Page 166 - University Bulletin

ASDS413 Design and Analysis of Experiments
Credits: 3 (3,1,0) Prerequisite: STAT111 and ASDS321
The main objectives of the course are to deal with basic statistics, design of experiments,
uncertainty and error analysis, general characteristics of measurement systems, statistical analysis
of experimental data, empirical modeling, experimental uncertainty analysis, as well as guidelines
for planning and documenting experiments.

ASDS429 Digital Image Processing
Credits: 3 (3,0,0) Prerequisite: ASDS213
This course includes topics like image sampling and quantization, colour, point operations,
segmentation, morphological image processing, linear image filtering, image transforms, noise
reduction, restoration, compression, feature extraction and recognition tasks. Students learn to
apply material by implementing and investigating image processing algorithms in Python.

ASDS433 Data Visualization
Credits: 3 (3,1,0) Prerequisite: ASDS225
This course provides a comprehensive introduction to data visualization principles and techniques,
tailored for students in applied statistics and data science. Emphasizing the importance of
effectively communicating data-driven insights, the course explores key topics such as visual
perception, chart selection, interactive dashboards, and storytelling with data. Students will learn
to create compelling visualizations using tools like Tableau, Power BI, and Python libraries (e.g.,
Matplotlib, …). Through hands-on projects, they will practice transforming raw data into
meaningful graphics while adhering to best practices in design and ethics. By the end of the course,
students will be able to present complex information clearly and persuasively to diverse
audiences.

ASDS450 Ethical and Social Aspects of Analysts
Credits: 3 (3,0,0) Prerequisite: ASDS311
The course concentrates on the theory and practice of statistics and data science ethics. It covers
the basics of ethical decision-making and emphasizes group work and presentations. Topics
studied in the course include risk and reliability, privacy, info-war, crime, access, business ethics,
copyright, patents, and more.

ASDS490 Capstone Project
Credits: 3 (3,0,0) Prerequisite: ASDS381
This is a capstone project course; the students work in teams to accomplish the learning outcomes
under supervision of a faculty advisor.

ASDS493 Cooperative Education
Credits: 10 (10,0,0) Prerequisite: Department Approval
The aim of this course is to provide students with the opportunity to spend a specified period of
time in local or international companies and institutions, and according to a suggested work plan
of training. The duration of the training is 7 months and carries a 10 credit hours weight. The
evaluation and supervision of the student’s performance is carried out by both the hosting
workplace and the relevant department. Emphasis will be placed on the application of theoretical
knowledge in real-world settings, helping students refine their skills in teamwork, communication,
and project management. By actively participating in cooperative learning environments, students
will gain valuable industry insights, expand their professional network, and enhance their
problem-solving capabilities in the dynamic field of language and media.

154 PSU UNDERGRADUATE BULLETIN