Computer Science

This course provides an introduction to computer programming and organization, using the Python programming language. With on-computer tools like PyCharm and online coding tools like Repl.it, students gain basic Python programming skills using libraries, such as Python’s PyGame graphics library. With fundamentals like data types, loop constructions, and knowledge of if/then logic mastered, the student works to program two to three games that involve on-screen motion and graphics. The games may vary, but programming a game such as Pong allows students to hone their skills and build more complex logic, more intricate subroutines, and more exciting results. Through this game design, the students will also gain additional experience handling strings and simple Python data structures like lists. In the final part of the course, the students jump into the world of microprogramming, where they can also use their growing Python programming knowledge. (No prior programming experience is expected or required)

This course takes a project-based approach to provide a rigorous introduction to the fundamentals of computer programming using the Java computer programming language. Java is an object-oriented programming language, and the basics of creating classes and objects in Java are provided. Students will be introduced to Java variables and control structures like if/then statements and program loops. Data structures such as arrays will be introduced. Students will use their programming skills to tackle challenges like sorting numbers, computing solutions to mathematical puzzles, and other projects. Animation basics such as frames, timers, and threads will also be introduced. A game, such as Pong, with animated graphics, will also be created. (Prerequisite: Computer Science II or Departmental permission)

Advanced Topics in Computer Science is a course for those students who have some programming experience and wish to do more. This yearlong Java programming course stresses above all an algorithmic approach and thinking like a computer scientist to solve programming problems. An algorithm can be looked at as a step-by-step plan, or method, to solve a problem. If the algorithm is efficient and clever, the plan can be implemented in code to solve hard problems like organizing vast sets of numbers, planning the shortest route through a complicated map, or playing chess. Developing the skill to create an efficient algorithm is a great aim for a student. The skill of thinking like a computer scientist can be applied in many other areas. In using an algorithmic approach, students can look carefully and critically at various solutions and pick the one that works “best.” Algorithmic solutions can be tested empirically by running programs for time (the fastest implementation wins) or by looking at them mathematically, such as by looking at the number of times the algorithm needs to run for a given set of data. The “Big O” (Order of N) analysis which analyzes the upper limit behavior of algorithms is just one way of classifying which algorithm works “best.” The study of data structures goes hand-in-hand with work in designing algorithms, so Advanced Topics in Computer Science will give students experience in developing programs with data structures such as graphs, maps, and trees. Concepts such as breadth/depth first search, game theory, vision, and recursion will be explored in exercises and in larger projects. Students will focus on larger programming projects. Special topics such as web scraping or phone application building may be explored, based on student interests. (Prerequisites: Java II or equivalent programming experience and permission from the Department)