Graduate-Level Courses in Information Systems and Analytics (MSIS / OMIS)

Professors Emeriti: Steven Nahmias, Stephen A. Smith

Professors: Narendra Agrawal (Benjamin and Mae Swig Professor), Gangshu Cai (Department Co-Chair), Manoochehr Ghiassi, S. Andrew Starbird, Andy A. Tsay

Associate Professors: Ram Bala, Tao Li, Haibing Lu (Department Co-Chair), David K. Zimbra, Sami Najafi-Asadolahi, Michele Samorani

Assistant Professors: Hussein El Hajj, Jingbo Hou, Wilson W. Lin, Yu-Wei Lin, Amber Xiaoyan Liu, Mohammad Amin Morid, Simrita Singh, Xiang (Shawn) Wan, Yaqiong Wang, Ying (Maggie) Zhang

Lecturers: Thunyarat (Bam) Amornpetchkul, Homi Fatemi, Rick Schaffzin, Sumana Sur, Xuan Tan, Xiaochen Zhu

MSIS & OMIS Courses Offered by the ISA Department

MSIS 2402/2502. Math for Business & Analytics with R

The objective of this course is to provide a comprehensive background in the

mathematical topics required for learning Quantitative Finance (QF) and Business Analytics and Data Science (BADS). The mathematical topics covered include Calculus, Linear Algebra, and Probability Theory. Applications of these topics in a variety of business contexts will be included. (4 units)

Prerequisites None.

MSIS 2403/2503/2603 or OMIS 3366. Database Management Systems- Fundamentals of SQL

This course aims to give an understanding of hands-on experience with the most widely used database tools. The objective of this course is to convey intermediate to advanced database concepts and to acquaint students with state-of-the-art software tools. The course will rely on classroom discussions, media articles and cases, as well as programming exercises and an integrative group project. Use of database software is required. A lab fee is required. Introduces database management and database management systems (DBMS). Teaches technical and managerial skills in database planning, analysis, logical design, physical design, implementation, and maintenance. Features hands-on training in database design, development, and implementation using relational DBMS software. Emphasizes designing and developing reliable databases to support organizational management. (2 units)

MS Prerequisite: Experience with computer usage. MBA Prerequisite: OMIS 3000.

MSIS 2407/2507/2607 or IDIS 3802. Data Analytics- Python 

Data analytics involves the application of scientific methodologies to extract, understand, and make predictions based on data sets from a broad range of sources. Data analytics requires knowledge and skills from three areas: (i) programming, (ii) math/statistics, and (iii) domain specific expertise. The objective of this course is to teach the programming skills relevant to data science. Students will learn to use a complete set of open source tools for data science in Python, including the Jupyter Notebook, NumPy, Pandas, Seaborn, scikit-learn, Colab, and many others. Students will learn skills that cover the various phases of exploratory data analysis: importing data, cleaning and transforming data, algorithmic thinking, grouping, aggregation, reshaping, visualization, time series, statistical modeling, and data exploration and communication of results. The course will utilize data from a wide range of sources and will culminate with a final project and presentation. (4 units)

Prerequisite: None.

MSIS 2427/2527/2627. Big Data Modeling and Analytics

Learn to analyze a massive amount of data with distributed computations using Spark's high-level data transformations. This class will teach scalable approaches to process large amounts of text with MapReduce, Spark, and Amazon Athena (an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL) (4 units)

Prerequisites: MSIS 2x07 & 2x03.

MSIS 2429/2529/2629. Dashboards, Scorecards, and Visualization

This course enables you to transform data into persuasive dashboards that effectively inform and guide management actions. Dashboards are persuasive if they motivate actions in an intended audience. Dashboards are effective if they offer comprehensive and reliable information. This course introduces and discusses the fundamental design principles and technology of dashboards and allows you to design, implement, and critique dashboards. (2 units)

Prerequisites: None.

MSIS 2431/2531/2631. Machine Learning w/Finance

The course will prepare participants for more rigorous analysis of large data sets as well as introduce machine learning models and data analytics for business intelligence. The course will be a rigorous and broad treatment of AI, machine learning, and deep learning. The course will use both R and Python programming languages to undertake hands-on learning in ML. (4 units)

Prerequisite: MSIS 2x07.

MSIS 2459. Financial Markets & Institutions

This course analyzes the main functions of financial institutions such as commercial banks, investment banks and insurance companies from the perspective of a corporate issuer, and reviews the recent developments in the financial service industry. (2 units)

Prerequisite: None.

