio.
Four Weeks:
Python Coding Camp
Before jumping into the fundamentals of data science techniques, you'll learn to
code in Python over a four-week Python data coding camp.
This is required for all participants.
Module 1:
Practical Applications
of Analytics
Examine use cases across industries of how organizations are leveraging data to
identify new opportunities as well as the increasing significance of data analytics
in capitalizing upon these opportunities.
Engage with a problem-solving framework that can be leveraged in approaching
data science problems.
Module 2:
Data Structures and
Plotting
Develop a fundamental understanding of data types, structures, and requirements
for creating models.
Module 3:
Introduction to
Statistics and
Explore and apply concepts related to statistics, probabilities, means, and
distributions.
Probability
•
Learn to format data, work with data, and create simple plots in Python.
• Explore sources, types, and requirements for data modeling
• Assess ways of understanding data through exploratory data analysis
• Explore plotting tools used to render easily comprehensible visualizations
• Practice data cleaning and assembling complex datasets
Utilize Python to create quantile-quantile plots and perform hypothesis tests.
•
07
Explore the basics of statistics, including means and distributions, Q-Q plots,
probability, and hypothesis testing
Examine the different types of models
Professional Certificate in Applied Data Science
Module 4:
Linear Models –
Ordinary Least
Squares
Apply the problem-solving framework to the creation of univariate and
multivariate linear regression models that minimize error and explain variation in
your data.
Interpret the output of models in ways that are understandable for general
audiences.
Apply metrics to regression models.
• Explore robust models in linear regression
• Assess how to interpret the outcomes of these models
Module 5:
Linear Regression:
Interactions and
Transformations
Perform Shapiro-Wilks test to assess normality and execute transformations when
necessary.
Create multivariate models with interaction variables.
Compare and select models based upon factors, such as goodness of fit and
model complexity.
Communicate results to a general audience.
• Examine model diagnostics, model fitting, and selection criteria
• Explore strategies for interpreting models and presenting results
Module 6:
Logistic Regression
and Applying GLMs
Apply the problem solving framework to the creation of logistic regression models
that determine the odds and probabilities of a given outcome.
Interpret the output of models in ways that can be communicated to a general
audience.
Apply metrics to classification models.
• Explore logistic functions, plots, and density functions
• Explore the concept of logit link function
Module 7:
Data Visualization
Strategies
Explore and apply knowledge of key strategies for effective data visualization.
Plot different types of data using Seaborn in Python.
Create a Dash interactive app in Python.
• Examine data visualization strategies
• Explore examples of effective and ineffective visualizations
Professional Certificate in Applied Data Science
08
Module 8:
Experimental Design,
Causal Research,
and Targeting Analysis
Explore techniques in experimental design, A/B testing, and Targeting Analysis.
Module 9:
Machine Learning
Apply ML techniques, such as K-means clustering, Random Forest, Classification
and Regression Trees, and Resampling through K-Fold Cross-Validation.
Perform an A/B test in Python.
• Explore causal attribution through difference-in-difference estimates and A/B
testing
• Assess the key factors to be considered while performing experiments and
research
Engage with applications of machine learning in industry.
• Explore the relevance of machine learning in the industry
• Explore algorithms that are likely to be encountered in practice, such as k-means
clustering and random forest
Module 10:
Final Project to Your
Job-Ready Portfolio
Develop a project and presentation to demonstrate the knowledge of the various
tools and techniques explored in the program.
Sample Assignments:
Explore and apply five common Machine
Learning algorithms
Perform RFM analysis to identify your
most profitable customers
Apply what you have learned throughout
the program to a final project and
presentation that will become the first
part of your data science portfolio
09
Professional Certificate in Applied Data Science

YOUR PORTFOLIO
A final capstone project allows you to pull together everything you have learned in the program and compose a
portfolio. Examples of previous student projects include:
The Power of Social Media
Quality in U.S. Healthcare
Wine Uncorked
Super Bowl Analysis
Trends and Patterns in U.S. Electricity Retail Prices
Flight Search Engine with Delay Prediction
The Brooklyn Real Estate Market
What Influences the Price of Airbnb?
Featured Student Projects
Wine Uncorked
By Avantika Agarwal, Dan Grande,
Brad Martin, Jess Nunez, Vamshi
Venkatesh, Julia Winder
Airbnb: A Data Analytics Report
By Adam Re, Deeksha Maggoo,
Mayuresh Vaidya, Neerja Bakshi and
Tayla Ma
The study explores the wonderful
world of wine through predictive
modeling and data visualization.
The study shares the case of Airbnb as
a primary focal company which uses a
platform as their primary business
model.
Flight Delayed
By Theodore Gordon, Andrew
Hennesy, Sagar Rastogi, Kam Yan
The Brooklyn Real Estate Market
By Saranya Bhattacharya, Matt
Capotosto, Gibs Donohue, Kening
Peng, Mengou Yang
The study determines what factors
most influence the probability of
flights being delayed at Boston
Logan Airport. In addition to
prediction, users will be provided
an easy visualization of the data via
Tableau.
Professional Certificate in Applied Data Science
The study presents the business case
and initial hypothesis; data
interpretation using descriptive
statistics; building a model to predict
home prices; and packaging the model
into a home seller pricing tool.
10

