Teaching

Data Science for Business

    Course Number: GSBA 524 
    Required Units: 3.0
    Level: Master's
    Contents: Statistics and Advanced Analytics, AI programming pair for R;

A career in business involves making numerous decisions such as whether to launch a new product, acquire a piece of property, enter new markets, expand production capacity, etc. Most of these decisions are made in an environment characterized by uncertainty and decision alternatives with complex tradeoffs. Often, information is available or can be obtained at a cost that can be used effectively to make better decisions. The main objective of this course is to teach you a set of foundational tools and illustrate their applications. These tools will be useful in general decision-making situations as well as other courses where you make financial, marketing and operational decisions.

Regression & Generalized Linear Models for Business Applications

    Course Number: Graduate School of Business Administration (GSBA) 604
    Required Units: 3.0
    Level: Phd 
    Comments: Master's students with quantitative backgrounds and interests can also enroll
    Contents: High-dimensional Methods, Predictive Modeling, Hierarchical Models
    Applications: Marketing, Economics, Finance, Healthcare Analytics, Management Sciences

Fall 2018 class materials can be accessed at: Click Here. This class will involve coding in the popular statistical “R”. Accompanying R-Labs for the statistical methods taught in class will provided. This year I plan to incorporate some Bayesian large scale modeling approaches.

Applied Business Statistics

    Course Number: Business Administration (BUAD) 310g
    Required Units: 4.0
    Level: Undergraduate
    Contents: Introductory Statistics; Business Analytics; Data Analysis Labs;

Class notes and lecture slides can be accessed at blackboard – USC’s e-learning platform. Please look at the class syllabus and blackboard announcements for all other information. If you feel the need to email me regarding the class, please use the email address mentioned in the syllabus in blackboard. Please note that the email address for this class is different from my USC or Marshall email. This is a compulsory core class for all USC Marshall undergraduates. Class participation and attendance is mandatory.

Introduction to Business Analytics

    Course Number: Business Administration (BUAD) 425
    Required Units: 2.0
    Level: Undergraduate

Leveraging large corporate datasets; slice and dice data; dash boards; data mining and statistical tools; neural network; multiple and logistic regression; decision tree; gain inference and decision making; clustering.

Teaching

Data Science for Business

    Course Number: GSBA 524 
    Required Units: 3.0
    Level: Master's
    Contents: Statistics and Advanced Analytics, AI programming pair for R;

A career in business involves making numerous decisions such as whether to launch a new product, acquire a piece of property, enter new markets, expand production capacity, etc. Most of these decisions are made in an environment characterized by uncertainty and decision alternatives with complex tradeoffs. Often, information is available or can be obtained at a cost that can be used effectively to make better decisions. The main objective of this course is to teach you a set of foundational tools and illustrate their applications. These tools will be useful in general decision-making situations as well as other courses where you make financial, marketing and operational decisions.

Regression & Generalized Linear Models for Business Applications

    Course Number: Graduate School of Business Administration (GSBA) 604
    Required Units: 3.0
    Level: Phd 
    Comments: Master's students with quantitative backgrounds and interests can also enroll
    Contents: High-dimensional Methods, Predictive Modeling, Hierarchical Models
    Applications: Marketing, Economics, Finance, Healthcare Analytics, Management Sciences

Fall 2018 class materials can be accessed at: Click Here. This class will involve coding in the popular statistical “R”. Accompanying R-Labs for the statistical methods taught in class will provided. This year I plan to incorporate some Bayesian large scale modeling approaches.

Applied Business Statistics

    Course Number: Business Administration (BUAD) 310g
    Required Units: 4.0
    Level: Undergraduate
    Contents: Introductory Statistics; Business Analytics; Data Analysis Labs;

Class notes and lecture slides can be accessed at blackboard – USC’s e-learning platform. Please look at the class syllabus and blackboard announcements for all other information. If you feel the need to email me regarding the class, please use the email address mentioned in the syllabus in blackboard. Please note that the email address for this class is different from my USC or Marshall email. This is a compulsory core class for all USC Marshall undergraduates. Class participation and attendance is mandatory.

Introduction to Business Analytics

    Course Number: Business Administration (BUAD) 425
    Required Units: 2.0
    Level: Undergraduate

Leveraging large corporate datasets; slice and dice data; dash boards; data mining and statistical tools; neural network; multiple and logistic regression; decision tree; gain inference and decision making; clustering.