Information Technology 685
1. Catalog Entry
Credit hours (3)
Prerequisites: ITEC 542 and ITEC 660
This course introduces analytical techniques from Artificial Intelligence and statistical techniques to analyze big data sources including social media, mobile devices and sensors. The course also covers parallel algorithms and industry best practices to enable data-driven decisions.
2. Detailed Description of Course
1) Databases and their evolution
2) Big data technology, no-SQL
3) AI techniques
4) Logic Rule, Uncertainty
5) Bayes rule, Naïve Bayes, Bayesian Network
6) Sentiment analysis
7) Association rule mining
8) Learning latent model, Machine learning
9) Cluster, classification
10) Linear and logistic regression
11) Least square, optimization
12) Non-linear model, Neural Network
13) Dimensionality reduction
14) Anomaly detection
15) Recommend system
16) Parallel computing, Map Reduce
17) Analytics tools
3. Detailed Description of Conduct of Course
The course will be delivered in a lecture and discussion format with demonstration and application of different information analytics techniques and algorithms.
4. Goals and Objectives of the Course
Students who complete this course will be able to:
1) Categorize data into groups based on attributes.
2) Classify information based on existing data.
3) Identify the relationship between elements of a decision.
4) Understand optimization, maximizing certain outcomes while minimizing others.
5) Develop decision logic or rules that will produce the desired action.
6) Predict an event in the future effectively based on certain model
7) Seek out subtle data patterns to answer questions about customer performance, such as fraud
8) Understand requirements in using big data analytics.
9) Simulate human behavior or reaction to given stimuli or scenarios.
5. Assessment Measures
A significant component of the assessment must measure each individual student’s mastery of the conceptual and applied knowledge and skills described in the course objectives. Evaluations may include but are not limited to assignments, projects, presentations, quizzes, and examinations.
6. Other Course Information
Review and Approval
April 23, 2014