Joshua Palicka


Hi! I'm a Computer Science professional with an M.S. in Computer Science from Seattle University with Data Science Proficiency. My skillset includes multiple programming languages, machine learning, AI, software design, data structures, and algorithms.

I'm currently seeking a data science career opportunity after I graduate in June and am eager to join a dynamic team and contribute my skills and passion. If you know of any open positions, please feel free to reach out. I look forward to making a meaningful impact in the data science community!

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Teaching Assistant


As a dedicated student and aspiring professional, I have taken the initiative to expand my learning experiences beyond the classroom. One such opportunity has been my role as a Teaching Assistant (TA) for four different courses: Fundamentals of Databases, Introduction to Data Science, Machine Learning, and Artificial Intelligence. Through this experience, I have been able to not only support students in their academic journeys but also further develop my own knowledge and skills in these subjects. My responsibilities as a TA have included grading assignments, providing guidance during office hours, and offering valuable feedback on student projects. This page showcases my TA experience, highlighting the background, course details, collaboration, and outcomes associated with my work in this capacity.


I began my journey as a Teaching Assistant in Winter of the 2021-2022 school year. After completing the Introduction to Data Science course in Fall 2021, my professor offered me the opportunity to be her TA for the undergraduate Fundamentals of Databases course the following quarter. Since then, I have continued to serve as one of her TAs every quarter.

My success as a TA can be partially attributed to my ability to educate others, which I have developed over the years through helping people with tech support in my free time. Additionally, my strong time management skills and ability to plan ahead have enabled me to balance my academic responsibilities with my TA work, ensuring that I can effectively support students while maintaining my own academic success.

Course Details

Fundamentals of Databases (CPSC 3300)

Fundamentals of Databases is an undergraduate course designed to introduce students to the design and use of database systems. The course covers the fundamental principles governing database management system design and operation, including the entity-relationship (ER) approach, the relational model, SQL, and the internal mechanisms of database management systems. Students learn how the ER model is expressed as relations and how to use a relational database system to create a database. Additionally, the course explores files, storage, and indexing structures in database systems.

As a TA for this course, I found the challenge of optimizing complex SQL queries to be a valuable learning experience, even though it wasn’t a frequent task. This helped me develop my problem-solving skills and further deepened my understanding of SQL and database systems.

Introduction to Data Science (CPSC 5305)

Introduction to Data Science is a foundational course that provides students with an overview of the field, the methodology for identifying, defining, and solving data-intensive problems, and operationalizing solutions. The course exposes students to common problems and technologies in both the analytic and systems areas within the field, while offering hands-on experience with popular tools and techniques. Additionally, the course delves into the ethical, privacy, and security implications of building data-intensive applications.

As a TA for this course, I found it particularly interesting to review and provide feedback on students’ group projects. Observing the diverse approaches and creative solutions students developed allowed me to gain new perspectives and insights into real-world data science applications.

Machine Learning (CPSC 4310)

Machine Learning is a comprehensive course that offers a broad introduction to the foundations, concepts, and algorithms of machine learning, as well as their applications in analyzing massive amounts of data for decision-making and prediction purposes. Students are expected to apply machine learning techniques to solve real-world problems in research or industry applications. Topics covered include model parameter learning, evaluation metrics, supervised learning, unsupervised learning, learning theory, and performance improvement.

As a TA for this course, as with 5305, I found it particularly engaging to review and provide feedback on students’ machine learning projects. Observing their innovative applications of machine learning concepts and techniques not only helped me gain insight into the potential of machine learning in real-world scenarios but also reinforced my understanding of the subject matter.

Artificial Intelligence (CPSC 4610 & 5610)

Artificial Intelligence is a dynamic field in computer science and engineering, characterized by various applications, active research domains, and a wide range of tools and problems. In this course, students gain an understanding of AI concepts and techniques, with an emphasis on building intelligent agents, environments, and systems. The curriculum explores use cases and applications of AI, as well as methods and tools for building AI systems for various applications. Students also have the opportunity to demonstrate AI in action through hands-on projects.

As a TA for this course, I found it particularly challenging to help students with their work on the Berkeley Pacman Project, a standard part of the Seattle University AI curriculum. This project, which I found difficult during my own studies, involves implementing AI algorithms to control Pacman’s actions in various game scenarios. Revisiting this project and observing the students’ perspectives on problem-solving not only helped me solidify my understanding of AI concepts but also provided valuable insights into the thought processes of other students, so that I could learn from their approaches.


Throughout my TA experience, collaboration has played a vital role in ensuring the success of both students and the courses I’ve supported. Working with the professor has allowed me to better understand her expectations and the course objectives, enabling me to provide more effective guidance to students. Coordinating with other TAs has helped create a supportive environment where we can share insights and work together to improve the overall learning experience for students.

During my virtual office hours, I have had the opportunity to directly support and guide students as they navigate through course material and tackle assignments. This one-on-one interaction has not only enhanced my communication and teaching skills but also provided feedback on students’ progress and areas where they may need further clarification or assistance.

Overall, my collaborative experiences as a TA have fostered a strong sense of teamwork and commitment to the success of the students in the courses I have been a part of.


Through my experience as a Teaching Assistant, I have seen multiple benefits, both for the students I have supported and for my own personal and professional growth:

Overall, my experience as a Teaching Assistant has been instrumental in shaping my personal and professional development, while also positively impacting the academic experiences of the students I have supported.