MSIS 2510. Prescriptive Analytics 

This course helps participants understand the principles of optimization in business

decisions and prepare computer based models from problem descriptions and determine optimal solutions using software tools. This course also prepares participants to interpret solutions to obtain insights regarding sensitivity to inputs, resource constraints, and their profitability impacts. (4 units)

Prerequisite: None.

MSIS 2413/2513/2613. Database Analysis, Design and Management

Course presents technical and managerial approaches to the analysis, design, and management of business data, databases, and database management systems. The topics include structured and unstructured data management, a comparison of relational and object-oriented databases, relational database conceptual and logical design, and database implementation and administration (2 units)

Prerequisite: None.

MSIS 2601. Object Oriented Analysis and Programming

Provide students with an overview of object-oriented programming methodology using the Java Programming Language. Course will present different programming paradigms, including structured (procedural) and object oriented, compare and contrast these approaches, object oriented programming concepts including data abstraction, abstract data types, classes and objects, inheritance, polymorphism, encapsulation, packages and interfaces, and multithreaded programming. To support GUI-based Java applications, concepts and tools such as event handling, Generics programming, Swing, and JavaFX, (libraries and classes introduced in JDK 8 and beyond) windowing systems and frameworks are introduced to support modern lightweight development of Java-based Applets. (4 units)

Prerequisite: Knowledge of C programming language or equivalent.

MSIS 2602 or OMIS 3372.  Information Systems Analysis and Design- Systems Modeling 

Methodology to assist in the analysis and design of computer-based information systems for business applications. Tools include data flow diagrams, flowcharts, Structured English, pseudo code, hierarchy charts, structure diagrams, and Warnier-Orr charts. Application of these tools to a systems development project is required.  Cross-listed with OMIS 372. Credit will not be given for both. (4 units)

MS Prerequisite: None. MBA Prerequisites: OMIS 3000

MSIS 2604 or OMIS 3378. Information Systems Policy and Strategy

Strategic management and deployment of information systems and technologies (ISTs) to improve business competitiveness. An examination of the role of IST strategy in enabling companies to effectively manage in the turbulent and dynamic business environment brought about by the Internet. Analysis of new business opportunities in electronic commerce brought about by ISTs, including organizational redesign that these technologies require. An examination of implementation and change management issues related to IST deployment in the new environment. Focuses on drawing lessons from the experiences of leading companies that are deploying ISTs to define and support their e-commerce strategies. (4 units)

MS Prerequisite: None. MBA Prerequisite: OMIS 3000.

MSIS 2606 or OMIS 3368 Software Project Management

An overview of software project development methodology, covering both technical and managerial aspects of software development. Examines alternate software life cycle models and introduces modern techniques for definition, design, implementation, and validation of software products. Prerequisite: Knowledge of or experience with a high-level programming language, or permission from an instructor. (4 units)

Prerequisite: MSIS 2601 & MSIS 2602. MBA Prerequisite: MSIS 2601 & OMIS 3372

MSIS 2621 or OMIS 3368 Business Intelligence and Data Warehousing

Introduces the business, technology, and managerial issues related to BI and DW solutions. Students will acquire practical skills in collecting business requirements, planning, defining, designing and developing a BI solution. Emphasis is placed on learning how to derive business value from BI and DW solutions. Hands-on experience will be obtained using a variety of BI tools. (4 units)

MS Prerequisite: MSIS 2603 & Mx07. MBA Prerequisite: OMIS 3366

MSIS 2622. Enterprise Systems and Analytics

Enterprise systems are data troves that can be used to improve business performance. Enterprise systems offer historic data that can be used to optimize business processes or uncover fraudulent activities. Gives students an understanding of enterprise system fundamentals, design options for business processes, and enterprise systems data. (4 units)

Prerequisite: None.

MSIS 2428/2528/2628. Applied Cloud Computing

Computing is migrating to the cloud. In this course, you will understand as-a-service concepts by using services from major cloud providers and learn how to d#eploy and manage cloud infrastructure. This course focuses on hands-on skills required to operate on the three prime cloud service platforms from Amazon, Google, and Microsoft. This course will offer an applied perspective on the core features of these platforms such as load balance, auto-scaling, serverless computing, and cloud AI. (2 units)

Prerequisite: None.

MSIS 2630. Web Programming

The course will focus on the design and development of web based applications using a number of currently popular tools and strategies; also to be explored is the use of databases as data repositories for web applications. Core technologies including HTML, CSS, JavaScript, PHP, and MySQL will be emphasized. (2 units)

Prerequisite: None.

