Undergraduate Courses
This website contains links to the official pages of the courses I offer in the undergraduate education.
- BIL 1003 Introduction
To Computer Engineering
Student orientation, critical and analytical thinking, data manipulation, operating systems, algorithms, Python coding, database systems and networking.. - BIL 3020 Introduction to Data
Science
Basic concepts; Data Types; Data Preparation; Dealing with Missing/Noisy Data; Data Reduction; Data Augmentation; Feature Selection; Outlier Removal; Supervised/Unsupervised Learning; Regression Modeling; Model Evaluation; Association Rules; Data Summarization and Visualization. - BIL 1004 Probability
and Statistics(previous semesters)
Basic probability concepts, conditional probability, random variables, pdf, cdf, discrete distributions, continuous distributions, multivariate distributions, moments, estimation, regression, confidence interval.. - BIL 4008 Data
Mining(previous semesters)
Preparing the data, data reduction, learning from data, statistical methods, decision trees, ensemble learning, cluster analysis, association rules, text mining, visualization methods - BIL 4001
Engineering Design and BIL 4000 Final Project
Popular and interesting final projects -
SEC 430 Machine
Learning (previous semesters)
Supervised learning, Bayes Decision Theory, Parametric methods, Feature Extraction, Clustering, Non-parametric methods, Decision trees, Kernel methods... -
COM 2001 Object-Oriented Programming
(previous semesters)
C++ syntax, pointer to functions, classes, objects, inheritance, composition, operator overloading, templates, virtual functions, etc.