The rapid advancement of artificial intelligence (AI) is transforming the way we work, interact, and make decisions. AI is integrated into applications and devices that are woven into our daily lives. How does AI work? What impact will AI have on individuals, communities, and our global society?

This course aims to provide students with the knowledge and skills to become informed digital citizens in the age of AI, ready to navigate the digital landscape. Students will gain fundamental technical understanding of how computers, the Web, and AI work, and will study three programming languages: HTML5, CSS, and JavaScript. Students will also examine and discuss societal and ethical issues related to the Web and AI technologies, and consider responsible and future use of these technologies.

An introduction to problem-solving through computer programming. Students learn how to read, modify, design, debug, and test algorithms that solve problems. Programming concepts include control structures, data structures, abstraction, recursion, and modularity. Students explore these concepts in the context of interactive programs, data processing, and graphics or audio, using the Python programming language.

Students are required to attend an additional two-hour laboratory section each week.

Video games are a popular form of interactive media that engage players in dynamic experiences through unprecedented combinations of storytelling, visualization, interactivity, and multi-sensory immersion. This course will introduce students to video game production and concepts. We will develop a framework for critically analyzing this medium, learn to identify effective strategies for creating games and describe what elements of design impact the final experience of a game. We’ll also identify the function of user agency in this medium to better understand how players are affected by representation in video games. Throughout the course, students will be asked to apply these concepts while building their own games and become familiar with the fundamentals of video game design.

Human-Computer Interaction is one of the areas that have transformed the way we use computers in the last 30 years. Topics include methodology for designing and testing user interfaces, interaction styles (command line, menus, graphical user interfaces, virtual reality, tangible user interfaces), interaction techniques (including use of voice, gesture, eye movements), design guidelines, and user interface software tools. Students will design a user interface, program a prototype, and test the results for usability.

An introduction to techniques and building blocks for organizing large programs. Topics include: modules, abstract data types, recursion, algorithmic efficiency, and the use and implementation of standard data structures and algorithms, such as lists, trees, graphs, stacks, queues, priority queues, tables, sorting, and searching. Students become familiar with these concepts through weekly programming assignments using the Java programming language. 

This course has a required co-requisite lab - CS 230L.

A student is required to have confirmation of authorization from the CS 111 faculty that is based on the mastery of the CS 111 concepts in order to enroll in CS 230. Students who did not take CS 111 at Wellesley and who wish to enroll in CS 230 should contact the CS department to take a placement questionnaire.

Accompanying required laboratory for CS 230.

The grading option chosen for the lecture (CS 230) - either Letter Grade or Credit/Non Credit - will apply to the lab as well; the final grade is a single unified grade for both lecture and lab and is based on the grading option you choose for the lecture.

An introduction to techniques and building blocks for organizing large programs. Topics include: modules, abstract data types, recursion, algorithmic efficiency, and the use and implementation of standard data structures and algorithms, such as lists, trees, graphs, stacks, queues, priority queues, tables, sorting, and searching. Students become familiar with these concepts through *additional self-driven weekly programming practice using the Java programming language.

Students are required to attend an additional two-hour laboratory section each week. CS 230P is open to all students who did not meet the prerequisites for CS 230, or for students who took CS 111 before the last semester, or students who would appreciate additional academic support because of their prior MATH and CS experience. Class meetings are followed by a 30-minutes practice session to provide for extra time to work with the instructor after class.

Students who wish to enroll in CS 230P must enroll in a lecture and an accompanying laboratory.

This is a required co-requisite laboratory for CS 230P.

The grading option chosen for the lecture (CS 230P) - either Letter Grade or Credit/Non Credit - will apply to the lab as well; the final grade is a single unified grade for both lecture and lab and is based on the grading option you choose for the lecture.

An introduction to techniques and building blocks for organizing large programs. Topics include: modules, abstract data types, recursion, algorithmic efficiency, and the use and implementation of standard data structures and algorithms, such as lists, trees, graphs, stacks, queues, priority queues, tables, sorting, and searching. Students become familiar with these concepts through weekly programming assignments using the Java programming language.

CS230X is intended for students with significant prior experience in Java programming as demonstrated by a 5 in CS AP A, or equivalent demonstration of experience. Students in this section will complete self-directed weekly labs. If you did not take the CS AP A exam and would like to take this class, you may take the CS placement questionnaire to see if you qualify.

Enrollment in this course is by permission of the instructor only. Students interested in taking this course should fill out this Google Form prior to registration.

This course offers an introduction to the theory of computation. Topics include languages, regular expressions, finite automata, grammars, pushdown automata, and Turing machines. The first part of the course covers the Chomsky hierarchy of languages and their associated computational models. The second part of the course focuses on decidability issues and unsolvable problems. The final part of the course investigates complexity theory.

