We are interested in adjuncts/part-time instructors who can provide instruction and expertise in one or more of the following areas for our graduate students at the iSchool: Information Management and Technology, Information Resources, cloud management, Public Libraries, Applied Machine Learning. Please see specific classes below and their class description and note in your cover letter which class you are interested in teaching. Those from marginalized groups, women, and veterans are encouraged to apply. · IST 614 Information Technology Management and Policy o This course introduces concepts and practices for information technology management and policy in public and private organizations and provides an overview of general management principles and how various types of information technology (IT) are a key strategic and tactical enabler for most business functions. The course also highlights the role of policy for IT and corporate governance, service delivery, standards, privacy, rights, ethics, accessibility, and security. The course has assignments and case studies promoting a deeper understanding of how to apply IT management and policy concepts · IST 615 Cloud Management o This course will equip students with skills in cloud enterprise service creation and management, and technical and business knowledge required for assessing opportunities and risks of cloud services. The course focuses on developing skills to manage cloud instances through lab assignments. Some of the labs use the services/infrastructure provided by top Cloud vendors in the market today. We note the course uses – cloud services – but some activities must be done in the student’s own accounts and machines. Conceptual themes will also be presented alongside technical aspects of cloud management. · IST 616- Information Resources: Organization and Access o Thursdays 5:00-7:45pm o This course is an introductory survey of principles, techniques, and standards used information systems to represent and organize information, especially those implemented in libraries and information centers. Goals of the course are twofold: (1) for those students that will not pursue a concentration in this area, to provide an overview of the topics, and (2) for those students who will concentrate in systems and technical services, to serve as a foundation course. The course covers the fundamental concepts of theory and practice in information organization, storage, and retrieval, including an introduction to existing systems and standards. Each topic is covered at the introductory level, expecting students who wish to pursue any of the areas to take further coursework. · IST 672 Public Library as Institution o This seminar in public libraries explores aspects of the public library within the context of demographic and technological changes and shifting economic and political forces. This course will place emphasis on the interrelationship of the public library with these forces. This course supports the mission of the university by educating students about the potential of a powerful civic institution to increase opportunity for all members of their respective communities. · IST 707 Applied Machine Learning o An introduction to advanced machine learning techniques and algorithms with a focus on machine learning model building and optimization, real-world applications, communication, ethics, and future directions in the field. This course will introduce the application of advanced machine learning methods for extracting patterns and knowledge from data to address stakeholder needs. The principles and theories underlying the methods will be discussed, and methods will be related to the issues in applying to real business and research problems. Students will acquire hands-on experience using state-of-the art tools to apply the methods covered. A central focus in this course is on communication, including translating stakeholder needs into technical methods, and communicating results in a transparent and compelling manner. The topics of the course will include the key tasks in applied machine learning, including data preparation, concept description, unsupervised and supervised techniques, deep learning, feature construction, optimization, evaluation, analysis, communication, and ethics. Through the exploration of the concepts and techniques of data analytics and practical exercises, students will develop skills that can be applied to business, science, or other organizational problems. This is a “flipped” class, meaning that the materials are made available for you to review in advance of class meetings, and class meetings are reserved for working through examples and clarifying points of confusion. There will be weekly readings based on the textbook, weekly assignments and in class oral “quizzes” to check learning progress, several larger assignments, and an extended group project.