Our Range of Learning Paths is built to help meet your goals.

Certificates

Comprehensive expertise in a subject area for professional transformation and workplace impact
  • 2 to 6 months
  • $2,000 to $10,000
  • Online

Courses

In-depth exploration of a topic within a short amount of time, delivering powerful insights and practical skills
  • 2 to 4 weeks
  • $299 to $1,199
  • Online

Workshops

Rapid development of specific, actionable skills and strategies to be immediately applied at work
  • 3 hours
  • $449
  • Online

Degrees

Academic credentials requiring formal admissions, prerequisites, and multi-year commitment
  • 15 to 24 months part-time
  • Prices vary
  • Hybrid
Select a Data Science & Analytics Program that fits your needs
Explore and compare flexible learning opportunities from across Cornell’s portfolio of world-class Data Science & Analytics programs.
Certificates(26)
Courses(23)
Workshops(2)
Degrees(2)
Showing 26 of 26
Ask Sage

Implementing Scientific Decision Making

Course
3 weeks
Online
You are required to have completed the following course or have equivalent experience before taking this course: Understanding and Visualizing Data
$1,380

Income Inequality and Intergenerational Mobility

Course
3 weeks
Online
This course introduces you to policy and data science surrounding income inequality and intergenerational mobility in the United States. You will begin with an in-depth background on sociology, demography, and economics along with an introduction to "big data'' and how it can be used in these fields of study to address complex policy problems. You will also explore essential functions in data science and the language of R before moving on to more complex statistics and data structures that will assist you in articulating big data. You will then investigate income inequality utilizing the Opportunity Atlas data project to examine geographic differences in intergenerational income mobility. Finally, you will further study this mobility across race, ethnicity, and gender, and you will engage in several opportunities to practice your new skill set in R, data, and policy analysis.
$999

Forecasting Supply Chain Demand

Course
2 weeks
Online
Supply chain analytics are everywhere. Consider the similarities between a grocery list and a demand forecast: Before going to the store, you note which groceries you already have in your home. Next, you think about how much of each item you used in the past. Based on this information, you can predict how much of each item you need to purchase. In this micro example, you are acting as a supply chain analyst. As you look at the implications of a larger-scale supply chain analysis, you'll grasp the complexity that organizations face in making accurate demand forecasts. When grocery shopping, if you make mistakes, you can just go on another trip and correct the purchase. In business situations, however, a mistake could mean a significant loss. In this case, you want to make decisions in a scientific and proven way. In this course, you will measure performance based on an existing dataset. You will then determine the best forecasting method based on the given data. Finally, you will expand the application of this data by calculating a forecast for future demand and considering holistic approaches for mitigating risk, applying practical skills to incorporate into your future work with supply chain analytics.
$999

Individual Ethics

Course
2 weeks
Online
In this course, you will examine the foundations of ethics in both people and organizations. By acquiring the skills to identify the sources of your own ethics, you will strengthen and clarify your ethical stance in the workplace. Through this lens, you will deploy “micro-ethics” in a decisive, purposeful way to situations you might encounter as a citizen in diverse communities such as teams, professional associations, organizations, or employers. This process will be informed by a survey of the “virtue ethics” framework along with mechanisms that help you handle ethical dilemmas. By the end of this course, you will have the necessary foundation to engage with ethics on a deeper level in your personal and professional contexts.
$1,199

Interpreting and Communicating Data

Course
2 weeks
Online
This course aims to make statistical analysis approachable and practical, as you learn how to read and interpret statistical reports in a business environment, and how to communicate statistical results to stakeholders. First, you will practice assessing the statistical components and representations of statistical results in a case study. You will then identify the appropriate method and conduct a summary analysis of a data set. Finally, you will prepare an executive summary of the key statistical points identified through your analysis and create a narrative summary with supporting graphics.
$999

Constructing Expressions in Python

Course
3 weeks
Online
Expressions are a core attribute of any Python program. In this course, you will construct expressions and reuse them to manipulate and compute variables in a variety of applications. This reusability enables a "create once, use everywhere" development paradigm which will streamline development of your current and future Python programs. You will develop the knowledge and skills to assign and access variables, combine variables and data in expressions, and leverage Python as a powerful calculator. You'll also use the enhanced capabilities of the IPython environment to do interactive work with Python and to explore your data through new analyses. The knowledge and skills you gain will help you construct Python expressions to streamline the development of your current and future Python data science projects.
$999

