Overview

Data science and machine learning are transforming entire industries and becoming an entrenched part of everyday life. The data revolution has led to a spike in the demand for data scientists and machine learning practitioners that shows no signs of slowing down.

The Postgraduate Diploma in Applied Data Science can help you meet this demand and accelerate your career in data science. Created in collaboration with Columbia Engineering Executive Education, the course will provide you with a deep knowledge of data science and machine learning concepts you can immediately put to work to solve data problems in your organization.

Emeritus and Columbia Engineering Executive Education

Columbia Engineering Executive Education is collaborating with online education provider Emeritus Institute of Management (Emeritus) to offer executive education courses.

An Emeritus Postgraduate Diploma contains multiple Emeritus Certificate courses created in collaboration with Columbia Engineering Executive Education, and may also include courses created independently by Emeritus. Upon successful completion, learners will be awarded a Postgraduate Diploma by Emeritus.

You can read more about the collaboration here.

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

Participants are required to possess an intermediate knowledge of Python since all assignments/application projects will be done using the Python programming language. Emeritus offers a complimentary Python for Data Science certificate course to meet this prerequisite. Participants who successfully complete this certificate course will receive a certificate of completion from Emeritus.

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  • Starts on

    Coming Soon

  • Duration

    9 Months, Online

    (6-8 hours per week)
  • Program Fees

    US$ 3,000*

  • * Payable in 2 equal installments
    Non-refundable application fee: USD 50

Curriculum & Faculty

syllabus

  • Python Basics
  • Intermediate Python
  • Relational Databases
  • SQL
  • Data Extraction (Analytics in Python 3.1 to 3.7 getting data from the internet)
  • Data Cleaning (Analytics in Python 3.1 to 3.7 Cleaning with Pandas)
  • Statistics & Exploratory Data Analysis
  • Sampling
  • Hypothesis Testing
  • Data Analysis & Visualization (numpy)
  • Data Analysis & Visualization (pandas)
  • Linear Regression
  • Logistics Regression, Step-wise Regression, Non-Linear Regression
  • Classification
  • Dimensionality Reduction
  • Naïve Bayes
  • K-Means
  • Text Mining
  • Clustering
  • Decision Trees
  • Time Series Analysis
  • Linear Optimization

Industry Examples

Data Exploration using Lending Club Loan Data

Data Exploration using Lending Club Loan Data

Data Management Using Northwinds Traders Data

Data Management Using Northwinds Traders Data

Data Wrangling using CNC Mill Tool Wear Data

Data Wrangling using CNC Mill Tool Wear Data

Hypothesis Testing using Cancer Atlas Data

Hypothesis Testing using Cancer Atlas Data

Natural Language Processing (NLP) implementation using Amazon product reviews

Natural Language Processing (NLP) implementation using Amazon product reviews

Faculty

Hardeep Johar
Hardeep Johar

Senior Lecturer Of Industrial Engineering And Operations Research

Vineet Goyal
Vineet Goyal

Associate Professor Industrial Engineering And Operations Research

Course Leaders

*Course Leaders are subject to change

Kristen Kehrer

Course Leader, Emeritus

Phil Capobres

Course Leader, Emeritus

Industry Leaders

In addition to Course Leaders, industry experts focusing on data science share their knowledge and experience through periodic guest lectures.

Learning Experience

Benefits to the Learner

Enhance Your Career capital

  • Professional acceleration through our enriched leadership toolkit.
  • Learn while you earn.
  • Get noticed. Get ahead.
  • Understand how to manage your career & personal brand.

Enhance Your Social Capital

  • Make new, life-long connections with experienced business people from a wide variety of cultures, industries, and backgrounds.
  • Inclusion in the Emeritus Network
  • Invitation to Emeritus alumni events globally including career panels, CXO speaker series, and industry interactions.

Manage Your Brand Capital

  • A Global Business Education on your resume
  • Top 10 percent of the class achieves the status of Emeritus Scholars determined by the overall diploma GPA

Deepen Your Intellectual Capital

  • World class curriculum and teaching by faculty from Columbia Engineering Executive Education.
  • Peer-to-peer learning through learning circles, classroom discussions, and project reviews.
  • Selective entrance criterion ensures you learn with the best.

CERTIFICATE

Certificate Click to view certificate

ADMISSION & FEES

Application Requirements

  • Minimum three years of professional work experience
  • Employment history (CV/resume)
  • University transcripts
  • All candidates who have received their bachelor’s or other degree or diploma from an education institution where English is NOT the primary language of instruction are required to demonstrate English language proficiency through ANY ONE of the following methods
    – Obtain a TOEFL minimum score of 550 for the paper based test or its equivalent
    – Obtain an IELTS minimum score of 6.0 Obtain a Pearson Versant Test minimum score of 59
    – Obtain a Certificate of Completion for a Certificate course offered by the Emeritus Institute of Management
    – Submit a document which shows that the candidate has, for the last 24 months or more, worked in ANY ONE of these countries: Antigua and Barbuda, Australia, The Bahamas, Barbados, Belize, Canada, Dominica, Grenada, Guyana, India, Ireland, Jamaica, New Zealand, Singapore, South Africa, St Kitts and Nevis, St Lucia, St Vincent and the Grenadines, Trinidad and Tobago, United Kingdom, United States of America
  • A completed Application Form
  • Proof of diploma/degree in any field of study (your highest qualification should be submitted)