This course examines how computers run programs, introducing key software and hardware abstractions and implementations between programming languages and transistors. The course traces representation and translation of data and programs through three broad topics in computer systems: computer hardware implementation, including digital logic, computer arithmetic, and machine organization; the hardware-software interface, including instruction set architecture, assembly code, and the C programming language; and abstractions for practical systems, including the physical memory hierarchy, the operating system process model, virtual memory, and memory management. Students complete extensive hands-on projects in hardware and software systems. Students are required to attend one three-hour laboratory weekly.

Accompanying required laboratory for CS 240.

The grading option chosen for the lecture (CS 240) - either Letter Grade or Credit/Non Credit - will apply to the lab as well; the final grade is a single unified grade for both lecture and lab and is based on the grading option you choose for the lecture.

Accompanying required laboratory for CS 240.

The grading option chosen for the lecture (CS 240) - either Letter Grade or Credit/Non Credit - will apply to the lab as well; the final grade is a single unified grade for both lecture and lab and is based on the grading option you choose for the lecture.

CS 304 is a course in full-stack web development. The stack comprises the front-end (typically a web browser), the back-end (a database for storing and retrieving user-contributed data) and the middleware that knits the two together. We will learn how to parse the incoming web request, route the request to the appropriate handler, retrieve data from the database that is relevant to the user's search, combine that data with static templates of web pages, and deliver that data to the browser. We will build endpoints to handle Ajax requests and learn about REST APIs.  We will also discuss performance, reliability,  concurrency, and security issues. In a semester project, we will create dynamic websites driven by database entries. In the fall, the CS 304 stack will comprise Flask and MySQL. In the spring, the CS 304 stack will comprise Node.js and MongoDB.

In recent years, Artificial Intelligence has enabled applications that were previously not thought possible—from systems that propose novel drugs or generate new art/music, to systems that accurately and reliably predict outcomes of medical interventions in real-time. But what has enabled these developments? Probabilistic Machine Learning, a paradigm that casts recent advances in Machine Learning, like neural networks, into a statistical learning framework. In this course, we introduce the foundational concepts behind this paradigm—statistical model specification, and statistical learning and inference—focusing on connecting theory with real-world applications and hands-on practice. This course lays the foundation for advanced study and research in Machine Learning. Topics include: directed graphical models, deep Bayesian regression/classification, generative models (latent variable models) for clustering, dimensionality reduction, and time-series forecasting. Students will get hands-on experience building models for specific tasks ,most taken from healthcare contexts, using a probabilistic programming language based in Python.

Enrollment in this course is by permission of the instructor only. Students interested in taking this course should fill out this google form prior to registration.

Human-Computer Interaction is one of the areas that have transformed the way we use computers in the last 30 years. Topics include methodology for designing and testing user interfaces, interaction styles (command line, menus, graphical user interfaces, virtual reality, tangible user interfaces), interaction techniques (including use of voice, gesture, eye movements), design guidelines, and user interface software tools. Students will design a user interface, program a prototype, and test the results for usability.

An introduction to problem-solving through computer programming. Students learn how to read, modify, design, debug, and test algorithms that solve problems. Programming concepts include control structures, data structures, abstraction, recursion, and modularity. Students explore these concepts in the context of interactive programs, data processing, and graphics or audio, using the Python programming language.

Students are required to attend an additional two-hour laboratory section each week.

If you have been previously waitlisted for CS 111, you will be prioritized during initial registration in November. If you have not been previously waitlisted, add yourself to the waitlist during initial registration. During registration changes period (in January 2024), waitlisted students will be offered seats, subject to availability. Students must add themselves to the Workday waitlist; faculty do not have the ability to add students to the Workday waitlist.

[Registration as of 1/22/24] This course is currently full and the Workday waitlist is closed. If a spot becomes available during the add period a student from the (now closed) waitlist will be contacted by course faculty and allowed to register by permission of instructor (POI). Students on the Spring 2024 waitlist will be given priority status for initial Fall 2024 registration; note that this priority does not guarantee a seat in the class.

An introduction to problem-solving through computer programming. Students learn how to read, modify, design, debug, and test algorithms that solve problems. Programming concepts include control structures, data structures, abstraction, recursion, and modularity. Students explore these concepts in the context of interactive programs, data processing, and graphics or audio, using the Python programming language.

Students are required to attend an additional two-hour laboratory section each week.

If you have been previously waitlisted for CS 111, you will be prioritized during initial registration in November. If you have not been previously waitlisted, add yourself to the waitlist during initial registration. During registration changes period (in January 2024), waitlisted students will be offered seats, subject to availability. Students must add themselves to the Workday waitlist; faculty do not have the ability to add students to the Workday waitlist.

[Registration as of 1/22/24] This course is currently full and the Workday waitlist is closed. If a spot becomes available during the add period a student from the (now closed) waitlist will be contacted by course faculty and allowed to register by permission of instructor (POI). Students on the Spring 2024 waitlist will be given priority status for initial Fall 2024 registration; note that this priority does not guarantee a seat in the class.