Building Compelling Slide Decks and Reports

Course
2 weeks
Online
When communicating your ideas or significant data through PowerPoint, it is essential that your presentation clearly articulates your points. PowerPoint templates can be visually distracting and obscure valuable insights when used incorrectly. Creating your own template allows you to customize a presentation that specifically targets your audience and embodies visual integrity. Reading reports are a summary of the most valuable points of your PowerPoint presentation that you can send out to key stakeholders after a presentation or in place of a presentation. Using PowerPoint slides to develop a report allows you to easily manipulate images or content to create a visually appealing summary of your presentation for key decision-makers. In this course, you will discover the visual design principles and content guidelines necessary to curate a professional PowerPoint presentation or reading report. This will first involve developing your own PowerPoint template using the visual standards that specifically target your audience. You will have the opportunity to develop two supporting PowerPoint slides with appropriate message titles and visual evidence such as charts, graphs, photographs, or artistic elements. You will explore the structural components used in PowerPoint presentations to create a sound structure that guides your audience through your points seamlessly. Finally, you will convert two existing PowerPoint slides into a compelling and professional one-page report. Students will require access to Microsoft PowerPoint in order to successfully complete this course.
$999

Presenting Quantitative Data

Course
2 weeks
Online
While it is extremely common to hear the word "data" in business today, what is less common is an understanding of how to collect the right data and then apply it to solving business problems. In this course, you will learn foundational concepts in statistics and how to collect and interpret data while applying statistics and statistical thinking to business problems. Additionally, in the practice of business statistics, it is essential to capture accurate data but also to communicate that data clearly and effectively. You will then explore methods of presenting this type of data and try it for yourself. Lastly, it may seem far-fetched to describe numeric values collected during a business day as a story, but when quantitative data is compiled into a visual tool such as a table or graph, it can indeed tell a story about that day's business activity. In this course you will examine how to display quantitative data through tables as well as best practices you should follow to determine which method is the best choice for communicating the data at hand.
$1,380

Understanding and Visualizing Data

Course
3 weeks
Online
In order to make important business decisions, you need all the information available.
$1,380

Using Predictive Data Analysis

Course
3 weeks
Online
You are required to have completed the following courses or have equivalent experience before taking this course: Understanding and Visualizing Data Implementing Scientific Decision Making
$1,380

Modeling Uncertainty and Risk

Course
3 weeks
Online
Decision making is never as simple as we would like it to be, since rarely does a single factor alone predict an outcome. In a competitive business environment, not taking this uncertainty into account has serious costs. In this course, you'll use foundations in probability to describe risk mathematically and incorporate those calculations into your decisions so you can take them to the next level. Working through increasingly complex modeling situations, you will learn to use estimates of probable future outcomes for Go/No-Go decisions and to run a Monte Carlo simulation allowing you to examine outcomes that vary based on multiple, interdependent decisions. You are required to have completed the following courses or have equivalent experience before taking this course: Understanding and Visualizing Data Implementing Scientific Decision Making Using Predictive Data Analysis
$1,380

Getting Started with Spreadsheet Modeling and Business Analytics

Course
2 weeks
Online
In order to make important business decisions, you need all the information available.
$1,380

Making Predictions and Forecasts with Data

Course
2 weeks
Online
In order to make important business decisions, you need all the information available.
$1,380

Predictive Analytics in R

Course
3 weeks
Online
Data modeling has become a pervasive need in today's business environment. Often the volume of data you need to process goes beyond the capabilities of spreadsheet modeling. When this is the case, the statistical programming language R offers a powerful alternative. With R, you can avoid the cost of standalone statistical packages. Likewise, you don't need a huge investment in learning the structures required to use a more fully featured programming language. In this course, you will work through the basic methods of predictive analytics, including generating descriptives, visualization, single and multiple regression, and logistic regression. The benefits of using R for logistic regression are significant, and these are explored in detail. When you have completed this course, you will have gained experience developing R code to solve novel problems in which basic predictive methods are required.
$1,380

Exploring Data

Course
2 weeks
Online
Databases are a requirement for virtually all organizations as a way of storing information digitally, with SQL employed as the main programming language to communicate with and manipulate those databases. In this course, you will discover how datasets can be explored and manipulated using SQL. You will go from exploring what SQL is and writing your first query to understanding how to produce categorically targeted summary statistics from a large database. Along the way, you will explore a large dataset, filter and group data based on categorical and conditional preferences, and order that data, thereby yielding valuable insights and exemplifying best practices to bring back to your role.
$1,199

Querying Relational Databases

Course
2 weeks
Online
Data drives many real-world endeavors, which means that storing and accessing the data is foundational to success. Relational databases are an industry-standard data storage mechanism for maintaining data integrity while allowing flexible data retrieval. You will begin this course by examining the basic table structures that form a relational database. Using the relational database format, you will define connections between your data fields and determine how those can be expressed. You will then practice normalizing a relational database to ensure data integrity and reduce redundancy. As this course concludes, you will use a relational database system called OmniDB along with structured query language (SQL) to retrieve specific information from the database.
$1,199