PROGRAM FACULTY
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
“My goal is to demystify data
analytics and help you unlock your
potential as a data scientist. Together
we will explore this landscape and
develop your toolkit so that, using
data science, you can provide
valuable solutions to your future
organization. My hope is that you will
learn the key concepts to accelerate
your journey of becoming a
successful data scientist, whatever
your industry or field of work may be.”
–Geoffrey Parker
Professor of Engineering at
Dartmouth College
Director of the Master of Engineering
Management Program at Thayer School of
Engineering
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.
Accolades
 Top 10 Harvard Business Review Must Reads for 2017; Top 10 Harvard Business Review Must Reads for
Business Models 2019 (Pipelines, platforms, and the new rules of strategy, 2016)
 Top Ten Course, Tuck School of Business, 2018 (Platforms)
 Best Paper Award, MIS Quarterly, 2017 (Platform Ecosystems: How Developers Invert the Firm)
 Golden Book Award Best Business Book, 2016 (Platform Revolution, Mandarin edition)
 All Time Top 50 Harvard Business Review article (Strategies for Two-Sided Markets)
11
Professional Certificate in Applied Data Science

PROFESSIONAL CERTIFICATE
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.
This is to certify that
John Smith
has completed the studies and satisfied the requirements for the online
Professional Certificate in Applied Data Science
February 18, 2021
Geoffrey G. Parker
Professor of Engineering
Alexis Abramson
Dean, Thayer School of Engineering
Powered by
About the Thayer
School of Engineering
at Dartmouth
Located in Hanover, New Hampshire, Dartmouth has one
of the oldest professional schools of engineering in the
country offering an engineering sciences education
unencumbered by departmental divisions that fosters
cross-disciplinary innovation in research and teaching.
Graduate programs at Thayer School of Engineering at
Dartmouth include the Master of Engineering
Management (MEM), MS, PhD, dual degrees with The
Geisel School of Medicine at Dartmouth, and the nation's
first PhD Innovation Program. Dartmouth
undergraduates study engineering as part of a liberal
arts education leading to the Bachelor of Arts (AB)
degree; most majors take additional courses leading to
the professional Bachelor of Engineering (BE) degree.
Professional Certificate in Applied Data Science
About Emeritus
The Thayer School of Engineering at Dartmouth
is collaborating with online education provider
EMERITUS to deliver its Professional Certificate
programs through a dynamic, interactive, digital
learning platform. By working with EMERITUS,
the Thayer Engineering School brings its growing
portfolio of courses online to address the
evolving demands of individuals entering the
growing field of Data Science. EMERITUS’
approach to learning is based on a cohort-based
design to maximize peer to peer sharing and
includes live teaching with world-class faculty
and hands-on project-based learning. In the last
year, more than 30,000 students from over 150
countries have benefited professionally from
EMERITUS’ programs.
12

A COMMUNITY OF LEARNERS
Using the ‘flipped classroom’ format, Professor Parker's
lecture videos will offer a high-level overview of the key
concepts. Students are encouraged to participate in
assignments with the guidance of subject matter
experts. You will engage in these assignments through
live web chats with the guidance of Course Leaders
(CLs). You will be able to share your screens while
working on these assignments and will have
opportunities to benefit both from peer learning and CL
guidance. Live Coding Sessions are one assignment
type for this program. There are also coding exercises
using platforms such as Vocareum and Atomic
Assessments.
Small group sessions allow for high-touch mentoring
and hands-on learning. Synchronous learning — when
learning occurs at the same time, but not in the same
place — replicates a classroom learning environment,
so you learn from your peers, course leaders and
13
mentors, brainstorm, share assignments, experience
team learning and community/network-building in
real-time group chats.
Assignments are built around real-world tasks that
prepare students to contribute creative input in data
science. The program is fully graded — allowing you to
not only measure your own progress but to provide
prospective employers with concrete evidence of the
skills you have mastered.
Program videos are of two types: (1) Main concept
videos and (2) coding demos. The main concept videos
are filmed with Professor Parker. These include core
frameworks of data science that won’t get outdated
and are scaffolded with demo videos (screen captures)
for Python.
Professional Certificate in Applied Data Science
Easily schedule a call with a program advisor to
learn more
SCHEDULE A CALL
You can apply for the program here
APPLY
CONNECT WITH A
PROGRAM ADVISOR
Email: dartmouth@emeritus.org
Phone: +1 315-982-5094