BME6938/CIS6930 Multimodal Data Mining

Course Objectives: 1. Understand multimodal data mining in the biomedical domain; 2. Understand the concept, approaches, and limitations in analyzing different modalities of biomedical data. 3. Learn to use biomedical data programming libraries and skills to analyze multimodal biomedical data.

BME3053C Computer Applications for BME

The objectives this course are: 1) Develop a proficiency in the use of computer programming (specifically, MATLAB) to analyze biomedical measurements. 2) Develop an understanding of biomedical engineering problems that require quantitative analysis and visualization.

BME3053C Computer Applications for BME

The objectives this course are: 1) Develop a proficiency in the use of computer programming (specifically, MATLAB) to analyze biomedical measurements. 2) Develop an understanding of biomedical engineering problems that require quantitative analysis and visualization.

Instructor Evaluation: 4.63/5.00, Course Evaluation: 4.38/5.00

BME6938 Multimodal Data Mining

Course Objectives: 1. Understand multimodal data mining in the biomedical domain; 2. Understand the concept, approaches, and limitations in analyzing different modalities of biomedical data. 3. Learn to use biomedical data programming libraries and skills to analyze multimodal biomedical data.

Instructor Evaluation: 4.92/5.00, Course Evaluation: 4.70/5.00

BME3053C Computer Applications for BME

The objectives this course are: 1) Develop a proficiency in the use of computer programming (specifically, MATLAB) to analyze biomedical measurements. 2) Develop an understanding of biomedical engineering problems that require quantitative analysis and visualization.

Instructor Evaluation: 4.83/5.00, Course Evaluation: 4.53/5.00 (Historical highest for this course)

BME6938 Multimodal Data Mining

Course Objectives: 1. Understand multimodal data mining in the biomedical domain; 2. Understand the concept, approaches, and limitations in analyzing different modalities of biomedical data. 3. Learn to use biomedical data programming libraries and skills to analyze multimodal biomedical data.

Instructor Evaluation: 4.87/5.00

BME3053C Computer Applications for BME

The objectives this course are: 1) Develop a proficiency in the use of computer programming (specifically, MATLAB) to analyze biomedical measurements. 2) Develop an understanding of biomedical engineering problems that require quantitative analysis and visualization.

BME3053C Computer Applications for BME

BME3053C Computer Applications for BME

The objectives this course are: 1) Develop a proficiency in the use of computer programming (specifically, MATLAB) to analyze biomedical measurements. 2) Develop an understanding of biomedical engineering problems that require quantitative analysis and visualization.

CAP 5771 Principles of Data Mining

CAP 4770 Introduction to Data Mining

CAP 4770 Introduction to Data Mining

CAP 5610 Machine Learning

CAP 4770 Introduction to Data Mining

Data Mining is the nontrivial extraction of implicit, previously unknown, and potentially useful information from data. It has gradually matured as a discipline merging ideas from statistics, machine learning, database and etc. This is an introductory course for junior/senior computer science undergraduate students on the topic of Data Mining. Topics include data mining applications, data preparation, data reduction and various data mining techniques (such as association, clustering, classification, anomaly detection).

CAP 5610 Machine Learning

Machine learning is concerned with the question of how to make computers learn from experience. The ability to learn is not only central to most aspects of intelligent behavior, but machine learning techniques have become key components of many software systems. For examples, machine learning techniques are used to create spam filters, to analyze customer purchase data, to understand natural language, or to detect fraudulent credit card transactions.