64 courses with the subject MIS, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
MIS 175Introduction to Algorithms and Program Design4
This course introduces students to prgamming with an emphasis on computational problem-solving. Topics include program design and testing strategies, programming language syntax and semantics, scalar data types and an introduction to data structures, control structures, iteration, recursion, file input/output exceptions as well as introduction to algroithm analysis. Students will use a high-level programming language to develop programs and reinforce their understanding of topics.
This course continues the study of program development introduced in CSC 175. Topics include intermediate program design, object oriented programming (objects, types, inheritance, and polymorphism), basic data structures such as arrays and strings, and event-driven programming using a graphical user interface (GUI). Students will use a high-level programming language to complete several intermediate sized programming projects to reinforce concepts. Student may not take both CSC 170 and CSC 176.
This course provides an overview of the concepts and methodologies of information systems. The course focuses on the idea of information systems support for competitive decision-making, thus blending technical with managerial topics. Students will develop familiarity with the principles of information systems as well as hands-on experience with a variety of information systems tools and techniques.
MIS 325Introduction to Java Programming Programming4
This course will introduce you to programming and object oriented programming using Java. General programming topics include program design, testing strategies, and control structures such as conditionals, iteration. Object oriented topics include creating and using classes, inheritance and interfaces. Students will also learn about basic data structures such as arrays and strings. Students will solve programming problems in weekly lab sessions. Graduate students in the course will also be introduced to event-driven programming using a graphical user interface (GUI), recursion, and 2-dimensional arrays.
This course is a study of the COBOL programming language, with application of its features for table handling, sorting, sequential and random access file handling and modular programming.
This course will provide you the knowledge and techniques to approach phenomena analytically. Specially, you will learn the role and process of the data science lifecycle in understanding and gaining insight about phenomena, including how to ask the appropriate questions, identify the appropriate data and information needed, use the appropriate tools to analyze a large volume of data, evaluate the findings effectively with parameters, find the appropriate answers, and present the answers and compellingly. In the business context such knowledge can enable organizations to make quality decisions and develop important business strategies that can enhance organizational performance and that can contribute to significant financial gains. You will proficiently acquire such knowledge and techniques through class discussion, lectures, readings, as well as hand-on exercises. Prerequisite(s): STA 202 or MTH 112.
MIS 345Introduction to Human Computer Interaction and Design3
This course provides an introduction to the field of human-computer interaction (HCI), an interdisciplinary field that links computer and industrial design, software engineering, the organizational sciences and cognitive psychology. Students will examine theories of design, technology and interfaces in order to enhance and extend human capabilities. The course will cover foundational theories, principles and guidelines that inform design, as well as how these theories, principles and guidelines are applied in laboratory settings, in organizations and in daily life. Assignments and course projects provide hands-on experiential learning with course topics, and guest speakers and laboratory and industrial tours, when appropriate, will supplement the class lectures and activities.
This course will examine the design, control and operation of accounting information systems with a strong emphasis on integration. The course will present a thorough introduction to basic information systems theory, provide a working knowledge of systems analysis and design techniques, databases and enterprise systems. Understanding and appreciation of accounting information systems is critical to successfully managing, auditing and developing systems to support today's evolving business environment. This course offers a focused look at accounting information systems as part of enterprise resource planning systems, with a focus on SAP and other comparable enterprise systems to demonstrate concepts. Prerequisite(s): Grade of C or above in MIS 201, and in either ACT 201 and ACT 202, or in ACT 203 and ACT 204.
This course introduces students to Systems Analysis and Design (SA&D) principles for both enterprise information systems and AI-driven solutions. Students will learn to analyze organizational processes, uncover business requirements, and document workflows in order to identify automation opportunities and data needs. Through hands-on exercises, they will practice creating key SA&D artifacts (e.g., UML diagrams, requirements documentation) while exploring the potential of AI integration and automation tools to streamline processes and enhance system capabilities. The course balances foundational analysis and design techniques with practical insights into AI-enabled applications, preparing students to contribute effectively to modern system development projects.
MIS 385Programming in Visual Basic With Visual Basic3
This class covers the basics of structured programming using Visual Basic to develop decision support systems or management science applications. The theory and practice of structured programming, logic, systems development are covered in a series of iterative hands-on assignments, which are designed based on practical decision support systems or management science applications. Students can expect to learn how to create and program advanced Excel applications or other equivalent applications. A term project involving the development and documentation of a Visual basic program is required.
