Lecture Notes
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Depending on browser settings pdf, ppt, or pptx files may either download or open in a separate window on your computer.
Note that all files are the intellectual property of the presenters and copyright by the authors. No material may be transmitted or distributed in any manner without the expressed written permission of the author. Additional lecture material presented during class is not shown because of copyright restrictions.
- Fundamental Mathematical and Statistical Background
- Introduction to Data Science
- Introduction to R
- Matrix Algebra
- Statistical Inference
- Statistical Inference: Sampling Distributions
- Statistical Inference: Confidence Intervals for Means
- Statistical Inference: Confidence Intervals for Proportions
- Statistical Inference: Hypothesis Testing
- Test and Validation
- Time Series Analysis
- Linear Regression
- Unsupervised Learning
- Fundamentals of Databases and Data Mining
- Database Fundamentals
- Relational Database Models
- SQL
- Data Mining and Big Data
- Feature Engineering
- Data Warehousing
- Frequent Pattern Mining
- Fundamentals of Machine Learning Laboratory
- Guest Lectures
