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.

Since this course requires an intermediate knowledge of Python, you will spend the first part of this course learning Python for Data Analytics taught by Emeritus. This will provide you with the programming knowledge required to do the assignments and application projects that are part of the Applied Data Science course.


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.


Explore the theory, languages and concepts of this in-demand field while acquiring the Python programming knowledge you need to solve real-world data challenges. At the end of the course, you will be able to:

  • UTILIZE Python programming language to code your own algorithms or analytical models to examine data.
  • MANAGE and manipulate a large amount of data using Python packages.
  • REVEAL hidden yet important characteristics of any dataset using visual tools already built into Python.
  • FORMULATE explanations for past events and determine if it is true using available data.
  • DISCOVER hidden trends and draw useful insights using software packages designed for use with Python, like NumPy and Pandas
  • UNEARTH quality information from analysis of text-data like Facebook or Twitter posts and comments
  • CLASSIFY data points in a larger dataset; for example, assigning genres to one billion songs.
  • IDENTIFY relationships between data points to form groups in a larger data set; for example, grouping customers into segments using their previous buying patterns.

Emeritus and Columbia Engineering Executive Education

Columbia Engineering Executive Education is collaborating with online education provider Emeritus to offer executive education courses.

An Emeritus Certificate course created in collaboration with Columbia Engineering Executive Education is based on syllabus approved by Columbia Engineering Executive Education, and contains video content created and recorded by Columbia Engineering Executive Education faculty, combined with assessments, assignments, projects, cases, and exercises delivered by Emeritus. Upon successful completion of the course, learners will be awarded a certificate jointly by Emeritus and Columbia Engineering Executive Education.

You can read more about the collaboration here.


Take the first step to a Global Education

Your details will not be shared with third parties. Privacy Policy

  • Starts on

    November 17, 2020

  • Duration

    5 Months, Online

    (6 - 8 hours per week)
  • Course Fees

    US$ 2,350*

Curriculum & Faculty


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’t 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

Industry Examples

Data Exploration using Lending Club Loan Data

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.
Data Wrangling using CNC Mill Tool Wear Data

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 munching skills using Python’s pandas and NumPy libraries with the CNC Mill Tool Wear dataset.
Hypothesis Testing using Cancer Atlas Data

Hypothesis Testing using Cancer Atlas Data

  • Statistically test the impact of health factors in relation to cancer rates from around the globe.
Natural Language Processing (NLP) implementation using Amazon product reviews

Natural Language Processing (NLP) implementation using Amazon product reviews

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


Costis Maglaras
Costis Maglaras

Dean of Columbia Business School
David and Lyn Silfen Professor of Business

Hardeep Johar
Hardeep Johar

Senior Lecturer Of Industrial Engineering And Operations Research

Vineet Goyal
Vineet Goyal

Associate Professor Industrial Engineering And Operations Research

Learning Experience

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

  • Orientation Week
    Orientation 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.
  • Weekly Goals
    Weekly 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.
  • Recorded Video Lectures
    Recorded Video Lectures
    The recorded video lectures are by faculty from the collaborating university.
  • Live Webinars
    Live 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 Doubts
    Clarifying 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-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.
  • Continued Course Access
    Continued 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.



Assignments are given out weekly and they are based on the lectures or tutorials provided. They need to be completed and submitted as per the deadline for grading purposes. Extensions may be provided based on a request sent to the support team.

Discussion Boards

It is an open forum where participants pin their opinions or thoughts regarding the topic under discussion.


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.


Emeritus Network

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.


Program Highlights

Live Online Teaching
1 Live Online Teaching
12 Assignments
Moderated Discussion Boards
24 Moderated Discussion Boards
Q&A Sessions with Course Leaders
20 Q&A Sessions with Course Leaders
Quizzes / Assignments
50 Quizzes / Assignments
Faculty Video Lectures
200+ Faculty Video Lectures

Benefits to the Learner

Social Capital

Social Capital

  • Build new networks through peer interaction
  • Benefit from diverse class profiles
Brand Capital

Brand Capital

  • Certificate from Emeritus in collaboration with Columbia Engineering Executive Education
Intellectual Capital

Intellectual Capital

  • Global Business Education
  • Rigorous and experiential curriculum
  • World-renowned faculty
  • Globally connected classroom: peer to peer learning circles
  • Action learning: learning by doing
Career capital

Career capital

  • Professional acceleration through our enriched leadership toolkit
  • Learn while you earn
  • Get noticed. Get ahead.


Applied Data Science - Certificate Click to view certificate



  • The course requires an undergraduate knowledge of statistics (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation, etc.), calculus, linear algebra, and probability.


  • You can pay for the course either with an international debit or credit card, or bank wire transfer. On clicking the apply now button, 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

Participant Profile

Participant Experience


Evangelos-Marios Nikolados

Postgraduate Researcher, Imperial College London
Applied Data Science

I fairly enjoyed the flow in each week's module. Given an option, I would definitely take more module per week.


Jose Mansutti

Quality Manager, Tenaris
Applied Data Science

The Text Mining module was enlightening. The resources and potentialities of the tool were very well explained.


Shahid Mohsin Tanwar

Manager, Mahindra and Mahindra Ltd
Applied Data Science

What I liked about the course was the clarity in concepts and good use of examples. The course leaders, support team and professors gave a superb explanation and provided overall support during webinars, office hours and on mail.


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