MIS 399Independent Study in Information Systems1-6
A student who wishes to pursue an independent study project for academic credit must submit, prior to registration, a proposed plan of study that includes the topic to be studied and the goal to be achieved, the methodology to be followed, schedule of supervision, end product, evaluation procedure and the number of credits sought. The proposal must be approved by the supervising faculty member, the program director and Dean of the Madden School. The proposal will be kept on file in the office of the Dean of the Madden School. The hours and credit are to be determined by the student and the program director.
MIS 411Crowds, Social Media & Digital Collaboration3
Over the past years, crowds, social media, and digital collaborations have emerged as important topics in the IS field. Social media and other social information systems not only support communications and collaborations among the general crowd but also harness collective intelligence for innovation. This course covers the basic concepts and theories of social media, crowdsourcing, remixing, and sharing economy. Students will also learn analytics and applications around these trending topics.
This course provides an introduction to Business Intelligence, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data storage and retrieval, thus this course will review logical data models for both database management systems and data warehouses. Students will learn to extract and manipulate data from these systems and assess security-related issues. Data mining, visualization, and statisical analysis along with reporting options such as management dashboards and balanced scorecards will be covered. Technologies utilized in the course included SAP Business Warehouse, SAP Business Objects, Crystal Reports, and RapidMiner.
With the increased use of big data creating a paradigm shift in how marketers make decisions, the need to be able to extract meaningful information from this voluminous amount of data to make smarter decisions is becoming more important than ever. The course will provide students with the tools to develop a systematic, analytical approach to marketing decision making. The course aims at preparing students to (1)understand the value of competitive advantages leveraged by analytics; (2) understand the existence, advantages and limitations of different analytical approaches; and (3) to apply, interpret the input, and communicate the output from these tools and models, and apply them to help make fact-based decisions. The course takes on a hands-on experiential approach with real-world databases to facilitate the comprehension of the different analytical approaches discussed in class.
This course serves as an introduction to the cloud computing environment, discussing both fundamental concepts of how and why cloud systems work, as well as cloud technologies that manifest these concepts, such as Amazon AWS, Microsoft, Azure, and Open Stack. Students will learn about virtualizations, data parallelisms, security and privacy, cloud storage mechanisms, and cloud design architectures in the context of distributed systems. This course will be taught in a lab lecture style utilizing Amazon Web Services (AWS) as a learning platform. Recommended predecessor courses: MIS-478, MIS-455.
This course will offer an understanding of how human resource information systems are applied in organizations to support organizational strategy, improve efficiency and flexibility, increase productivity and performance, enhance retention and ensure compliance with employment law. The focus will be on merging information systems with a strategic human resource perspective. This course provides students with the knowledge, skills and abilities to identify, assess, develop and maintain an effective HR system. Students will develop a thorough understanding of the plan, design/acquisition, implementation and applications of a human resource information system (HRIS).Prerequisite(s): MIS 201 and HRM 301 or permission of the instructor.
This course focuses on introductory government systems concepts, processes and functions, utilizing the Federal Acquisition Regulations (FAR). Students will examine FAR regulations, processes and nomenclature, utilizing existing and proposed regulations and industry case studies, and appropriate support technology. Guest speakers and field research provide students with access and information from industry and academia.
MIS 440Machine Learning for Business Applications3
Machine learning, a subset of artificial intelligence, gives computers the capability to learn from data, identify patterns, and make decisions without being explicitly programmed. This course will cover different supervised and unsupervised machine learning algorithms, and their applications to structured and unstructured data including financial, marketing, health care, social media, entertainment, and socio-economic data. Four main problem domains will be covered (i) regression, (ii) classification, (iii) clustering, and (iv) association. Using machine learning to transform data into business decisions and communication of the results and insights from the analysis will be emphasized throughout the course. This course does not assume any prior exposure to machine learning theory or practice. Prerequisite(s): ANL 301 and STA 202, or permission of department chair.
As artificial intelligence (AI) has generated revolutionary impacts on daily life and all sectors of business, it becomes critically important to learn to develop and work with AI tools. This course introduced the nature and techniques of artificial intelligence in business applications. It focuses on what has contributed to the adoption of AI by business so rapidly and profoundly: automating business tasks and processes and performing analytics to generate insights over business performance. Students will learn the knowledge of the AI project development life cycle as well and hands-on skills to utilize AI tools. In addition, the course explores such important topics as human working with AI, and responsible and ethical AI. At the end of the semester, students should be able to understand, participate in, lead and evaluate an AI project and technically competent in impactful AI tools.