MSIS 2508. Machine Learning with Python

This course introduces participants to quantitative techniques and algorithms that are based on big and small data (numerical and textual). We also analyze theoretical models of big systems for prediction and optimization that are currently being used widely in business. It introduces topics that are often qualitative but that are now amenable to quantitative treatment. The course will prepare participants for more rigorous analysis of large data sets as well as introduce machine learning models and data analytics for business intelligence. (4 units)

Prerequisite: Mx07.

MSIS 2534/2634. Natural Language Processing

This course teaches students the fundamentals of Natural Language Processing (NLP). NLP has recently found several applications in business. There is now a foundation of content that students who wish to work in this field need to know and this course is aimed at providing students with a conceptual understanding of the field and its business applications, and a technical toolkit to implement NLP models. (4 units)

Prerequisite: Mx07.

MSIS 2536/2636. Deep Learning

Introduction to the topic of Deep Learning Neural Networks (DLNs), Linear Learning models using Logistic Regression, and adding hidden layers to create Deep Feed Forward Neural Networks. Detailed algorithms are used to train these networks using Stochastic Gradient Descent and the resulting algorithm called Backprop. Training processes of these networks are used with Tensor Flow tool and the MNIST and CIFAR-10 image data-sets. Some specialized DLN architectures including the following: (a) Convolutional Neural Networks (ConvNets), (b) Recurrent Neural Networks (RNNs), (c) Reinforcement Learning. Model parameter initialization, underfitting and overfitting are discussed as well as techniques such as Regularization. Issues such as the Vanishing Gradient problem that often cause problems during training are also discussed. (4 units)

Prerequisite: None.

MSIS 2537/2637. Reinforcement Learning

The objective of this course is to provide an in-depth introduction to the topic of Reinforcement Learning (RL) algorithms. These algorithms are based on the theory of Dynamic Programming and Markov Decision Processes, which originated more than fifty years ago. (2 units)

Prerequisite: None.

MSIS 2538/2638. Cloud Computing Architectures

Technologies make Cloud Computing possible and how IT leverages these technologies to make the enterprise computing environment more efficient. Students will learn how hardware virtualization is made possible through computer architecture advancement, hypervisor-based virtualization and container-based virtualization, and microservices. (4 units)

Prerequisite: None.

MSIS 2439/2539/2639. Data Visualization

Transform data into persuasive dashboards that effectively inform and guide management actions. Dashboards are persuasive if they motivate actions in an intended audience. Dashboards are effective if they offer comprehensive and reliable information. Introduces and discusses the fundamental design principles and technology of dashboards and allows you to design, implement, and critique dashboards. (2 units)

Prerequisite: 2x29.

MSIS 2641. Information Technology: Ethics and Public Policy

This course examines the intersection of law and commerce as it relates to technology companies such as those based in Silicon Valley. Students will learn to understand how to operate in this environment and the typical issues that arise in this environment as they relate to contracts, securities, intellectual property, privacy, and employment. (2 units)

Prerequisite: None.

MSIS 2650/OMIS 3374. Artificial Intelligence

The course begins by describing what the latest generation of artificial intelligence techniques can actually do. After an introduction of some basic concepts and techniques, the course illustrates both the potential and current limitations of these techniques with examples from a variety of applications. We spend some time on understanding the strengths and weaknesses of human decision-making and learning, specifically in combination with AI systems. Exercises will include hands-on application of basic AI techniques as well as selection of appropriate technologies for a given problem and anticipation of design implications. In a final project, groups of students will participate in the creation of an AI-based application. (4 units)

Prerequisite: MSIS 2607. Prior knowledge on statistics and programming are required.

MSIS 2688/OMIS 3388 : Supply Chain Technology

This course considers the framing of business problems from an enterprise resource planning (ERP) perspective. In addition, it considers the utility and selection of ERP, logistics, warehousing, and emerging supply technologies. At the end of this course students will be able to: analyze supply chain business problems from an ERP perspective, assess ERP and best of breed technologies for integrated business processes. and evaluate the utility of and select logistics, warehousing, cloud-based planning and online marketplaces. (2 units)

Prerequisite: None.

MSIS 2692: Data Structures and Algorithms

The course aims to equip students with the knowledge and hands-on experience to develop efficient algorithms that

solve complex computational tasks that arise in different domains, such as optimal matching or vehicle routing. Students will learn the data structures needed for various computational tasks, such as lists, hash tables, double-ended-queues, priority queues or heaps, and disjoint-sets. Topics covered include sorting algorithms, graph algorithms, and algorithm design strategies, such as iteration, recursion, divide-and-conquer, depth-first search, and breadth-first search. Students will be able to analyze the complexity of an algorithm, select the most appropriate data structure to solve a given problem, and develop algorithms that are as efficient as possible. Students are expected to have prior programming experience.

