This course will cover the fundamentals of business rules and logic in a business application development context. Students will acquire these skills using computer programming. A modern programming language will be used to learn and reinforce logical concepts, including abstraction, process flow, variable assignment, and control structures, as well as proper programming and application development practices, including documentation.

MIS 28800 Programming For Business Applications

Programming For Business Applications

Arrange with instructor before enrolling. Investigation in a specific Management Information Systems field. Permission of instructor required.

MIS 29000 Personal Productivity With AI

Personal Productivity With AI

This course introduces students to the principles of technology governance and regulation through a global lens, preparing future managers -- at technology firms and at the many companies that increasingly depend on technology to do business -- to navigate the legal, ethical, and strategic landscape of operating across borders. Topics range from the social, ethical, and economic foundations of governance to the regulation of artificial intelligence, with substantial coverage of antitrust, privacy, cybersecurity, content moderation, national security, the environment, and intellectual property, depending on number of credit hours. Illustrative cases are drawn primarily from digital technology but extend into life sciences, agriculture, hard tech, and more. Students will compare how governments in the United States, the European Union, China, India, Brazil, and other major jurisdictions approach these challenges, and will examine the role of international organizations and standard-setting bodies. No prior background in law, economics, or technology is required.

MIS 35600 Global Technology Governance

Global Technology Governance

This case-oriented course is designed to familiarize students with existing and emerging technologies and their business applications. It also covers issues, problems, and opportunities that information systems (IS) executives and general managers face when managing IS resources in their organizations. Includes lectures, presentations, case analyses and discussions, and a World Wide Web project. Case discussions cover real situations and deal with the operational and strategic decisions that every IS manager has to make in managing and exploiting the available information technology.

MIS 38200 Management Information Systems

Management Information Systems

This course will cover the business rules and logic in a business application development context. These skills will be acquired using computer programming; specifically employing Python. Solution development will reinforce logical concepts process flow, variable assignment, and control structures, as well as proper programming and application development practices.

MIS 38800 Python For Business

Python For Business

Cloud computing and big data technologies are rapidly enhancing an organization's business intelligence ecosystem. Two modules of the course are specially designed for students to gain valuable hands-on experience in collecting, cleaning, formatting, integrating, and storing massive amounts of data that may be structured or unstructured, archived, or streaming in a cloud platform. The first module will introduce cloud computing fundamentals, its enabling technologies, main building blocks, and hands-on experience through projects utilizing Google Cloud Platform (GCP). The second module will cover processes for creating data pipelines in GCP so that the student will be able to curate big data for training, analysis, and prediction using AI/ML and other data science techniques.

MIS 46700 Big Data & Cloud Computing

Big Data & Cloud Computing

Most degree programs offer students an opportunity to apply the knowledge learned from their studies in an applicable area via a thesis, a research project, or capstone. This course provides such an opportunity and is designed specifically for Business Analytics & Information Management undergraduate students that will pursue analytical-type careers (e.g., Data/OR Analyst, Data Scientist, Decision Scientist, Consultant, Developer, etc.). This course is designed to polish and integrate the knowledge, skills, and abilities you have developed from your coursework by successfully developing an analytics solution with an industry partner in a structured fashion. Thus, most of your time will be devoted to working with your project teammates to provide the answers and deliverables specified by the partner over the course of many sprints. Every project team will be provided with a project description, data dictionary, and access to the dataset (or directions in where to find the necessary data), as well as an NDA to read, understand, sign, and return to your professor before you can gain access to the data. These are tasks that might be required of you to perform when you work on a new project or have a new client. Students are expected to be familiar with at least one programming language (e.g., Python, R). Permission of instructor required.

MIS 47800 Experiential Project In Analytics

Experiential Project In Analytics

This course is an introduction to the techniques and algorithms for creating effective data visualization. Visualizations are graphical depictions of data that can improve comprehension, communication, and decision making. This course emphasizes application in business settings where visual representation methods that are covered in this course will improve our understanding of complex data and models. We focus in particular on pattern identification, difference and trends in data sets across categories, space, and time. In addition to participating in in-class discussions, students will have sufficient hands-on experience with the tools and techniques covered in this course. Students will be expected to complete several short programming and data analysis assignments. Students will also have an opportunity to work as groups on a final project. Permission of department required.

MIS 47900 Data Visualization

Data Visualization

This course analyzes the changes in business models that have been enabled by Internet technologies, and exposes students to hands-on data analyses to quantify the impact these technologies and business models have on firms, economies, and people. A programming course such as MGMT 28800 Programming for Business Applications or MGMT 38800 Python for Business or CS 17600 Data Engineering in Python or CS 17700 Programming with Multimedia Objects or CNIT 17500 Visual Programming or CS 18000 Problem Solving & Object Oriented Programming and a statistics course such as STAT 30301 Probability & Statistics for Business or MGMT 30500 Business Statistics is highly recommended.

MIS 48800 Data-Driven Decisions In Digital Markets

Data-Driven Decisions In Digital Markets

Covers the theory and practice of database design and usage. Students will learn the importance of data modeling concepts and how to use these effectively and how to plan and design a database, including issues such as data security and control.