Exploring Data Sets With R

Course
2 weeks
Online
When you think about what data analysts and data scientists do on a day-to-day basis, you might have a general understanding of types of conclusions they make, but how do they arrive at those conclusions? The statistical programming language R is widely used in data science; understanding the basics of how it works can help you manipulate and visualize data in a quick, flexible manner, and it may improve your communication with data scientists on your team. In this course, you will explore the basics of statistical programming and develop R skills. As you hone your ability to use commands in R, you will combine those basic skills to complete more complex tasks, such as data manipulation and visualization. Finally, you will examine how to repeat tasks in R, which makes it easier to manipulate large data sets. This course involves many hands-on coding exercises to help you gain confidence in your newfound programming skills. System requirements: This course contains a virtual programming environment that does not support the use of Safari, Edge, tablets, or mobile devices. Please use Chrome, Firefox, or Internet Explorer on a computer for this course.
$999

Understanding Data Analytics

Course
2 weeks
Online
By some estimates, 90% of the data that has ever existed has been created in the last two years. This is a staggering figure and has given rise to new challenges and opportunities in almost every industry: What kind of data do you need to collect to compete, and how can you make sense of it once you have collected it? As technology evolves and the volume of data increases, how can you make the best use of all this information? How can you use the data to help drive your decision-making? How can you make data work for you? How can you ensure your data accurately reflects the population in which you're interested? In this course, you will determine the types of engineering and business questions you can answer, the kinds of problems you can solve, and the decisions you can make, all through using data analytics. You will explore best practices for collecting information so that you can make informed predictions, develop insights, and better inform organizational decision-making. You will see real-world examples that demonstrate how those tools work. Additionally, you will have a chance to apply some of the concepts to your own work. You will explore best practices for sampling and examine how different types of sampling are suited for different situations. Finally, you will see real-world examples that demonstrate how those tools work and have a chance to practice sampling techniques in some case-study scenarios.
$1,199

Finding Patterns in Data Using Association Rules, PCA, and Factor Analysis

Course
2 weeks
Online
Visualization is one of the most simple and effective ways to find patterns in data. These patterns include: What is the general range and shape of the data set? Are there any clusters of observations? Which variables correlate with each other? Are there any obvious outliers? As your data set grows in terms of the number of data points and variables, however, it becomes increasingly difficult to visualize all this information at once. At most, you can plot data points on a three-dimensional axis and add further distinctions of size, color, shape, and so on. Yet this can easily become too busy and difficult to read. How, then, do we find patterns in really big data sets? In this course, you will explore several powerful and commonly utilized techniques for distilling patterns from data. You will implement each of these techniques using the free and open-source statistical programming language R with real-world data sets. The focus will be on making these methods accessible for you in your own work. You are required to have completed the following course or have equivalent experience before taking this course: Understanding Data Analytics
$1,199

Finding Patterns in Data Using Cluster and Hotspot Analysis

Course
2 weeks
Online
When you have large groups of objects, it is often helpful to split them into meaningful groups or clusters. One example of this would be to identify different types of customers so that a company can more efficiently route their calls to a helpline. As a second example, suppose an automobile manufacturer wanted to segment their market to target the ads more carefully. One approach might be to take a database of recent car sales, including the social demographics associated with each customer, and segment the population purchasing each type of automobile into meaningful groups. Specialized approaches exist if your data contains information that relates to time and geography. You can use this additional information to identify geographical and temporal hotspots. Hotspots are regions of high activity or a high value of a particular variable. These results can help you focus your attention on a particular region where a problem is occurring more than usual, such as the incidence of asthma in a large city. In both cluster and hotspot analysis, the results can help you discover new and interesting features, problems, and red flags regarding the data being analyzed. In this course, you will explore several powerful and commonly utilized techniques for performing both cluster and hotspot analysis. You will implement these techniques using the free and open-source statistical programming language R with real-world data sets. The focus will be on making these methods accessible and applicable to your work. You are required to have completed the following courses or have equivalent experience before taking this course: Understanding Data Analytics Finding Patterns in Data Using Association Rules, PCA, and Factor Analysis
$1,199

Regression Analysis and Discrete Choice Models

Course
2 weeks
Online
A story can play an important role in understanding data. It can help distill complex information into something manageable- something we can think about easily, relate to, and use to make decisions. For many problems that we encounter globally, however, a story that describes what already happened is not enough precision for the job we want to perform. Often, we would like to use available data to make numerically accurate predictions about what might happen in the future. This task requires the construction of mathematical models that are well suited to our real-world problems. In this course, you will explore several types of statistical models used with data to make predictions. These models bring with them a whole batch of important concerns, such as estimation and validation, that make the entire process into both an art and a science. You will implement each of these techniques using the free and open-source statistical programming language R with real-world data sets. The focus will be on making these methods accessible for you in your own work. You are required to have completed the following courses or have equivalent experience before taking this course: Understanding Data Analytics Finding Patterns in Data Using Association Rules, PCA, and Factor Analysis Finding Patterns in Data Using Cluster and Hotspot Analysis
$1,199