Prerequisite: Mx07.

MSIS 2801. Mobile Payment and eCommerce Security

This course reviews the advancements in mobile payments, crypto-currency and on-line transaction security and will prepare you to engage in platform and application development for this emerging new market. You will learn the fundamentals of secure chip-cards processing as mandated by Europay, MasterCard and Visa (EMV). Various mobile payment technologies will be discussed in detail with a special focus on the pros and cons of Near Field Communication (NFC), secure element, Host Card Emulation (HCE), Bluetooth, QR codes, tokens and eWallets. The course covers online transaction security risks such as Heartbleed, and fraud prevention methods including multi-level authentication, biometrics, cloud-based security and Fast Identification Online (FIDO). The course concludes with a discussion on the role of crypto-currency and future trends. (2 units)

Prerequisite: None.

MSIS 2803. Internet of Things

This course introduces students to the principles underlying the Internet of Things (IoT). It starts with the history of various technologies that have enabled IoT. It will cover types of IoT architectures, sensor technologies, hardware platforms, communication protocols at various IoT stacks, machine-to- machine communication, IPv6-based solutions, the IEEE 802.15.4 standard that governs and defines IoT protocols, the IoT cloud infrastructure, and security and remote management of IoT devices. This course will also provide students with the application skills necessary to cement the IoT principles learned. Students who would like to take on leadership or managerial roles will find the principles learned in this course very helpful in implementing a unique and effective IoT-based business strategy for their organization. Students will be required to work in teams to design and build working IoT systems. (2 units)

Prerequisite: None.

MSIS 2804. Mobile App Development for Business Applications

Mobile platforms and apps have become core components of business today. With over 2.5 million apps available for smartphones, understanding the basic concepts underlying mobile apps has become a core necessity for business practitioners - particularly for executives and entrepreneurs. Business professionals now need to obtain in-depth knowledge of what is inside a mobile app, how one gets built, and where the business value resides. The best and most practical way for these professionals to develop this knowledge is for them to actually build a set of mobile apps, hands-on from the ground up. This course presents the business and technical foundation for mobile platforms and app development. (2 units)

Prerequisite: None.

MSIS 2651. Mobile Programming

Mobile platforms and apps have become core components of business today. With over 2.5 million apps available for smartphones, understanding the basic concepts underlying mobile apps has become a core necessity for business practitioners – particularly for executives and entrepreneurs. Business professionals now need to obtain in-depth knowledge of what is inside a mobile app, how one gets built, and where the business value resides. The best and most practical way for these professionals to develop this knowledge is for them to actually build a set of mobile apps, hands-on from the ground up. This course presents the business and technical foundation for mobile platforms and app development. (2 units)

Prerequisite: None.

MSIS 2805 or OMIS 3807. How Engineers, Business people and Lawyers Communicate With Each Other

Students from business, engineering, and law learn to understand each other's perspectives, speak each other's language, and work together effectively in a collaborative environment. Students from different schools will be organized into teams to work together on a simulated project involving a technological matter, such as privacy/security or IP. (2 units)

Prerequisite: None.

MSIS (2440/2441) or (2540/2541) or (2640/2642). Industry Practicum

Experiential Learning project for M.S. involving external industry partners. (4 units for MSFA; 6 units for MSBA/MSIS)

MSIS 2445 or (2545/2543) or (2645/2646). Design Capstone

Experiential Learning project for M.S. involving internal partners. (4 units for MSFA; 6 units for MSBA/MSIS)

MSIS 2684 or OMIS 3384. Supply Chain Management

Focuses on the key challenges and issues relating to design, analysis, and management of supply chains to gain competitive advantage. The goal of the course is to assess supply chain performance and improve execution by effectively managing inventory, capacity, logistics and supply chain relationships. Additional topics include the role of information technology in this context, supply chain network design, and managing supply chains in environments with product innovation and proliferation. (4 units)

MS Prerequisites: None. MBA Prerequisite: OMIS 3252.

OMIS 3000. Business Analytics

Business Analytics is the scientific analysis of data to make better business decisions. Students in this course will learn to use analytics platforms across a wide variety of applications such as marketing, finance, and 2508agement. They will become familiar with current technological environments for statistical/machine learning and visualization. (4 units)

Prerequisite: OMIS 3200 and OMIS 3202 for MBA Students.

OMIS 3200. Quantitative Methods

Introduction probability and statistical analysis, emphasizing applications to managerial decision problems. Discusses descriptive statistics, probability theory, sampling distributions, statistical estimation, hypothesis testing, and simple and multiple regressions. Additional topics may include exploratory data analysis, analysis of variance, and contingency tables. (2 units)

Prerequisites: None.

