- Lecturer: Fabian Vassel
Search results: 2748
Students are introduced to the basic principles of public relations and how these operate in the practical world of the profession. Of particular note is the full understanding of public relations as a management function that fosters a mutual understanding between an organization and its publics.
This course will provide the IMC major with a foundation upon which the appreciation for the rudiments of visual communication and their application can be developed.
Rapid development and expansion of new media create a variety of new approaches to social media marketing but also new sorts of ethical issues and conundrums. Therefore, there is also the continuous need for IMC practitioners to understand the ever changing digital landscape, understand how social media has disrupted traditional marketing and PR; and be able to evaluate contemporary and prevailing ethical issues.
This course examines how modern industry uses social media, builds online communities, develops strategies and campaigns to enhance the IMC process. It also addresses the ethical issues facing social media marketers, journalists, public relations specialists and bloggers.
The graduate should be able to appreciate the value of various social media networks, identify ethical issues, craft effective social media marketing and content strategies and identify future trends in new media as part of the IMC process.
- Lecturer: Ricardo Baccas
This course introduces probability and statistics to students of Information Technology as well as the application of these concepts to the computing discipline. It examines the basic concepts of probability theory including counting and measuring and conditional probability and independence of events. It studies discrete, continuous, and joint random variables and functions of random variables. The course shows how to sum independent random variables, generate random numbers, and random event generation. It also discusses the Law of large numbers and the Central Limit Theory. The course also introduces linear and nonlinear regression, sampling distributions, confidence intervals, and hypothesis testing. The applications of these concepts to computing will be stressed throughout the course.
- Tutor: Andre' Grant
- Lecturer: Kirk Morgan