DCS861A Emerging Information Technologies II

Instructors: Dr. Chuck Tappert

Other Information:
Pace Portal  SurveyMonkey  1 Pace Plaza  

Graduate Assistant:

Deep Learning, Ian Goodfellow, Yoshua Bengio, and Aaron Courville. MIT Press, 2016.
TensorFlow for Machine Intelligence, Abrahams, et al. Bleeding Edge Press, 2016.
Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity, Hendler and Mulvehill. Apress, 2016.

Course Description:
     The Emerging Information Technologies two-semester course sequence presents a variety of emerging information technology topics not fully covered in the other DPS course material. Some of the materials covered in the courses are chosen by the instructors with additional topics presented by the student teams and the guest speakers. In covering these materials and in the presentations, many dissertation research possibilities will be discussed.
     The emerging information technology topics covered typically include the technological life cycle, pervasive computing, small computing devices (handheld and wearable computers), communicating with machines in human modalities (voice, handwriting, and natural language applications), wireless communication, big data and analytics, biometrics, pattern recognition, and data mining. The course goals are to learn about the emerging information technologies, their issues and potential impact, and to become aware of various dissertation research possibilities.
     This course provides many opportunities to learn about the emerging information technologies, and particularly those areas requiring further research that could become a dissertation topic. The guest speakers bring you to the frontier of current work in their areas of expertise and present possibilities for further work. The course assignments and team presentations also provide opportunities to investigate topics for potential dissertation work.

Graded Events and Grade Scale

Team topic presentation and asociated Research Day Conference paper: a team presentation on an emerging IT topic of current interest. Include potential dissertation and discussion topics as appropriate.

Classroom etiquette: please turn cell phones off during class time.

Incompletes: in order to be fair to those students who complete the course in a timely manner, our policy is to reduce the grade of those students taking an incomplete by a letter grade for each semester, or portion thereof, that the incomplete is in effect.

Graded Events
Event Possible points per person
Team Topic Presentation
Research Day Conf. Paper
400 points
Individual Participation 100 points
Totals max 500 points

Grade Scale
1000 points = 100%
Grade Assigned Score Definition
A  93-100% 930 or more points Dominates the Material
A-  90-93% 900-929 pointss Masters the Material
B+  87-90% 870-899 points Good Understanding
with Flashes of Stellar Work
B  83-87% 830-869 points Good Understanding
B-  80-83% 800-829 points Aptitude for the Subject
Less than 80%
below 800 points Weak for Graduate Work