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Data Science for Business


DATA SCIENCE FOR BUSINESS

Move Beyond the Spreadsheet

Data Science for Business teaches you how to effectively use data to tackle your
business decisions and motivate those around you to take action based on
evidence. Designed for managers, this course provides a hands-on approach for
demystifying the data science ecosystem and making you a more conscientious
consumer of information.

Brought to you by:






WHAT YOU'LL LEARN

The course will be delivered via HBS Online’s course platform and immerse
learners in real-world examples from experts at industry-leading organizations.
By the end of the course, participants will be able to:

Play an Introduction to Data Science Ready video with Audio Descriptions
Play an Introduction to Data Science Ready video with Audio Descriptions
Go to Course Syllabus
 * Move beyond the spreadsheet with a foundational understanding of data science
   tools, processes, and models, to understand the importance of data science
   and how it relates to business decisions and organizational success
 * Leverage data science to hone your decision-making skills and learn how to
   identify and avoid common mistakes while interpreting datasets, metrics, and
   visualizations
 * Create a data-driven framework for your organization and for yourself;
   develop hypotheses and insights; identify data and missing components; and
   speak a common language with your data teams to lead to actionable
   recommendations
 * Understand key techniques such as data curation, regression models,
   prediction and analyses, and visualization, and learn how to read basic code,
   such as R, in order to comprehend the syntax that informs data requests
 * Assess applicable methodologies in statistics, data analytics, and data
   science by hearing from real-world examples across industries, topics, and
   business challenges



ABOUT THE PROFESSOR

Yael Grushka-Cockayne is the Altec Styslinger Foundation Bicentennial Chair in
Business Administration and Senior Associate Dean for Professional Degree
Programs at the University of Virginia Darden School of Business, and was
formerly a Visiting Professor of Business Administration at Harvard Business
School and Professor of Business Administration. Her research and teaching
activities focus on data science, forecasting, project management, and
behavioral decision-making. Her research is published in numerous academic and
professional journals, and she is a regular speaker at international conferences
in the areas of decision analysis, project management, and management science.
In 2014, Grushka-Cockayne was named one of "21 Thought-Leader Professors" in
Data Science.




WHO WILL BENEFIT


ASPIRING MANAGERS

Get a headstart on your next career by gaining new technical skills and a
data-driven mindset.


MANAGERS AND RISING LEADERS


Dig into your organization’s datasets to create compelling business plans that
increase revenue while mitigating risk.


PRODUCT MANAGERS

Develop market-driven products by using data to identify and predict market
size, competition, and buyer trends.




PROGRAM STRUCTURE

Data Science for Business consists of approximately 20 hours of material
delivered over a four-week period. You can complete the coursework on your own
time while meeting regular deadlines.


Coming Soon
 * Length: 4 Weeks
 * Cost: $1,600
 * Dates to Be Announced Soon

Sign Up for Alerts

 * 
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SYLLABUS

Data Science for Business will teach you how to think beyond the spreadsheet,
and effectively use data to tackle your business decisions, becoming a stronger
manager. By the end of the course, you should understand how to create a
data-driven framework for your organization or yourself; develop hypotheses and
insights from visualization; identify data mistakes or missing components; and,
speak the language of data science across themes such as forecasting, linear
regressions, and machine learning to better lead your team to long-term success.

Learning requirements: In order to earn a Certificate of Completion from Harvard
Online and Harvard Business School Online, participants must thoughtfully
complete all 6 modules, including associated quizzes, by stated deadlines.

Download Syllabus (pdf)



Modules Case Studies Takeaways Key Exercises Module 1: The Data Science Shift
 * Carvana: Good Data and Bad Buys

 * Apply the steps of the Data Driven Decision Framework
 * Identify the benefits that data science brings to business problems

 * Translate business problems into data hypotheses
 * Explore and describe datasets
 * Use visualizations to generate hypotheses

Module 2: Data Wrangling
 * Fannie Mae: Identifying Investments

 * Relate the quality of data with the the quality of the conclusions
 * Assess the quality of data
 * Guide decisions for merging tables and managing missing data

 * Prepare and clean data for analysis
 * Examine data dictionaries
 * Design table joins
 * Identify solutions for managing missing data

Module 3: Visualization
 * StockX: Drawing Demand

 * Incorporate visualizations throughout the data science process
 * Interpret charts and graphs
 * Develop questions from visualizations
 * Design visualizations for clear communication with maximal impact

