CSCI 268 Internet of Things
Internet of things (IoT) concerns the integration of people, processes, and technology with connectable devices and sensors to enable impactful applications including remote monitoring, status, manipulation, and evaluation of trends. Advancements in miniaturization and the proliferation of low-cost network connected devices, sensors, and machines has seen the expansion of impactful Internet of Things (IoT) applications that have transformed a variety of domain areas from inventory control and manufacturing to transportation. Consumer and business driven applications lead IoT applications due to the monetization of efficiencies afforded by the agility of data-driven business decisions. IoT presents significant opportunity for positive impact on quality of life and social good.
Prerequisites: CSCI 140
Anticipated Terms Offered: varies
DSCI 103 – Data, Computing and Society
Data in the 21st Century draws many parallels to Oil in the 18th Century, while its use is increasing, its applications and full utility remain largely untapped. While limited in usefulness it its raw form, substantial value arises from its refining, that is the derivative forms from its processing, mixture with other components, and its transformation. Such processes on Data are purposed with gaining insights, nuggets of information not directly observable. One finds achievement of efficiencies engendered by the refining of data ranging broadly across diverse domains from transportation and commerce to entertainment and healthcare. More recently, governments have employed data to improve apportionment of funds and delivery of critical services. An organization’s ability to employ data and use it to generate insights enables better decision-making. In this course, we cover introductory concepts purposed with building student background in the Data Science process, that is posing questions, gathering data, developing analyses, and articulating data-informed decisions. We also introduce students to entry level computational tools and methods purposed with extracting insights from data as we survey the Data Science process and consider its impact. Students will also be challenged to consider issues concerning privacy, bias, and ethics surrounding data and crafting data-informed decisions. A goal of the course is to expose students to examples from varied domains.
(This is a general elective course for the Data Science Major and does not count towards the Data Science Minor.)
*LAPTOP Required
Course Designation/Attribute: FA, DI
Anticipated Terms Offered: Annually (Depending of availability of faculty to teach it)
