Data has been called the new global currency, and its meteoric rise is transforming entire industries and driving the demand for practitioners who can wield its power. From health care and finance to entertainment, cybersecurity and beyond, the need for data scientists continues to grow in tandem opportunities for career advancement within the field.

To help fill this talent gap and further the use of data science to solve real-world problems, Columbia Engineering Executive Education has partnered with EMERITUS to create the Applied Data Science course.

Our approach to this course is to teach the underlying concepts and statistics of Data Science.

Going beyond the theory, our approach invites participants into a conversation, where learning is facilitated by live subject matter experts and enriched by practitioners in the field of data science. We expect learners would be required to put in 6-8 hours per week.

Upon successful completion of the course, participants will receive a verified digital certificate from EMERITUS in collaboration with Columbia Engineering Executive Education.



Data has been called the new global currency, and its meteoric rise is transforming entire industries and driving the demand for practitioners who can wield its power. From health care and finance to entertainment, cyber security and beyond, the need for data scientists continues to grow in tandem with opportunities for career advancement within the field. This course is highly effective for professionals looking to fill this talent gap and further the use of data science to solve real-world problems.

Previous batches have come from

  • Industries: Banking, Software, Consulting, Education, Telecommunication, Healthcare and Energy industries.
  • Countries: United States, India, United Kingdom, Canada, Australia, France, Mexico, Germany.



At the end of the course you will be able to

  • Learn the basics of programming using python – (only tool used) right from how to acquire data (data acquisition) to its basic uses in Machine Learning
  • Help introduce you to the fundamental concepts on statistics
  • Working knowledge of algorithms to deal with data

EMERITUS and Columbia Engineering

Columbia Engineering is committed to pushing the frontiers of knowledge and shaping discoveries to meet the needs of society. Over the years, Columbia’s faculty and students have made remarkable contributions that have spurred technological and social progress. Today, Columbia carries the tradition of innovation as engineering transforms nearly every aspect of life. Faculty at Columbia Engineering have won 10 Nobel Prizes in physics, chemistry, medicine, and economics.


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  • Faculty Video Lectures
  • Peer Learning
    Moderated Discussion Boards
  • assignment icon
  • Real World Applications
    Application Projects
  • Q&A Sessions with Course Leaders
  • webinar
    Live Online Teaching



Import and analyze data with NumPy and Pandas

Clean and visualize data with Pandas and Matplotlib

Understand the shape of data

What to do when you don’ have or need all the data

How to answer common questions about your data

Introduction to modeling and interpretation

Determine and evaluate the right model for your data

Intro to Machine Learning for binary outcomes

Deeper dive into classification methods

Introduction to unsupervised methods in machine learning

Automatic understanding of text sentiment

Automatic understanding of text topics


Data Wrangling using CNC Mill Tool Wear Data

  • Practice using Python’s data framework to process and manipulate data with the CNC Mill Tool Wear dataset.
  • Hone your data wrangling and munging skills using Python’s pandas and NumPy libraries with the CNC Mill Tool Wear dataset.

Hypothesis Testing using Cancer Atlas Data

  • Statistically test the impact of health factors in relation to cancer rates from around the globe.

Data Exploration using Lending Club Loan Data

  • Use Python’s NumPy library to explore and uncover insights in Lending Club’s loan data.
  • Using Python’s powerful Pandas library to wrangle and munch Lending Club’s loan data.

Natural Language Processing (NLP) implementation using Amazon product reviews

  • Implement Natural Language Processing (NLP) techniques to automate the understanding of product reviews from Amazon.


  • Vineet Goyal
    Vineet Goyal
    Associate Professor Industrial Engineering And Operations Research
    Columbia Engineering Executive Education
  • Costis Maglarasy
    Costis Maglaras
    David And Lyn Silfen Professor of Business
    Columbia Business School Executive Education
  • Hardeep Johar
    Hardeep Johar
    Senior Lecturer Of Industrial Engineering And Operations Research
    Columbia Engineering Executive Education


EMERITUS follows a unique online model. This model has ensured that nearly 90 percent of our learners complete their course.

  • OrientationOrientation Week
    The first week is orientation week. During this week you will be introduced to the other participants in the class from across the world. You will also learn how to use the learning platform and other learning tools provided.
  • Goal SettingWeekly Goals
    On other weeks, you have learning goals set for the week. The goals would include watching the video lectures and completing the assignments. All assignments have weekly deadlines.
  • Video LecturesRecorded Video Lectures
    The recorded video lectures are by faculty from the collaborating university.
  • Live WebinarsLive Webinars
    Every few weeks, there are live webinars conducted by EMERITUS course leaders. Course leaders are highly-experienced industry practitioners who contextualize the video lectures and assist with questions you may have regarding your assignments. Live webinars are usually conducted between 1 pm and 3 pm UTC on Tuesdays and Wednesdays.
  • Clarifying DoubtsClarifying Doubts
    In addition to the live webinars, for some courses, the course leaders conduct Office Hours, which are webinar sessions that are open to all learners. During Office Hours, learners ask questions and course leaders respond. These are usually conducted every alternate week to help participants clarify their doubts pertaining to the content.
  • Follow-UpFollow-Up
    The EMERITUS Program Support team members will follow up and assist over email and via phone calls with learners who are unable to submit their assignments on time.
  • Continuous Course AccessContinued Course Access
    You will continue to have access to the course videos and learning material for up to 12 months from the course start date.

