In this page I give an overview of my previous teaching experience at Pennsylvania State University, at Michigan Technological University and in Cardiff University.:

Cardiff University:

**MA1500 – Introduction to Probability (Fall 2015, Fall 2016, Fall 2017, Fall 2018, Fall 2019, Fall 2020)**: This is the first probability course for first year Math undergraduate students at Cardiff University. It covers basic probability including probability theory, basic distributions, moments, discrete joint probability distributions, conditional probability distributions.**MA2501 – Programming and Statistics (Spring 2016, Fall 2016, Spring 2018, Spring 2019, Spring 2020, Spring 2021)**: This is a module which has a two-fold objective. First to teach the basics of programming principles to students and second to show them how they can do standard statistical techniques (exploratory data analysis, hypothesis testing, regression, multivariate data analysis, dimension reduction, clustering) in a software. I am teaching this using R. In this class I am using a flipped-classroom approach were a handout is given to student to go through simple examples and we then meet in class to do more complicated examples. Each week we spend 1 teaching hour in a standard lecture room and 2 teaching hours in a lab, which enables active learning to all the students. The students have coursework (almost every week) and they have a project were we usually simulate a board game.**MA3505 – Multivariate Statistics (Spring 2015, Fall 2016)**: This is a module I suggested to the Statistics group to be added to the curriculum. It had 15-20 students each semester when I taught it included a lecture each week in the lab as I was teaching modern multivariate statistical techniques and we were applying them to real datasets.**MA0263 – Computational Statistics****(Spring 2014, Spring 2015)**: This module was about teaching the undergraduate students to use statistical software to run some basic statistical methods. There were about 20-30 students in the module. There was a lecture in the lab every week to write code to run some of the statistical methodology we were developing. This is a module that was used to as a base to develop MA2501 that I am currently teaching and which includes teaching programming principles.**MA2002 – Matrix Algebra (Fall 2013, Fall 2014)**: A required second year module that had 140-160 students. The second time I taught it I added some interesting applications of Matrix Algebra in other areas of Mathematics and in Computing.

Michigan Technological University:

**MA5761 – Computational Statistics (Fall 2010, Fall 2011):**This was the first graduate course that I taught and it had 5-10 students each time, most of them studying for a Ph.D. in Mathematics/Statistics at MTU.**MA3710 – Introduction to Statistics for Engineers (Fall 2010, Spring 2011, Fall 2011, Spring 2012)**: The biggest service course the school was offering to Engineers. There were about 45-50 students every semester in this course.

Pennsylvania State University:

**STAT319 – Applied Statistics for Sciences (Fall 2006, Spring 2007, Spring 2008, Spring 2009, Spring 2010)**: This was a contunuation of STAT 318. It was for students not majoring in Statistics but needing some background to Probability and Statistics. I had students from Computer Science, Biology and other degree backgrounds in that module and it varied between 30-40 students. Classic lecture style computing**STAT318: Elementary Probability (Fall 2007, Fall 2008, Fall 2009)**: This was the first part of a series of two courses. It was for students not majoring in Statistics but needing some background to Probability and Statistics. I had students from Computer Science, Biology and other degree backgrounds in that module and it varied between 30-50 students.**STAT200 – Elementary Statistics (Summer 2006, Summer 2007, Summer 2008, Summer 2010)**: STAT200 was probably one of the biggest service course throughout the campus at Penn State. I taught it only in Summer terms and I had classes of 45 students. It consisted of fast paced 75-minute lecture every day for 6 weeks (2 out of the 5 days every week were lab meetings)