DR. MUGIZI ROBERT RWEBANGIRA -INSTRUCTOR

Ade	David	Kristian
Rhonda	Robert	Seun
Shawna	Sulaimon	Tonique

Syllabus

Grades

SPRING 2010 CLASS

SPRING 2011 CLASS

Date	Day	Lec #	Topic	Materials
1/9	M	1	What is Machine Learning? Probability Review. Bayes Rule
1/11	W	2	Introduction to Octave/Matlab(variables, colon notation)
1/16	M		MARTIN LUTHER KING JR DAY
1/18	W	3	More on Octave (matrix operations)
1/23	M	4	Simple Linear Regression
1/25	W	5	Linear Regression (one variable)
1/30	M	6	Linear Regression (one variable)
2/1	W	7	Linear Regression (multiple variables, polynomial regression)
2/6	M	8	Naïve Bayes Classifier
2/8	W	9	Naïve Bayes Classifier (continued)
2/13	M	10	Perceptron
2/15	W	11	Perceptron (continued)
2/20	M		PRESIDENT’S DAY
2/22	W		!!! TEST 1!!!
2/27	M	12	Perceptron (continued)
2/29	W	13	Gradient Descent
3/5	M	14	Gradient Descent (continued)
3/7	W		MIDTERM
3/12	M		SPRING BREAK
3/14	W		SPRING BREAK
3/19	M	15	Artificial Neural Networks
3/21	W	16	Artificial Neural Networks (continued)
3/26	M		!!CLASS CANCELLED!!
3/28	W		!!CLASS CANCELLED!!
4/2	M	17	Project Presentations
4/4	W		!!CLASS CANCELLED!!
4/9	M	18	Project Presentations
4/11	W	19	Project Presentations
4/16	M	20	Project Presentations
4/18	W	21	Project Presentations