MIS 54400 Database Management Systems

Database Management Systems

Focuses on information systems development theories, practices, and tools for rapid adaptation and management of leading-edge as well as emerging computing paradigms. MGMT 54400 Database Management is highly recommended. Permission of department required.

MIS 54500 Systems Development

Systems Development

With the rise in big data, Machine Learning has experienced rapid growth over the last ten years with major advances in its subfields of Deep Learning, Reinforcement Learning, Natural Language Processing, Computer Vision, Robotics, and other subfields. The purpose of this course is to provide the students with a systematic introduction to the recent developments in deep learning through the coverage of modern machine learning concepts and practical business applications, as well as hands-on experience with modern machine learning frameworks. The course plans to cover neural nets, convolutional neural networks, recurrent networks, deep generative models and deep reinforcement learning.

MIS 56700 Deep Learning For Business Analytics

Deep Learning For Business Analytics

In the ever-evolving landscape of business management, a manager's pivotal role lies in the skillful organization and astute utilization of business data to inform critical decision-making. This master's level course is meticulously designed to empower participants with the essential proficiencies in database management, enabling them to excel in this multifaceted managerial domain. With an emphasis on foundational database management concepts, this course serves as a comprehensive guide to mastering the art of efficient data utilization. The journey begins with delving into the intricacies of conceptual data modeling, culminating in the creation of precise entity-relationship (ER) diagrams. Subsequently, participants will navigate the realm of logical design, immersing themselves in the intricacies of the relational data model. A pivotal skillset in the modern business landscape, the structured query language (SQL) is explored in detail, equipping participants with the capability to extract actionable insights from complex data repositories. This dynamic course curriculum is skillfully reinforced through practical application. Participants engage in collaborative group projects that span successive segments, cementing their grasp of the primary concepts and techniques.

MIS 57600 Database And SQL

Database And SQL

Provides the basic concepts and skills needed to analyze and organize business data, as well as to utilize the organized data to answer a variety of business queries. After successful completion, students will have an understanding of why database management is important and what it entails, how to analyze the data requirements of a business scenario and represent these requirements by means of entity-relationship (ER) diagrams, translate an ER diagram into normalized relations for a relational database management system, write simple and relatively complex data retrieval commands in the SQL language for an Oracle database, use Microsoft Access as a front end to a server database in Oracle, be familiar with several selected topics of current interest in the data management arena.

MIS 58200 Management Of Organizational Data

Management Of Organizational Data

The purpose of this class is to provide students with a basic understanding of the tasks and challenges facing IT and analytics project managers. Students learn about projects, roles and responsibilities of project managers. We start by discussing the skills and approaches commonly used in creating and monitoring project plans and braking complex projects down into manageable segments. We also discuss important areas defined in PMI's PMBOK, like scope, time, cost and quality management. Next we look at how IT projects have traditionally been managed, and move on to the study of agile methods. We go through some of the most important aspects of agile project management, such as user stories, agile teams an agile planning, execution and tracking. In learning these tools and techniques, we take a hands-on approach wherever possible and use project management software, exercises and case studies.

MIS 58500 Information Technology Project Management

Information Technology Project Management

Because data grows exponentially and becomes complex, we need computational methods to collect, store, and analyze them in order to be successful in science, engineering, business, and other professions. Python Programming, is an introductory programming class that meets this need. You will learn how to write computer programs in Python language to solve real-world problems. This class is designed for students that want to learn to computer programming for data science. This course guides students through the basic Python programming language, from initial concepts to final data analysis using python and external packages.

MIS 58600 Python Programming

Python Programming

DevOps describes the intersection of software development and delivery and provides the means to continuously supply the latest functional version of software to customers. DevOps is highly reliant on agile development methods, version control systems, modern software packaging and deployment techniques, and cloud delivery technologies. This course is delivered in three focused units: Development, Deployment, and Maintenance. Students will work both individually and in agile teams to develop, deliver, and refine software projects. Permission of department required.

MIS 58710 DevOps & Technology

DevOps & Technology

This course offers an in-depth exploration of the principles and practices of Business Intelligence (BI) through computational methods. Students will delve into a wide array of topics, ranging from the fundamentals of BI to advanced data manipulation and the application of machine learning techniques in business contexts. The course emphasizes computational proficiency and practical utility. The methods taught are widely applicable across various functions and industries within the digital economy. A key aspect of digital transformation is the ability to make data-driven decisions and leverage artificial intelligence (AI) for business opportunities. While many firms can summarize their data, few possess the computational skills to extract meaningful insights and, if necessary, integrate additional data sources to derive comprehensive business intelligence. More importantly, firms often lack the capability to generate actionable insights. This course is highly hands-on, focusing on problem-solving and deriving insights from real-world data. Students are expected to actively participate through related readings, case discussions, in-class activities, and practical work with datasets, guided by lecture notes, readings, and assignments. The major concepts and techniques will be reinforced through a group project that involves providing data-driven insights into a real-world business problem. The course aims to bridge the gap between theoretical knowledge and practical application, preparing students to utilize computational methods for business intelligence in various professional settings.