MIS 445Mobile Applications and Business Strategies3
The course explores the important challenges and connect with their stakeholders. Students will learn the technical, managerial and marketing aspects of mobile applications. Technically, they will learn the development process and technical infrastructure of mobile applications. Mangerially, students will learn how to develop business strategies to exploit mobile applications for the advancing and repositioning of organizations. For marketing, students will learn to market the newly developed mobile applications and at the same time to use mobile applications to market and promote the organizations and their products or services.
Deep learning is one class of machine learning algorithms. It is one of the fundamental topics of artificial intelligence. This course aims to provide students with the basics of deep learning so that students can apply it to various AI tasks. In this course, we will start with simple machine learning concepts and models, then we will move on to deep neural networks and their applications.
This course provides students with the knowledge of the design, use, and evaluation issues of health informatics applications. The topics include: (1) health informatics as a discipline; (2)career options for health informatics; (3)major health applications and commercial vendors; (4) strategic information systems planning; and (5) new opportunities and emerging trends.
This course covers the requirements, management and performance of enterprises engaged in the use of technology. Requirements determination, analysis, design, and cost management activities for technological enterprises are covered; a focus on the management of life cycle costs is emphasized. The management of third-party organizations, outsourcing and project management activities are also covered. The legal, environmental, and ethical issues associated with the management and performance of technological enterprises are important components of this course. Guest speakers and case studies from local, national, and international technological enterprises, agencies and regulatory organizations are employed in this course.
MIS 460Project Management for Intelligent Systems3
This course prepares students to plan, manage, and deliver successful system development projects, with a focus on both traditional enterprise information systems and AI-enhanced applications. Anchored in the Project Management Institute's PMBOK Guide, students will learn core project management principles while exploring how AI technologies are transforming project planning, execution, monitoring, and stakeholder engagement. Through hands-on projects and real-world case studies, students will apply project management methodologies and leverage AI-powered tools to improve forecasting, automate workflows, optimize schedules, and manage risk. The course emphasizes ethical and professional conduct and prepares students for micro-credentials in AI-enhanced project management. Prerequisite(s): MIS 201 or permission of department chair/program director.
Information systems, composed of technology, people, information, systems, organizations, policies, and society, contain many complex and interdependent elements. The large-scale systems within which many information systems reside, including organizations, technology systems, communities, nations, and even human biological systems, can be similarly complex, with interdependent elements. Information systems researches study technology, people, information, organizations and systems in order to understand information systems, and the interactions between and the impacts of those elements and information systems, on individuals, groups, organizations, and other systems. Research design is the process of formulating a research plan that addresses research questions of interest. A sound research design ensures that the data and evidence obtained assists in effectively addressing the research questions under study. Key to good research design are research methods, approaches and techniques used to carry our research, which are facilitated by the collection of meaningful and useful data and evidence, and by analysis, assessment and interpretation of that data and evidence. This course provides an overview of the fundamentals of research design and research methods, including research question and hypothesis formulation; data and evidence collection and analysis; and the challenges of research design and methods. Students in this seminar course work closely with a Le Moyne factuly mentor while conducting research in Information Systems, either on campus at Le Moyne or in the field. McDevitt Information Systems Research Scholars who have gone through a year-long faculty research mentoring process in previous years and have prepared and published their own research also seve as mentors to students in this class. Students and their mentors participate in bi-monthly research seminars led by the Le Moyne faculty mentor, at which they present their research, collaborate on their findings and discuss their progress. Open to students eligible for Departmental Honors, Honors in Information Systems, and Independent Study Research. Junior or Senior standing; or permission of instructor. Prerequisite(s): MIS 201.
This course provides an overview of the concepts and principles of telecommunications systems and networks, blending technical with managerial topics. Students will focus on the challenges inherent in securing financial telecommunications networks, particularly the challenges of insider threats. Students will local area networks, wide area networks, wireless networks, value-added networks, as well as other networks. Students will complete a series of network installation and test projects, and will analyze network design cases throughout the semester. Guest speakers from industry and case studies from on-going research will provide a real-world contect for the topics discussed in class. Students may sit for network certification following completion of the course.