EMERITUS Program Support Team

If at any point in the course you need tech, content or academic support, you can email program support and you will typically receive a response within 24 working hours or less.


Device Support

You can access EMERITUS courses on tablets, phones and laptops. You will require a high-speed internet connection.



On completing the course you join a global community of 5000+ learners on the EMERITUS Network. The Network allows you to connect with EMERITUS past participants across the world.



  • Starts 27 June 2019
  • 3 Months
  • 6-8 hours per week
  • Course Fees USD 1400


  • The course requires an undergraduate knowledge of statistics (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation etc.), linear algebra, and probability.
  • All assignments/application projects will be done using the Python programming language. You should have an intermediate knowledge of Python or you should have completed the Emeritus Python for Data Science course prior to joining this course.


  • You can pay for the course either with an international debit or credit card (unfortunately we are unable to accept Diners credit cards), or through a bank wire transfer. On clicking the apply now button below, you will be directed to the application form and the payment page.
  • We provide deferrals and refunds in specific cases. The deferrals and refund policy is available here.
  • You will be provided a course login within 48 hours of making a payment.


  • Please provide your work experience and your current employer via the application.
  • You can apply by clicking the Apply Now button


We have listed two type of FAQs:

  • FAQs common to all courses. These are available at COMMON FAQs
  • Course specific FAQs




  • Applied Machine Learning:
    Teaches you the essential statistical tools and methods, and algorithms that can help you create models that can analyse vast amount of data to predict outcomes that can be immensely useful for your personal and business ventures alike. By working on the real-life application projects, you also acquire the knowledge of how different algorithms are used in different kinds of industry scenarios.
  • Applied Data Science:
    Teaches you the essentials of data science – from extraction, visualization to analysis and insights. Via EDA, this course will let you discover the underlying patterns in the vast quantity of data, and let you answer the whys and whats about those data points using hypothesis testing. In this course you will learn to use foundational ML algorithms to derive sentiments from text, group data points or split datasets to find insights.
  • Applied Artificial Intelligence:
    Teaches you to the essentials of creating intelligent systems. Starting with the foundation of AI, this course teaches you the tools and techniques that make a system intelligent – search techniques, machine learning algorithms to group data points or split datasets to find insights, finding fast and optimal solutions to highly complex problems bound by real-world constraints, decide the best logical course of action to achieve its goal.

The Applied Data Science course is a rigorous 3-month online certificate course designed for working professionals to develop practical knowledge and skills, establish a professional network, and accelerate entry into data science careers.

The rise of data science is disrupting entire industries. Everyone from biologists and movie makers to car makers and restaurateurs has begun to realize that data science is transforming their profession. This has led to a surge in the demand for data scientists which is expected to continue over the next several years. The objective of this course is to provide professionals with a knowledge of Data Science concepts, including expertise in relevant tools/languages and an understanding of popular algorithms and their applications.

With the knowledge gained in this course, you’ll be able to introduce the techniques to organizations not yet utilizing Data Science. Business Analysts/Data Professionals looking to move into Data Science roles will particularly benefit from this course.

This certificate course will prepare you for a variety of job roles, such as Data Scientist, Data Science Engineer, Business Analyst – Data Science, Data Science Project Lead, Data & Analytics Manager and more.

This course is designed for professionals currently in or seeking to secure a position as a:

  • Data Analyst
  • Business Analyst
  • Statistician/Mathematician
  • Data Engineer
  • Big Data Engineer
  • Software Developer

Absolutely! Knowledge of Data Science has become a requisite across industries, and all businesses will eventually need to use these techniques to thrive. While your current role may not require Data Science knowledge, it is almost certain that Data Science skills will be in high demand in almost every industry in the future.

This course is NOT intended to provide superficial Data Science concepts. Rather, the course delves deeper and is aimed at developing professionals who can advance their careers as practitioners in Data Science roles.

Columbia Engineering Executive Education is collaborating with online education provider EMERITUS Institute of Management to offer a portfolio of high-impact online courses. These courses leverage Columbia’s thought leadership in management practice developed over years of research, teaching, and practice.

Recommended System Requirements

  • Processors: 2.60 GHz
  • RAM: 8 GB of RAM
  • Disk space: 2 to 3 GB
  • Operating systems: Windows 10, MacOS and Linux
  • Python download link (Links to an external site)
  • Compatible tools: Any text editor, Command prompt

Minimum System Requirements

  • Processors: 1 GHz
  • RAM: 1 GB of RAM
  • Disk space: 1 GB
  • Operating systems: Windows 7 or later, MacOS and Linux
  • Python versions: 2.7.X, 3.6.X (Links to an external site)
  • Compatible tools: Any text editor, Command prompt


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