Master of Science in Applied Analytics
offered by Columbia University

Private University
1 Campus
Estd. 1754

Master of Science in Applied Analytics
at
Columbia University
Overview

Gain a comprehensive overview of the analytics principles and concepts

Duration	24 months
Total fee	₹63.02 Lakh
Mode of learning	Online
Course Level	PG Degree

Master of Science in Applied Analytics
at
Columbia University
Highlights

Earn a master degree from Columbia University

Master of Science in Applied Analytics
at
Columbia University
Course details

Who should do this course?

For Individuals looking to enhance decision-making

What are the course deliverables?

Learn to recognize opportunities to impact an organization's strategic direction
Learn to source, store, and model the internal and external data
Learn to incorporate sophisticated data analytical techniques, approaches, and models
Develop the management and analytical skills necessary to implement change based on data-driven decisions

More about this course

This course prepares students with the practical data and leadership skills to succeed in the coming era
An innovative curriculum featuring both Management and Technical Cores that will equip you with the tools to analyze data, produce actionable information, and create an analytical culture within an organization
A well-rounded approach covering the required soft (leadership) and hard (technical) skills you will need to advance in your career

Master of Science in Applied Analytics
at
Columbia University
Curriculum

Term 1

Applied Analytics in the Organizational Context

Applied Analytics Frameworks and Methods I

Research Design

Storytelling with Data

Term 2

Strategy and Analytics

Applied Analytics Frameworks and Methods II

Managing Data

Elective

Term 3

Analytics and Leading Change

Capstone

Elective

Master of Science in Applied Analytics
at
Columbia University
Faculty details

David Madigan

David Madigan has worked for AT&T Inc., Soliloquy Inc., the University of Washington, Rutgers University, and SkillSoft, Inc. and has over 100 publications in such areas as Bayesian statistics, text mining, Monte Carlo methods, pharmacovigilance, and probabilistic graphical models.

Kitty Kay Chan

Dr. Kitty Kay Chan teaches machine learning and other data analytics methods. She specializes in data analytics for practical application in business operations, regulatory oversight, law enforcement, performance and damage valuation, strategic development, and policy assessment.

Vincent Agboto

Vincent Agboto is currently a Senior Scientist and Econometrician at Dobson DaVanzo & Associates where he leads methodological and data analytics work on Medicare data, health economics and payment systems. Previously, he has served as Senior Statistical Scientist at Allina Health,President and Principal Senior Statistical Consultant at Stats Solutions Consulting, and Director of Research at HealthPartners in Minneapolis, Minnesota.

Adam Askarian

Dr. Adam Askarian is a technology entrepreneur having experience in building startups in Silicon Valley and New York City, as well as leading data teams at fortune 500 companies. Currently, he is CTO and founding team member at Flowcode, a leading data, and technology platform for direct to consumer business.

Master of Science in Applied Analytics
at
Columbia University
Entry Requirements

Eligibility criteria Up Arrow Icon

Education: U.S. bachelor's degree or international equivalent
Prerequisite: Students must have advanced analytical writing skills and be comfortable with spoken English

Conditional Offer Up Arrow Icon