This course introduces students to the foundations of data management, with a central focus on SQL. Students will use SQL to define, query, and manipulate structured data in support of both enterprise information systems and artificial intelligence (AI) applications. The course emphasizes techniques to wrangle, transform, and validate data for use in analytics, generative AI, and machine learning workflows. Following a learn-by-example pedagogy, students will explore how to generate SQL-based answers to real business questions. Practice exercises, solution reviews, and assignments reinforce learning throughout the semester.
Participation in a real-world learning experience is provided in internship opportunities. The intern reports as required to a faculty member, and both student and faculty member assesses the internship as it relates to the student's academic program and desired organizational experiences.
MIS 495Special Topic in Information Systems Research Methods3
Information systems, composed of technology, people, information, systems, organizations, policies, and society, contain many complex and interdependent elements. The large-scale systems within which many information systems reside, including organizations, technology systems, communitites, nations, and even human biological systems, can be similarly complex with interdependent elements. Information systems researchers study technology, people, information, organizations and systems in order to understand information systems, and the interactions between and the impacts of those elements and information systems, on individuals, groups, organizations, and other systems.
This course is intended for honors students and is required for the honors degree in Information Systems. The student conducts an independent research project under the guidance of at least one faculty member in the program. The Honors Committee evaluates a written and oral presentation of the research project. This course may only be taken by permission of the program director.
An overview of management information systems (MIS) and their structure is provided through case analysis. Topics covered include the underlying concept of information, decision-making, management and how organizations affect the design of information systems. The impact of information systems on human behavior, organizations and societies is analyzed. Information resources management models underlie the technical and management focus of the course. Students are expected to complete group and individual projects using commercially available spreadsheet, database and systems analysis software packages.
MIS 525Introduction to Java Programming Programming3
This course will introduce you to programming and object oriented programming using Java. General programming topics include program design, testing strategies, and control structures such as conditionals, iteration. Object oriented topics include creating and using classes, inheritance and interfaces. Students will also learn about basic data structures such as arrays and strings. Students will solve programming problems in weekly lab sessions. Graduate students in the course will also be introduced to event-driven programming using a graphical user interface (GUI), recursion, and 2-dimensional arrays.
This course focuses on introductory government systems concepts, processes and functions, utilizing the Federal Acquisition Regulations (FAR). Students will examine FAR regulations, processes and nmenclature, utilizing existing and proposed regulations and industry case studies, and appropriate support technology. Guest speakers and field research provide students with access and information from industy and academia.
This course will examine the design, control and operation of accounting information systems with a strong emphasis on integration. The course will present a thorough introduction to basic information systems theory, provide a working knowledge of systems analysis and design techniques, databases and enterprise systems. Understanding and appreciation of accounting information systems is critical to successfully managing, auditing and developing systems to support today's evolving business environment. This course offers a focused look at accounting information systems as part of enterprise resource planning systems, with a focus on SAP and other comparable enterprise systems to demonstrate concepts. Prerequisite(s): Grade of C or above in MIS 201 (or MIS 501), and in either ACT 201 and ACT 202, or in ACT 203 and ACT 204.
This course covers the management, strategies, and performance of enterprises engaged in digital transformation. Digital strategies in value chain and supply chain activities, innovation and leadership during inflection points, and alignment of digital strategies with organizational capabilities and processes are introduced. Organizational value propositions and shared value strategies, ethics, and organizations' sustainability impacts are covered in the course. The role of digital leadership and governance, including ethics in compliance and audits, are important components of the course. Students will complete and present a semester-long project in digital transformation for an external organization. Guest speakers and case studies from local, national, and international organizations are employed in this course.
MIS 611Crowds, Social Media & Digital Collaboration3
Over the past years, crowds, social media, and digital collaborations have emerged as important topics in the IS field. Social media and other social information systems not only support communications and collaborations among the general crowd but also harness collective intelligence for innovation. This course covers the basic concepts and theories of social media, crowdsourcing, remixing, and sharing economy. Students will also learn analytics and applications related to these trending topics. (Please note that students who have taken MIS 411 should not take this course).
MIS 690Graduate Information Systems Independent Study3
This course provides an opportunity for graduate students to conduct independent research under the direction of a faculty member. Since the study of Information Systems is interdisciplinary, research linking business, technology and social and organizational science in explorations of how systems that convey information work can be studied independent study format--whether those systems are human, technological, natural, economic, social or other. Research in Information Systems thus explores technical and business topics, along with ethical questions that arise in business applications of technology in organizations. Open to students eligible for graduate Business of Information Systems research. Prerequisite(s): MIS-501; or permission of instructor.
