ECE398BD: Fundamentals of Machine Learning (Lectures)
You can find the typed notes for this class [here]. The course follows essentially linearly with the notes.
 Topic  Quiz 
Lecture 1  Introduction to the course; Review of linear algebra and probability  
Lecture 2  kNearest Neighbor Classifiers and Bayes Classifiers  
Lecture 3  Linear Classifiers and Linear Discriminant Analysis  
Lecture 4  Naive Bayes and Kernel Tricks  Quiz 1, 4:30 PM 
Lecture 5  Logistic Regression, Support Vector Machines and Model Selection  
Lecture 6  Kmeans Clustering  Quiz 2, 4:30 PM 
Lecture 7  Linear Regression  
Lecture 8  SVD and EigenDecomposition  
Lecture 9  Principal Component Analysis  
Lecture 10  Optimization Methods for Machine Learning, Q&A 

Useful links:
Big Data Tutorial slides
Big Data in the music industry
Big Data and Machine Learning in Healthcare: How, Why, and When