DIPLOMA FEE

USD 3000 Payable in 2 equal installments

NON-REFUNDABLE APPLICATION FEE

USD 50

DIPLOMA COMMENCES

TBD

APPLICATION DEADLINE

TBD

COURSE FAQs

We have listed two type of FAQs:

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

COURSE SPECIFIC FAQs

With respect to the growth and demand for data scientists, insights collected by Glassdoor and

Forbes predict that there will be a 28 percent increase in the demand for data scientists by 2020, with an average salary of over US $100,000. Data scientist has been ranked as the best job in the USA on Glassdoor consecutively for the last three years. Data science is an interdisciplinary field. Data scientists need to be curious and results-oriented, with exceptional industry-specific knowledge and communication skills that allow them to explain highly technical results to key stakeholders to drive strategic decision making in the organization.
We are unable to comment about the specific details of courses from other providers. We would encourage you to list the things you are looking for in a course and then compare our course with other providers’ courses. We have listed some of the parameters our learners have found relevant:
Attributes Emeritus Benefit
Type SPOC (Small Private Online Course) — typically cohorts of 150 people with individualized attention
Delivery Fixed start and end dates
Duration Nine months
Support
  • Dedicated support for academic and non-academic queries.
  • Follow-up to nudge you along to completion.
  • Discussion board to debate and learn with the cohort
Content
  • 20 application projects
  • 1 capstone project
  • 20 discussions
  • 10 live classes
Grading All quizzes and assignments are graded
Learning Outcome
  • Refresher data management tools such as Python, relational databases, and data extraction and cleaning tools
  • Exploratory data analysis techniques such as statistical distributions, sampling, hypothesis testing, and data visualization using numpy and pandas
  • Regression techniques such as linear, logistic, step-wise, and non-linear regression
  • Classification techniques, such as dimensionality reduction, Naïve Bayes, and K-means
  • Text mining, clustering, decision trees, time series analysis, and linear optimization
Faculty Vineet Goyal: Professor Vineet Goyal has a Bachelor’s degree in Computer Science from Indian Institute of Technology, Delhi and a PhD from Carnegie Mellon University. Before coming to Columbia, he spent two years as a postdoctoral associate at the Operations Research Center at MIT.
Hardeep Johar: Hardeep Johar received an MA in Economics from the Birla Institute of Technology and Science and is a Fellow of the Indian Institute of Management Calcutta. He received a PhD in Information Systems from NYU Stern School of Business. Prior to joining Columbia, Johar has worked as a quantitative trader at Morgan Stanley, Credit Suisse, and Deutsche Bank, at a tech startup (MSpoke), and has taught at NYU Stern School of Business and the Gabelli School of Business at Fordham University.
Course Fee USD $3,000
Credential Postgraduate Diploma in Applied Data Science from Emeritus and Columbia Engineering
After you complete your Postgraduate Diploma in Applied Data Science, you can take any one of the following courses: Applied Machine Learning: This course teaches you the essential statistical tools and methods and computer algorithms that can help you create models that can analyze vast amount of data to predict outcomes that can be immensely useful for your personal and business ventures alike. By working on real-life application projects, you also acquire the knowledge of how different algorithms are used in different kinds of industry scenarios. Applied Artificial Intelligence: This course teaches you 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, and deciding the best logical course of action to achieve its goal.
The concepts and models taught in the diploma covers both B2C and B2B business models. The application projects such as housing price prediction, human activity recognition, and credit card fraud detection are some of the B2B business models. We urge you to participate in the discussions, contextualize the topic under discussion, and ask pointed questions to understand why and how a tool or an algorithm will apply in a B2B context.
Yes, all the concepts are relevant to businesses of all sizes. We use examples of large companies since these are easy for everyone to relate to. However, the frameworks and concepts are applicable to smaller businesses, too. Keep in mind that large companies were also small companies once, who grew owing to their successful strategies. We urge you to participate in the discussions, contextualize the topic under discussion, and ask more pointed questions to understand why and how a framework or strategy will apply in a smaller company.
Yes, the frameworks and concepts we teach are not specific to an industry or business. Each application project is just one way of using a specific algorithm or tool. As numerous examples illustrate, data science concepts find their application in various other domains as well. We urge you to participate in the discussions, contextualize the topic under discussion, and ask more pointed questions to understand why and how a framework or strategy will apply in a specific industry.
Generally, professionals in the following roles are most likely to derive the maximum benefit from the course:
  • CXO/Chief Data Officer
  • Product/Project Manager
  • Data Engineer
  • Data Scientist
  • Software Engineer
  • Data Analyst
  • Consultant
  • Business Analyst
  • Statistician
  • Database Engineer