OMIS 3052. Analytics-driven Organizational Transformation

This course introduces key business functions and studies how analytics is used in those business functions. Various business applications across different functional areas and industry verticals will be analyzed using real and simulated data to get a deeper understanding of analytics principles. The objective of the course is to provide the right level of exposure to the day-to-day life of an analytics professional. Examples of business functions that will be studied are sales and marketing, finance, supply chain, HR, and finance. (2 units)

Prerequisites: OMIS 3000

OMIS 3202. Analytical Decision Making

This course covers how to rigorously formulate decision problems, understand mathematical optimization, deal with the uncertainties inherent in real business problems, while introducing computer modeling tools like important Excel add-ons, R, Mathematica, CrystalBall, and @Risk. (2 units)

Prerequisites: OMIS 3200.

OMIS 3250. Analysis, Design, and Management of Enterprise Platforms

Introduces the information technology infrastructures that enable within and across firm operations, and the competitive advantages that information technology can offer various firms. Focuses on how firms effectively utilize information technology resources in their business models and operations. (2 units)

Prerequisites: OMIS 3200.

OMIS 3252. Operations Management

This course introduces how firms get the right products and services to the right people, in the right place, at the right time and cost. In addition to firms that provide physical goods, this course covers information-enabled, supply-demand matching networks like Uber and AirBnB that vastly reduce cost and increase convenience in operationally intensive industries.. (2 units)

Prerequisites: OMIS 3202.

OMIS 3385. Supply Chain Analytics

This course will introduce students to a selection of important problems from all key areas of SCM-Plan, Source, Make and Distribute. Through real world case studies, students will learn about the broader business context within these problems. They will learn how to apply appropriate descriptive and prescriptive techniques to solve these SC problems, and the use of cloud based technology platforms to store, access, visualize and analyze data to make and communicate effective decisions. (2 units)

Prerequisites: OMIS 3000.

MSIS 2687 or OMIS 3387. Global Supply Chain Management

Global supply chains are the vitally important dynamic networks that connect people, information, processes and resources across the world involved in the production and services to customers. This course explores global supply chain relationships, transactions, channels and logistics infrastructure. Trends and challenges with respect to analytics, politics, economics and sustainability concerns in global supply chains are discussed. (2 units).

Prerequisite: OMIS 3000

OMIS 3390. New Product Development

Introduces students to the methods companies use to develop and release new products. New product development is a challenging, rewarding activity that can make the difference between success or failure for a company, especially in technology-based industries. The traditional view that new product development is an “art” practiced by engineers has now given way to an understanding that it is a discipline that must be learned and practiced to be successful. Examines the sequence of activities needed to successfully develop and launch a new product or service; understand how the different functions and roles in product development interrelate and work together; learn how to balance strategic and tactical activities in successful product development; develop a better understanding of how to determine and satisfy customer needs; understand the financial aspects of product development; develop the skills to analyze and improve product development efforts within a company. (4 units)

Prerequisites: OMIS 3000

OMIS 3391. Accelerating Innovation

This course introduces how contemporary organizations procure innovation ingredients (technology, IP, new business models), from outside the company, through deal-making, to fill gaps and get faster time-to-market. It also covers a 3-box framework, to recognize and manage inherent operational conflicts encountered, as companies innovate new business models, while maintaining current ones. Students lean practical deal-making skills to drive innovation, such as analyzing what external resource(s) (including IP) a firm wants for achieving its strategic intent, finding and selecting who to partner with, structuring and negotiating business contracts, and managing the deal to extract potential synergies. Student teams also study business development activities of a company. (4 units)

Prerequisites: OMIS 3000

OMIS 3392. Econometrics for Business Analytics with R

This is a 4-unit course designed in two parts. The 3 unit lecture session introduces a broad set of econometric tools to analyze large-scale real-world company data to make data-driven business decisions. The 1-unit lab session features hands-on training in practical data analytics skills using the powerful statistical software environment R. Topics include the Ordinary Least Squares (OLS), model selection, Generalized Least Squares (GLS), instrumental-variables regression, quantile regression, count data models, binary outcome models, and selection models. Cross listed with FNCE 2409 and ECON 2509. (4 units)

Prerequisites: ECON 3000 for MBA Students.

OMIS 3808. Supply Chain Finance

This course connects firms' supply chain management decisions to their financial decisions.  The objective of this course is to interpret how financial performances are affected by supply chain decisions, understand different supply chain finance mechanisms, study risk management in the presence of supply chain finance, and describe new technologies related with supply chain finance. (2 units)

Prerequisites: OMIS 3000