This course offers a rigorous, example-driven approach to enterprise data management and governance, with strong emphasis on SQL proficiency and advanced data preparation techniques. Students will learn to model, query, transform, and manage structured data for use across enterprise information systems and AI-driven environments. Topics include data quality enforcement, metadata and lineage tracking, role-based access, data ethics, and audit strategies. Students will also evaluate how governance policies impact data usability for analytics, decision support, and machine learning. Through extended hands-on assignments, real-world use cases, and reflection on technical readings, students will develop a strategic understanding of how data assets are managed and governed at scale.
This course is designed to provide students with problem-solving skills in the field of quantitative management. The case approach is adopted to introduce complex real life examples to student-teams in a competitive environment. The course also introduces theoretical grounds for some analytical models emphasizing the assumptions and limitations of these models. The assigned cases include applications of regression, networking, linear programming, PERT, queuing theory, decision making under uncertainty and simulation. The students are required to use available computer packages as problem-solving tools and are encouraged to conduct sensitivity (what-if) analysis in their decision making approaches.
This course introduces students to system development methodologies for both enterprise and AI-driven information system solutions that can automate or augment business processes efficiently and/or that can help implement business strategies effectively. Particularly, it will focus on the analysis and design stage of the systems development life cycle. Students will learn to analyze business processes and uncover automation opportunities and data needs. Students will learn to utilize conventional and AI-powered tools to gather, document, and communicate functional and non-functional requirements for enterprise and AI-driven business systems and produce analysis and design artifacts.
Data is useful if relevant and insightful information can be extracted from it to better understand the past (descriptive analytics), anticipate future events (predictive analytics), and direct the course of the best decision (prescriptive analytics). This course will cover different supervised and unsupervised machine learning algorithms, and their applications to structured and unstructured data including financial marketing, health care, social media, entertainment, and socio-economic data. te effective communication of the results and insights from the analysis, including via well-designed visualizations will be emphasized throughout the course. This course does not assume any prior exposure to machine learning theory or practice.
This course focuses on the challenges associated with risk management in large-scale systems. It considers the nature of social, organizational and technological risk and discusses the role of risk analytic, risk management and risk communications. It also discusses several analytic approaches to risk management and mitigation and analyzes case studies of risk in several large-scale systems: aerospace, biomedical, global networks, healthcare, transportation and safety-critical domains such as firefighting and oil spill response. Using several strategic models, students discuss the importance of tactical and strategic risk management and employ several of the models in case analyses.
This course provides students with the knowledge of the design, use, and evaluation issues of health informatics applications. The topics include: (1) health informatics as a discipline; (2) career options for health informatics; (3) major health applications and commercial vendors; (4) strategic information systems planning; and (5) new opportunities and emerging trends.
This course focuses on introductory project management processes, technology and tools, utilizing the Project Management Institute's (PMI) Project Management Body of Knowledge (PMBOK) and the Software Engineering Institute's (SEI's) Capability Maturity Model Integration (CMMI) processes and nomenclature. Students examine the processes and theory of project management as well as industry case studies, and will utilize project management software in support of their management activities. Guest speakers and field research provide students with access and information from industry and academia. Students are engaged in a semester-long project. Initially, they are required to identify the project scope and team charter for their project; subsequent assignments require them to prepare a business case, work breakdown structure, cost estimate, and final project documentation for their project.
MIS 712Information Systems and Network Security Cybersecurity3
This course provides an overview of the concepts and principles of telecommunications systems and networks, blending technical with managerial topics. Students will focus on the challenges inherent in securing financial telecommunications networks, particularly the challenges of insider threats. Students will local area networks, wide area networks, wireless networks, value-added networks, as well as other networks. Students will complete a series of network installation and test projects, and will analyze network design cases throughout the semester. Guest speakers from industry and case studies from on-going research will provide a real-world context for the topics discussed in class. Students may sit for network certification following completion of the course.
The course explores the important challenges and needs of today's organizations to go mobile to connect with their stakeholders. Students will learn the technical, managerial and marketing aspects of mobile applications. Technically, they will learn the development process and technical infrastructure of mobile applications. Mangerially, students will learn how to develop business strategies to exploit mobile applications for the advancing and repositioning of organizations. For marketing, students will learn to market the newly developed mobile applications and at the same time to use mobile applications to market and promote the organizations and their products or services.
