Data Mining: Advanced Concepts and Algorithms

Data Mining: Advanced Concepts and Algorithms

As the amount of research and industry data being collected daily continues to grow, intelligent software tools are increasingly needed to process and filter the data, detect new patterns and similarities within it, and extract meaningful information from it. Data mining and predictive modeling offer a means of effective classification and analysis of large, complex, multi-dimensional data, leading to discovery of functional models, trends and patterns.

Building upon the skills learned in previous courses, this course covers advanced data mining, data analysis, and pattern recognition concepts and algorithms, as well as models and machine learning algorithms.

Topics include:

• Data mining with big data
• Artificial neural networks
  • Back-propagation
  • Feed-forward networks
  • Radial-basis functions
  • Recurrent neural networks
• Probability graph models and Bayesian learning
• Hidden Markov models
• Support vector machines
• Ensemble learning: bagging, boosting, stacking
• Random forests
• Data mining tools
• Text mining

Practical experience:

• Hands-on data mining projects

Course typically offered: Online in Fall and Spring

Prerequisites: CSE-41288 Advanced Business Intelligence: Introduction to Predictive Analytics  and Fundamentals of Data Science or equivalent experience required.

Next Steps: Upon completion of this course, consider taking the Data Mining Practicum to continue learning.

NOTE:
This course is no longer available.
Students who are currently enrolled in Data Mining for Advanced Analytics certificate program are advised to take CSE-41287 Linear Algebra for Machine Learning as substitute. For any questions, please contact unex-techdata@ucsd.edu.

Course Number: CSE-41262
Credit: 3.00 unit(s)
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