MS in Business Analytics

MSBA Courses

Introduction to Probability and Statistics

Introduces tools for decision-making under uncertainty, ranging from the fundamentals of probability theory, decision theory, and statistical models to basic software for data analysis.

Skills acquired:

Statistical Independence, Conditional Probability, Bayes Theorem, Distributions, Expectation, Variance, Decision Trees, Sampling, Interval Estimation, Correlation, Simple Regression.

Programming in R and Python

An introduction to Python and R programming, focusing on data analytics applications. It addresses basic concepts and progresses to functions, program modularity, algorithms, and data structures.

Skills Acquired:

Python, R, Conditionals, Loops, Functions, Program Modularity, Algorithms, Data Structures.

Business Fundamentals

Offers a foundational overview of general business management, exploring organizational structure and the interplay between key business domains such as accounting, finance, operations, and marketing.

Skills Acquired:

Organizational Structure, Accounting, Finance, Operations, Marketing.

Statistical Foundations of Business Analytics

This course teaches data analysis and statistical inference for business decisions, focusing on probability, Bayesian modeling, multivariate analysis, and model-building with real-world data applications.

Skills Acquired:

Probability, Statistical Inference, Bayesian Modeling, Multivariate Analysis, Causal Inference, A/B Testing, Experimental Design, Diagnostics, Model-Building.

Modern Data Management

Focuses on managing and retrieving all data types, covering relational systems, database theory, Big Data models, and an introduction to Hadoop and Apache Spark from both technical and business perspectives.

Skills Acquired:

Data Management, Relational Databases, SQL, MySQL, SQLite, MongoDB.

Data Exploration and Visualization

Introduces data visualization principles and techniques, incorporating statistics, graphic design, and cognitive psychology to enhance understanding of complex data through effective visual representations.

Skills Acquired:

Data Visualization, Design Principles, Tableau, Excel, Dashboard Design, Web-Based Visualizations.

Machine Learning Fundamentals

Explores machine learning techniques for structured and unstructured business datasets, including linear regression, k-nearest neighbors, SVMs, principal components, and clustering methods.

Skills Acquired:

Linear Regression, K-Nearest Neighbors, SVMs, Unsupervised Learning, Principal Components, Clustering Methods.

Machine Learning for Business Applications

Continues machine learning techniques for business, focusing on model selection, nonlinear prediction, and latent variables modeling for practical business applications.

Skills Acquired:

Model Selection, Overfitting, Bias-Variance Tradeoffs, Ensemble Learning, Feature Selection, Regularization, Decision Trees, Regression Splines, Hidden Markov Models.

Optimization

This course develops optimization models for decision making, applying methodologies like linear programming and heuristics to strategic and operational business applications.

Skills Acquired:

Linear Programming, Integer Programming, Nonlinear Programming, Constraint Programming, Heuristics, Column Generation.

Business Value for Integrative Analytics

An integrative course detailing the path from analytical modeling to business value, covering descriptive, predictive, and prescriptive analytics phases for solving business problems.

Skills Acquired:

Analytical Modeling, Descriptive Analytics, Predictive Analytics, Prescriptive Analytics.

Managing Teams and Organizations

Covers organizational behavior from micro and macro perspectives, focusing on effective team work, organizational networks, and fostering an innovation culture.

Skills Acquired:

Team Building, Team Coordination, Organizational Networks, Innovation Culture.

Data Analytics in Finance

Addresses finance areas reliant on data analytics like high-frequency trading and asset management, employing statistics, machine learning, and NLP/text-mining tools.

Skills Acquired:

High Frequency Trading, Asset Management, Performance Analysis, Credit Analysis, Data Mining, NLP/Text-Mining.

Operations and Supply Chain Analytics

Focuses on analytics tools for strategic and operational decisions in manufacturing and service firms, aiming to maximize enterprise value through supply chain and operations management.

Skills Acquired:

Supply Chain Design, Demand Forecasting, Inventory Planning, Revenue Management, Healthcare Management.

Analytical Marketing

Emphasizes quantitative marketing strategies, applying data mining and machine learning to solve problems through case studies on pricing, customer churn, and direct marketing.

Skills Acquired:

Data Mining, Machine Learning, Pricing Decision Systems, Customer Churn Analysis, Direct Marketing.

Business Communication

Aims to enhance presentation and argumentation skills targeted at business audiences, focusing on delivering analytical insights for strategic decision-making.

Skills Acquired:

Presentation Skills, Argument Construction, Audience Analysis, Business Analytics Communication.

Ethics and AI

Explores ethical challenges and policies in AI use within businesses, aiming to develop responsible practices based on core principles like autonomy, fairness, and benefit.

Skills Acquired:

Ethics in AI, Corporate Responsibility, Policy Analysis, AI Governance Principles.

Experiential Learning

Provides hands-on business analytics experience through projects requiring data management, quantitative modeling, and presentations to company executives.

Skills Acquired:

Quantitative Modeling, Business Analytics Application, Large Language Models (LLMs), Collective Intelligence, Digital Twin.