This course provides an introduction to Business Intelligence, including the processes, methodologies, infrastructure, and current practices used to transform business data into useful information and support business decision-making. Business Intelligence requires foundation knowledge in data storage and retrieval, thus this course will review logical data models for both database management systems and data warehouses. Students will learn to extract and manipulate data from these systems and assess security-related issues. Data mining, visualization, and statistical analysis along with reporting options such as management dashboards and balanced scorecards will be covered. Technologies utilized in the course included SAP Business Warehouse, SAP Business Objects, Crystal Reports, and RapidMiner.
This course covers the requirements, management and performance of enterprises engaged in the use of technology. Requirements determination, analysis, design and cost management activities for technological enterprises are covered; a focus on the management of life cycle costs is emphasized. The management of third party organizations, outsourcing and project management activities are also covered. The legal, environmental and ethical issues associated with the management and performance of technological enterprises are important components of this course. Guest speakers and case studies from local, national and international technological enterprises, agencies and regulatory organizations are employed in this course.
In a world where data is more valuable than oil, the need to apply cutting-edge computational analyses, in addition to conventional statistical approaches, to derive meaning from large noisy databases and provide insight into understanding the outcome of marketing strategies is becoming more important than ever. this course will teach students how to leverage data and use analytics to form impactful marketing strategies. By learning the different analytical approaches and how to apply them to make marketing decisions, students enhance their understanding of the importance of marketing analytics.
This course serves as an introduction to the cloud computing environment, discussing both fundamental concepts of how and why cloud systems work, as well as cloud technologies that manifest these concepts, such as Amazon AWS, Microsoft, Azure, and Open Stack. Students will learn about virtualizations, data parallelisms, security and privacy, cloud storage mechanisms, and cloud design architectures in the context of distributed systems. This course will be taught in a lab lecture style utilizing Amazon Web Services (AWS) as a learning platform. Recommended predecessor courses: MIS 712, MIS 717.
This course will offer an understanding of how human resource information systems are applied in organizations to support organizational strategy, improve efficiency and flexibilty, increase productivity and performance, enhance retention and ensure compliance with employment law. The focus will be on merging information systems with a strategic human resource perspective. This course provides students with the knowledge, skills and abilities to identify, assess, develop and maintain an effective HR system. Students will develop a thorough understanding of the plan, design/acquisition, implementation and applications of a human resource information system (HRIS).
This course will provide you the knowledge and techniques to approach phenomena analytically. Specially, you will learn the role and process of the data science lifecycle in understanding and gaining insight about phenomena, including how to ask the appropriate questions, identify the appropriate data and information needed, use the appropriate tools to analyze a large volume of data, evaluate the findings effectively with parameters, find the appropriate answers, and present the answers and compellingly. In the business context such knowledge can enable organizations to make quality decisions and develop important business strategies that can enhance organizational performance and that can contribute to significant financial gains. You will proficiently acquire such knowledge and techniques through class discussion, lectures, readings, as well as hand-on exercises. Prerequisite(s): STA 501.
MIS 741Artificial Intelligence, Automation, and Analytics3
As artificial intelligence (AI) has generated revolutionary impacts on daily life and all sectors of business, it becomes critically important to learn to develop and work with AI tools. This course introduced the nature and techniques of artificial intelligence in business applications. It focuses on what has contributed to the adoption of AI by business so rapidly and profoundly: automating business tasks and processes and performing analytics to generate insights over business performance. Students will learn the knowledge of the AI project development life cycle as well and hands-on skills to utilize AI tools. In addition, the course explores such important topics as human working with AI, and responsible and ethical AI. At the end of the semester, students should be able to understand, participate in, lead and evaluate an AI project and technically competent in impactful AI tools.
Deep learning is one class of machine learning algorithms. it is one of the fundamental topics of artificial intelligence. This course aims to provide students with the basics of deep learning so that students could apply it in various AI tasks. In this course, we will start with simple machine learning concepts and models, then we will move on to deep neural networks and their applications.
This course focuses on the intricacies of Generative AI, with a concentration on practical applications and hands-on learning. The curriculum begins by covering the theoretical foundations of generative AI, exploring deep learning model backgrounds and transformer-based architectures, while examining their underlying mechanisms. Students will learn how to customize and deploy generative AI models, gaining the skills to integrate generative AI into business use cases. The course also focuses on designing and building g AI agents into complex automated workflows enabling sophisticated automation solutions. This course provides students with hands-on experience by equipping them with the cutting-edge skills required to navigate the fast-evolving field of generative AI and to drive innovations and meet organizational objectives in various industries.
