Online Master’s in Informatics Courses

IT alignment to Cloud computing concepts, technologies, models, types, characteristics, architecture, IT governance, corporate politics that support varies building business cases for strategic IT investments, risk management, oversight of cloud based information security policies, and general executive-level business knowledge for information resource managers.

Incorporation of creative, alternative, parallel thinking methods, and computer-aided innovation (CAI) into existing governance processes and protecting the resulting intellectual property as a critical resource to sustain competitiveness in the global marketplace.

Techniques for integrating information from disparate systems by different manufacturers using different formats and communication protocols. Topics include: XML, EDI, Web services, and standards-based open-source collaboration.

Organizing and using resources to complete structured projects, activities, and tasks within defined scope, quality, time and cost constraints including the selection and alignment of performance metrics to bottom-line goals of the enterprise.

Directed research and study in informatics, information technology, information resource management, or healthcare information management. This course may be repeated.

History, foundational techniques, and applications of artificial intelligence (AI) technology including rule-based systems, expert systems, artificial neural networks, supervised and unsupervised machine learning, large language models, generative pre-trained transformers (GPT), and natural language conversational user interfaces. Topics include transformative applications of AI in business, education, healthcare, and the arts.

Human cognitive augmentation, intelligence amplification, and cognitive amplification through using artificial intelligence (AI) and cognitive systems capable of matching or surpassing expert-level human performance. Topics include cognitive architectures, intelligent agent architectures, theories of human expertise, the design of innovative artificial expertise systems, and the societal, cultural, and commercial impacts of the democratization of expertise.

Theoretical foundations, practical applications, and technical aspects of crafting effective prompts to maximize artificial intelligence (AI) performance, evaluating accuracy and relevance of AI behavior and AI responses in different contexts.

Laws, regulations, guidelines, and enforcement dictating data protection safeguards and privacy practices as well as the ethical, moral, and legal issues involved in securing data and information against cybersecurity threats.

Cybersecurity management, network and security foundation, data recovery techniques, network vulnerability assessments and technologies, issues such as cyber intelligence and internet governance, anticipating attacks, using monitoring tools, and developing defensive strategies.

Fundamental topics necessary for digital forensics investigation. Cyber-crime laws, the 4th Amendment, compliance and requirements, collection and handling, analysis, and reporting. Topics include: File forensics techniques, forensics artifacts, and anti-forensics.

Structural design of shared information environments, such as customizable user interfaces, website portals, intranets, and online communities and the conceptual forms maximizing effective presentation and usability.

Use of information technology to facilitate better business decisions by collecting and analyzing the efficiency and productivity of internal operations as well as external influences such as competitors, market trends, and global economics.

Select subjects and current trends in the social, cultural, political, and technical issues associated with information resource management.

Overview of informatics and its implications within the healthcare environment. Clinical decision support, human and organizational factors, public health informatics, interoperability, and current issues in health informatics, including best practices, are emphasized.

Foundational structure of healthcare quality management and patient safety initiatives, effects of internal and external initiatives affecting processes of measuring, monitoring, and analyzing quality patient care through the use of qualitative and quantitative statistical tools, analysis, effective resource utilization, and the application of continuous quality improvement models. Topics also include how new technological applications, such as AI and Telehealth, are impacting healthcare quality improvement and patient safety.

Directed research and study in informatics, information technology, information resource management, or healthcare information management. This course may be repeated.

Preparation of a thesis and research in the pursuit of the masters degree in informatics. Students are required to complete a minimum of 6 hours, but this course may be repeated for additional hours.

Statistical estimation methods using R. Topics will include basic programming in R including simple graphs, data input and output, basic statistical concepts including probability theory, linear regression models, general linear models, piecewise linear regression, logistic regression, and factor analysis including exploratory and confirmatory analysis.

The fundamentals of data mining, data management, and data warehousing. Topics include design and querying of relational databases, design, setup, and use of data warehouses and various data and text mining methodologies.

Case-based approach to understanding the role and impact of data analytics on business performance. Data cleaning and data quality, analytics project life cycle, machine learning, fundamentals of good visualization, effective technical communication strategies, and ethical frameworks for business analytics are explored.

The essential and practical skills in visualization, including computer graphics, visual data representation, physical and human vision models, numerical representation of knowledge and concepts, animation techniques, pattern analysis, and computational methods. Various software tools will be studied including R, gg-plot2, and Tableau 8.

Quantitative modeling tools and techniques used to solve problems faced in modern supply chains such as forecasting demand, determining the capacity of a manufacturing line, and optimizing the production operation.

Principle and practical issues while effectively integrating data analytics topics using R/Python. Topics will include data preparation, missing data, lists, functions, and loops.

Methods and tools to collect, analyze, and report website usage data by visitors, emphasizing the nature of the visits to websites and visitors’ demographics. Concepts, tools, tutorials, and case studies that business managers need to extract and analyze the seven layers of social media data, including text, actions, networks, apps, hyperlinks, search engine, and location layers will be emphasized.