 * Critique existing charts and identify methods of improvement
 * Generate insight with graphs
 * Design visualizations to express data clearly

Module 4: Time Series Forecasting
 * NICU beds: Creating Capacity

 * Connect yesterday’s data with tomorrow’s prediction
 * Evaluate temporal patterns in data
 * Match the time scale with the business problem
 * Select appropriate smoothing techniques for time series forecasting

 * Determine when time series analysis is useful and informative
 * Select appropriate methods for exponential smoothing

Module 5: Linear Regressions
 * Bark Gift Shop: Motivating Managers
 * ATO Pictures: Marketing Movies

 * Interpret linear regression results
 * Extend intuition into analysis
 * Apply advanced methods to gain sophistication and insight to your
   understanding

 * Identify relationships between variables
 * Write hypotheses
 * Explain the parts of a linear model, including interactions and dummy
   variables
 * Interpret linear regression results

Module 6: Logistic Regressions and Machine Learning
 * Carvana and Fannie Mae

 * Differentiate linear and logistic regression
 * Conceptualize Machine Learning
 * Evaluate model fit

 * Complete a confusion matrix
 * Interpret results from logistic regression, CART, random forest, lasso, and
   neural networks
 * Select a model to guide decisions

Syllabus
Module 1: The Data Science Shift
Case Studies
 * Carvana: Good Data and Bad Buys

Takeaways
 * Apply the steps of the Data Driven Decision Framework
 * Identify the benefits that data science brings to business problems

Key Exercises
 * Translate business problems into data hypotheses
 * Explore and describe datasets
 * Use visualizations to generate hypotheses

Module 2: Data Wrangling
Case Studies
 * Fannie Mae: Identifying Investments

Takeaways
 * Relate the quality of data with the the quality of the conclusions
 * Assess the quality of data
 * Guide decisions for merging tables and managing missing data

Key Exercises
 * Prepare and clean data for analysis
 * Examine data dictionaries
 * Design table joins
 * Identify solutions for managing missing data

Module 3: Visualization
Case Studies
 * StockX: Drawing Demand

Takeaways
 * Incorporate visualizations throughout the data science process
 * Interpret charts and graphs
 * Develop questions from visualizations
 * Design visualizations for clear communication with maximal impact

Key Exercises
 * Critique existing charts and identify methods of improvement
 * Generate insight with graphs
 * Design visualizations to express data clearly

Module 4: Time Series Forecasting
Case Studies
 * NICU beds: Creating Capacity

Takeaways
 * Connect yesterday’s data with tomorrow’s prediction
 * Evaluate temporal patterns in data
 * Match the time scale with the business problem
 * Select appropriate smoothing techniques for time series forecasting

Key Exercises
 * Determine when time series analysis is useful and informative
 * Select appropriate methods for exponential smoothing

Module 5: Linear Regressions
Case Studies
 * Bark Gift Shop: Motivating Managers
 * ATO Pictures: Marketing Movies

Takeaways
 * Interpret linear regression results
 * Extend intuition into analysis
 * Apply advanced methods to gain sophistication and insight to your
   understanding

Key Exercises
 * Identify relationships between variables
 * Write hypotheses
 * Explain the parts of a linear model, including interactions and dummy
   variables
 * Interpret linear regression results

Module 6: Logistic Regressions and Machine Learning
Case Studies
 * Carvana and Fannie Mae

Takeaways
 * Differentiate linear and logistic regression
 * Conceptualize Machine Learning
 * Evaluate model fit

Key Exercises
 * Complete a confusion matrix
 * Interpret results from logistic regression, CART, random forest, lasso, and
   neural networks
 * Select a model to guide decisions





THE HBS ONLINE ADVANTAGE

Play an Introduction to the HBS Online Platform video with Audio Descriptions
Play an Introduction to the HBS Online Platform video with Audio Descriptions
 * World-class faculty
 * Edge-of-your-seat online learning
 * Global peer collaboration and networking
 * Real-world, case-based learning

Harvard Business School Online offers a unique and highly engaging way to learn
vital business concepts. Immerse yourself in real challenges faced by business
leaders across a variety of industries. You’ll wrestle with the same issues and
imperfect information, while problem-solving and interacting with fellow
learners from around the world.