Supervised Learning Techniques

Course
2 weeks
Online
Supervised learning is a general term for any machine learning technique that attempts to discover the relationship between a data set and some associated labels for prediction. In regression, the labels are continuous numbers. This course will focus on classification, where the labels are taken from a finite set of numbers or characters. The prototypical and perhaps most well-known example of classification is image recognition. The goal is to take an image (represented by its pixel values) and determine what objects are in the image. Is it a dog? A grapefruit? A stop sign? There are many practical classification tasks, such as determining whether an individual's financial history makes them high risk for a loan, whether there is a defect in a material based on some sensor readings, or whether a new email is spam or not. These problems share the same basic form and can be solved with many different types of mathematical, statistical, and probabilistic models developed by the machine learning community. In this course, you will explore several powerful and commonly utilized techniques for supervised learning. You will implement each of these techniques using the free and open-source statistical programming language R with real-world data sets. The focus will be on making these methods accessible for you in your own work. You are required to have completed the following courses or have equivalent experience before taking this course: Understanding Data Analytics Finding Patterns in Data Using Association Rules, PCA, and Factor Analysis Finding Patterns in Data Using Cluster and Hotspot Analysis Regression Analysis and Discrete Choice Models
$1,199

Neural Networks and Machine Learning

Course
2 weeks
Online
Neural networks, a nonlinear supervised learning modeling tool, have become hugely popular within the last two decades because they have been successfully applied to a wide range of problems, including automatic language processing, image classification, object detection, speech recognition, and pattern recognition. They are mathematical models that are loosely built up based on an analogy to the interconnected neuron in the brain. They take in a vector or matrix of input data and output either a classification value or an approximation to a functional value. The beauty is that the relationships between the inputs and outputs can be highly non-linear and complex. In this course, you will explore the mechanics of neural networks and the intricacies involved in fitting them to data for prediction. Using packages in the free and open-source statistical programming language R with real-world data sets, you will implement these techniques. The focus will be on making these methods accessible for you in your own work. You are required to have completed the following courses or have equivalent experience before taking this course: Understanding Data Analytics Finding Patterns in Data Using Association Rules, PCA, and Factor Analysis Finding Patterns in Data Using Cluster and Hotspot Analysis Regression Analysis and Discrete Choice Models Supervised Learning Techniques
$1,199

Grow Your Analytics Expertise

Cornell University’s selection of Data Science & Analytics programs, including 15+ certificates, combines technical depth with practical business application through expert-led instruction and small cohorts. Participants learn from Cornell faculty at the forefront of data science research while gaining hands-on experience through personalized projects, collaborative learning, and engagement with global data professionals.

Explore Program Details
Program TypeEducational GoalCourse FormatOfferedCourse StructureDurationTotal HoursWeekly Commitment
Certificates
Comprehensive expertise in a subject area for professional transformation and workplace impactOnline cohort-based (<35 students) with expert facilitator hosting live sessionsRecurring start datesMost certificates include 4 to 8 individual courses with multiple start and end dates to select from; 360 Certificates offer over 20+ individual courses including core courses and electives2 to 6 months depending on individual course requirements40 to 100 hours3 to 8 hours per week for the duration of the certificate
Courses
In-depth exploration of a topic within a short amount of time, delivering powerful insights and practical skillsOnline cohort-based (<35 students) with expert facilitator hosting live sessionsRecurring start datesOne standalone course with multiple start and end dates to select from2 to 4 weeks depending on individual course requirements10 to 25 hours3 to 8 hours per week for the duration of the certificate
Workshops
Rapid development of specific, actionable skills and strategies to be immediately applied at workLive, online, and Cornell faculty-led with an interactive cohortSpecific dates and timesOne 3-hour short-form live program with specific dates and times; multiple Workshops offered monthly3 hours3 hoursActive participation during the Workshop only
Degrees
Academic credentials requiring formal admissions, prerequisites, and multi-year commitmentOnline cohort-based and on campus in Ithaca, NYSpecific start dates once a year, often in January or AugustA series of 2- to 15-week asynchronous online courses designed by Cornell faculty with weekly live virtual sessions, with between one and three week-long residency sessions on campus in Ithaca, NY15- to 24-month part-time program for working professionalsVary by degree15 to 20 hours per week during each online course; full-time on campus during each week-long residency

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