MIS 58900 Computational Business Intelligence

Computational Business Intelligence

Graduate-level variable-title course examining strategic, analytical, or emerging MIS topics. Emphasis is placed on advanced data-driven decision-making and the strategic use of technology. Permission of instructor required.

MIS 59000 Visual Analytics

Visual Analytics

MIS 59000 MBT Capstone

MBT Capstone

MIS 59000 Advanced Database

Advanced Database

MIS 59000 Cloud Computing I

Cloud Computing I

MIS 59000 Emerging Tech & Bus Models

Emerging Tech & Bus Models

MIS 59000 Big Data And MLOps

Big Data And MLOps

This course prepares master students with the advanced and frontier technique for analyzing unstructured data that is built on the prerequisite of basic data analysis on structured data (e.g., data mining using python). Upon completion, students are expected to be competent and skilled in collecting, processing, and analyzing online unstructured data using the state-of-art artificial intelligence modeling (e.g., neural networks and deep learning methods) and the mainstream open-sourced toolboxes (e.g., NLTK, scikit-learn, keras, and TensorFlow); students should at least be proficient to design and lead industry-level practical projects conceptually when working with data scientist. We take text and image as examples for illustration and cover applications of: Text mining and feature extraction (e.g., sentiment, topic, readability, etc.); Image classification (e.g., recognition, etc.); Advanced applications (e.g., translations, chatbot, image expression, etc.). The course is formatted as a combination of seminars and hands-on coding practices in class. Students are expected to code (and debug) in the class. The main method topics covered include Crawling unstructured data using scrapy. Representation and embedding of text and image. Unsupervised learning for unstructured data (e.g., LDA topic modeling, clustering, etc.) Supervised learning for unstructured data (e.g., classic ML models, A/D/C/RNN, LSTM, etc.). Permission of instructor required.

MIS 59800 Analyzing Unstructured Data

Analyzing Unstructured Data

The core models of microeconomics are fundamental to day-to-day management decisions. This course will cover economic models that describe firm production, pricing, entry/exit decisions, market efficiency, and welfare. Such economic models will be applied to the analyses of a variety of market conditions, including monopoly, oligopoly, and monopolistic competition. It will provide students with an understanding of the implications of economic theory on technology products, firms, markets, and consumers.

MIS 68000 Economic Analysis Of Technology Markets

Economic Analysis Of Technology Markets

This course is a comprehensive exploration of designing digital products that can improve the quality of people's daily lives. It covers value creation with technology and a human-centered design process including improv brainstorming, storyboarding, interviewing, sketches, and selling. Students will learn how to ideate and how to iteratively refine ideas with real users. Students will consider factors driving technology product design decisions such as the unique economic characteristics of today's technology-intensive markets and their impact on strategic interactions among firms and consumers. Students will also learn to discover unmet user needs, reframe problematic situations, envision multiple possible product concepts, and assess their feasibility, viability, and desirability. The course culminates in the creation of a business model, a product sketch, and a plan for taking the product to market.

MIS 68200 Digital Product Design

Digital Product Design

Digital technologies such as the Internet, IoT, and AI are rapidly and fundamentally transforming today's companies and industries. They have enabled completely new ways for companies to organize work, generate innovations, make decisions, and interact with customers, suppliers, and competitors. This course is designed for students who want to deeply analyze digital transformations and, more importantly, manage technology-driven businesses. Applying information economics principles and theoretical rigor, this course studies how digital technologies affect consumer behavior, business model innovations, market design, and competitive outcomes. This course trains students to apply data analytics skills to real business problems and develop a rich understanding of the strategic value of digital transformations.

MIS 68300 Technology-Driven Business

Technology-Driven Business

This course will cover the foundations of corporate governance and government intervention, exploring the current landscape of each in the context of technology markets. Students will learn how to assess the risks and rewards of disruptive new technologies as they study the unique challenges facing regulators and technology companies. Special attention will be paid to antitrust issues in the technology space, challenges facing digital businesses, and the governance and regulation of artificial intelligence (AI).

MIS 68510 Technology Governance And Regulation

Technology Governance And Regulation

Leading-edge companies in every industry are relying on data and AI to replace intuition and guesswork in their decision-making. This course prepares students to understand how AI can be utilized to create value and a sustainable competitive advantage. It teaches the scientific process of using AI to transform data into predictions and insights for making better business decisions in a real-world setting. Upon completion, students should be able to identify and evaluate value propositions of AI advances, conduct successful AI implementations, and manage AI-driven digital transformations.

MIS 68700 AI For Business Decisions

AI For Business Decisions

Advanced graduate-level variable-title course emphasizing research, innovation, and strategic application of information systems. Topics may include emerging technologies, advanced analytics, or systems research. Permission of instructor required.

MIS Courses

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MIS Courses

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An unofficial catalog for Purdue courses made by Purdue students.GitHub·Maintained byBoilerexams··Join the team