Play students explain their experience an HBS Online course video with Audio
Descriptions
Play students explain their experience an HBS Online course video with Audio
Descriptions
Play students explain their experience an HBS Online course video with Audio
Descriptions
Play students explain their experience an HBS Online course video with Audio
Descriptions


STORIES FROM OUR LEARNERS

 * > This course was impactful especially using case studies of real-life
   > situations to solve complex and confusing problems. The results of this
   > will help improve my managerial decisions within and outside the
   > organizations to minimize risks and increase profits
   
   
   Bamidele Ajisogun,
   Sr. Project Analyst Business Intelligence, Strategy, Product Development &
   Innovation UPMC Workpartners

 * > This course had an amazing instructor, amazing examples, and an amazing
   > user interface that made it easy for me to grasp the material and learn
   > simultaneously with others around the world.
   
   
   Shawn Carrington, Jr.,
   Senior Executive Officer Perspecta, Inc.

 * > The platform was engaging, innovative, and allowed me to interact with the
   > material in a way I never expected from an online course.
   
   
   Bethany Larson,
   HBS Online Participant

 * > I had never experienced such an immersive platform online, and could argue
   > that it was more effective at building and solidifying knowledge than some
   > of the in-class courses I took in college.
   
   
   Ryan Dumlao,
   HBS Online Participant

 * 
 * •
 * •
 * •
 * •
 * 








REQUEST MORE INFORMATION


Sign up to receive additional information about this course. Find out what other
learners are doing with the skills they gained, and evaluate if this course is
the right fit for you.



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FREQUENTLY ASKED QUESTIONS


Do I have to log in at a set time? How does the grading process work? At this
point, you probably have a few questions, and we’ve got answers.



Learn More

Learn More



ENROLLMENT ELIGIBILITY


Our easy online application is free, and no special documentation is required.
All applicants must be at least 18 years of age, proficient in English, and
committed to learning and engaging with fellow participants throughout the
course. We confirm enrollment eligibility within one week of your application.




Earn Your Certificate

Enroll today in Harvard Online's Data Science for Business course.




 
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HOW ARE HBS ONLINE COURSES DELIVERED?

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platform.

Our platform features short, highly produced videos of HBS faculty and guest
business experts, interactive graphs and exercises, cold calls to keep you
engaged, and opportunities to contribute to a vibrant online community.



DO I NEED TO COME TO CAMPUS TO PARTICIPATE IN HBS ONLINE PROGRAMS?

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No, all of our programs are 100 percent online, and available to participants
regardless of their location.



HOW DO I ENROLL IN A COURSE?

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All programs require the completion of a brief application. The applications
vary slightly from program to program, but all ask for some personal background
information. You can apply for and enroll in programs here. If you are new to
HBS Online, you will be required to set up an account before starting an
application for the program of your choice.

Our easy online application is free, and no special documentation is required.
All applicants must be at least 18 years of age, proficient in English, and
committed to learning and engaging with fellow participants throughout the
program.

After submitting your application, you should receive an email confirmation from
HBS Online. If you do not receive this email, please check your junk email
folders and double-check your account to make sure the application was
successfully submitted.

Updates to your application and enrollment status will be shown on your
Dashboard. We confirm enrollment eligibility within one week of your
application.



DOES HARVARD BUSINESS SCHOOL ONLINE OFFER AN ONLINE MBA?

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No, Harvard Business School Online offers business certificate programs.



WHAT ARE MY PAYMENT OPTIONS?

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We accept payments via credit card, Western Union, and (when available) bank
loan. Some candidates may qualify for scholarships or financial aid, which will
be credited against the Program Fee once eligibility is determined. Please refer
to the Payment & Financial Aid page for further information.

We also allow you to split your payment across 2 separate credit card
transactions or send a payment link email to another person on your behalf. If
splitting your payment into 2 transactions, a minimum payment of $350 is
required for the first transaction.

In all cases, net Program Fees must be paid in full (in US Dollars) to complete
registration.



WHAT ARE THE POLICIES FOR REFUNDS AND DEFERRALS?

+–

After enrolling in a program, you may request a withdrawal with refund (minus a
$100 nonrefundable enrollment fee) up until 24 hours after the start of your
program. Please review the Program Policies page for more details on refunds and
deferrals. If your employer has contracted with HBS Online for participation in
a program, or if you elect to enroll in the undergraduate credit option of the
Credential of Readiness (CORe) program, note that policies for these options may
differ.


 





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