Spring 2025 Decision, Risk & Operations Management B8103 section 002

Business Analytics II: Foundations of AI

Business Analytics II: AI

Call Number 16560
Day & Time
Location
T 9:00am-12:15pm
To be announced
Points 1.5
Grading Mode Standard
Approvals Required None
Instructor Hongseok Namkoong
Type LECTURE
Method of Instruction In-Person
Course Description

Business analytics refers to the ways in which enterprises such as businesses, non-profits, and governments use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. Modern data collection methods – arising in bioinformatics, mobile platforms, and previously unanalyzable data like text and images – are leading an explosive growth in the volume of data available for decision making. The ability to use data effectively to drive rapid, precise, and profitable decisions has been a critical strategic advantage for companies as diverse as Walmart, Google, Capital One, and Disney. Many startups are based on the application of AI & analytics to large databases. With the increasing availability of broad and deep sources of information – so-called “Big Data” – business analytics are becoming an even more critical capability for enterprises of all types and all sizes. AI is beginning to impact every dimension of business and society. In many industries, you will need to be literate in AI to be a successful business leader. The Business Analytics sequence is designed to prepare you to play an active role in shaping the future of AI and business. You will develop a critical understanding of modern analytics methodology, studying its foundations, potential applications, and – perhaps most importantly – limitations.

Web Site Vergil
Department Decision, Risk and Operations
Enrollment 75 students (74 max) as of 12:06PM Tuesday, December 3, 2024
Status Full
Subject Decision, Risk & Operations Management
Number B8103
Section 002
Division School of Business
Open To Business, Engineering:Graduate, Journalism
Section key 20251DROM8103B002