This course explores the dynamic field of algorithmic trading with a focus on practical applications and hands-on learning. Students will gain a strong foundation in financial market structures, trading strategies, and quantitative analysis while developing, backtesting, and optimizing trading algorithms. Leveraging a leading low-code algorithmic trading platform, students will access historical data, simulate live trading, and implement robust risk management techniques. The course also emphasizes integrating trading models into automated workflows for seamless execution. By the end of the course, students will acquire the skills to design and deploy sophisticated algorithmic trading systems, preparing them for careers in quantitative finance and financial technology. Pre-requisites: MIS 501 or instructor permission.
This course is designed to introduce students to the principles and best practices of data visualization within the realm of business analytics. In an era dominated by data-driven decision-making, the ability to effectively communicate insights through visualization is indispensable across various fields, including marketing, finance, operations, and human resources. Students will gain hands-on experience with industry-standard tools like Tableau and Power BI, learning how to create, critique, and improve visualizations to explore, explain, and influence using data. The course emphasizes data storytelling and equips students with the skills to support managerial decision-making and strategic analysis.
Information systems, composed of technology, people, information, systems, organizations, policies, and society, contain many complex and interdependent elements. The large-scale systems within which many information systems reside, including organizations, technology systems, communities, nations, and even human biological systems, can be similarly complex, with interdependent elements. Information systems researches study technology, people, information, organizations and systems in order to understand information systems, and the interactions between and the impacts of those elements and information systems, on individuals, groups, organizations, and other systems. Research design is the process of formulating a research plan that addresses research questions of interest. A sound research design ensures that the data and evidence obtained assists in effectively addressing the research questions under study. Key to good research design are research methods, approaches and techniques used to carry our research, which are facilitated by the collection of meaningful and useful data and evidence, and by analysis, assessment and interpretation of that data and evidence. This course provides an overview of the fundamentals of research design and research methods, including research question and hypothesis formulation; data and evidence collection and analysis; and the challenges of research design and methods. Students in this seminar course work closely with a Le Moyne factuly mentor while conducting research in Information Systems, either on campus at Le Moyne or in the field. McDevitt Information Systems Research Scholars who have gone through a year-long faculty research mentoring process in previous years and have prepared and published their own research also seve as mentors to students in this class. Students and their mentors participate in bi-monthly research seminars led by the Le Moyne faculty mentor, at which they present their research, collaborate on their findings and discuss their progress. Open to students eligible for Master's Thesis research. Prerequisite(s): MIS 501.
MIS 785Programming in Visual Basic With Visual Basic3
This class covers the basics of structured programming using Visual Basic to develop decision support systems or management science applications. The theory and practice of structured programming, logic, systems development are covered in a series of iterative hands-on assignments, which are designed based on practical decision support systems or management science applications. Students can expect to learn how to create and program advanced Excel applications or other equivalent applications. A term project involving the development and documentation of a Visual basic program is required.
Courses in this series offer an in-depth exploration of specific issues within the field of management information systems, as well as topics of current interest to students and instructors.
MIS 795Special Topics in Information Systems Research Methods3
Information systems, composed of technology, people, information, systems, organizations, policies, and society, contain many complex and interdependent elements. The large-scale systems within which many information systems reside, including organizations, technology systems, communitites, nations, and even human biological systems, can be similarly complex with interdependent elements. Information systems researchers study technology, people, information, organizations and systems in order to understand information systems, and the interactions between and the impacts of those elements and information systems, on individuals, groups, organizations, and other systems.
Participation in a real-world learning experience is provided in internship opportunities. The intern reports as required to a faculty member, and both student and faculty member assess the internship as it relates to the student's academic program and desired organizational experiences. Six hours of approved work experience is required to generate one credit.
This course provides an opportunity for graduate students to conduct independent research under the direction of a faculty member. Since the study of Information Systems is interdisciplinary, research linking business, technology and social and organizational science in explorations of how systems that convey information work can be studied in a students masters thesis--whether those systems are human, technological, natural, economic, social or other. Research in Information Systems thus explores technical and business topics, along with ethical questions that arise in business applications of technology in organizations.