Video games are a popular form of interactive media that engage players in dynamic experiences through unprecedented combinations of storytelling, visualization, interactivity, and multi-sensory immersion. This course will introduce students to video game production and concepts. We will develop a framework for critically analyzing this medium, learn to identify effective strategies for creating games and describe what elements of design impact the final experience of a game. We’ll also identify the function of user agency in this medium to better understand how players are affected by representation in video games. Throughout the course, students will be asked to apply these concepts while building their own games and become familiar with the fundamentals of video game design.

An introduction to techniques and building blocks for organizing large programs. Topics include: modules, abstract data types, recursion, algorithmic efficiency, and the use and implementation of standard data structures and algorithms, such as lists, trees, graphs, stacks, queues, priority queues, tables, sorting, and searching. Students become familiar with these concepts through weekly programming assignments using the Java programming language. 

Students are required to attend an additional two-hour laboratory section each week.

A student is required to have confirmation of authorization from the CS111 faculty that is based on the mastery of the CS111 concepts in order to enroll in CS230. If you did not take CS111 and wish to enroll, please contact the CS230 team.

[Registration as of 1/22/24] This course is currently full and the Workday waitlist is closed. If a spot becomes available during the add period, a student from the (now closed) waitlist will be contacted by course faculty and allowed to register by permission of instructor (POI). 

An introduction to techniques and building blocks for organizing large programs. Topics include: modules, abstract data types, recursion, algorithmic efficiency, and the use and implementation of standard data structures and algorithms, such as lists, trees, graphs, stacks, queues, priority queues, tables, sorting, and searching. Students become familiar with these concepts through weekly programming assignments using the Java programming language. 

Students are required to attend an additional two-hour laboratory section each week.

A student is required to have confirmation of authorization from the CS111 faculty that is based on the mastery of the CS111 concepts in order to enroll in CS230. If you did not take CS111 and wish to enroll, please contact the CS230 team.

[Registration as of 1/22/24] This course is currently full and the Workday waitlist is closed. If a spot becomes available during the add period, a student from the (now closed) waitlist will be contacted by course faculty and allowed to register by permission of instructor (POI). 

Accompanying required laboratory for CS 230.

Accompanying required laboratory for CS 230.

An introduction to the design and analysis of fundamental algorithms. General techniques covered: divide-and-conquer algorithms, dynamic programming, greediness, probabilistic algorithms. Topics include: sorting, searching, graph algorithms, compression, cryptography, computational geometry, and NP-completeness.

This course offers an introduction to the theory of computation. Topics include languages, regular expressions, finite automata, grammars, pushdown automata, and Turing machines. The first part of the course covers the Chomsky hierarchy of languages and their associated computational models. The second part of the course focuses on decidability issues and unsolvable problems. The final part of the course investigates complexity theory.

CS 304 is a course in full-stack web development. The stack comprises the front-end (typically a web browser), the back-end (a database for storing and retrieving user-contributed data) and the middleware that knits the two together. We will learn how to parse the incoming web request, route the request to the appropriate handler, retrieve data from the database that is relevant to the user's search, combine that data with static templates of web pages, and deliver that data to the browser. We will build endpoints to handle Ajax requests and learn about REST APIs.  We will also discuss performance, reliability,  concurrency, and security issues. In a semester project, we will create dynamic websites driven by database entries. In the fall, the CS 304 stack will comprise Flask and MySQL. In the spring, the CS 304 stack will comprise Node.js and MongoDB.

In the past decade, we have experienced the rise of socio-technical systems used by millions of people: Google, Facebook, Twitter, Wikipedia, etc. Such systems are on the one hand computational systems, using sophisticated infrastructure and algorithms to organize huge amount of data and text, but on the other hand social systems, because they cannot succeed without human participation. How are such systems built? What algorithms underlie their foundations? How does human behavior influence their operation and vice-versa? In this class, we will delve into answering these questions by means of: a) reading current research papers on the inner-workings of such systems; b) implementing algorithms that accomplish tasks such as web crawling, web search, random walks, learning to rank, text classification, topic modeling; and c) critically thinking about the unexamined embrace of techno-solutionism using a humanistic lens.

Enrollment in CS 315 is by permission of the instructor only. Interested students should fill out this Google Form.

Tangible user interfaces emerge as a novel human-computer interaction style that interlinks the physical and digital worlds. Extending beyond the limitations of the computer mouse, keyboard, and monitor, tangible user interfaces allow users to take advantage of their natural spatial skills while supporting collaborative work. Students will be introduced to conceptual frameworks, the latest research, and a variety of techniques for designing and building these interfaces. Developing tangible interfaces requires creativity as well as an interdisciplinary perspective. Hence, students will work in teams to design, prototype, and physically build tangible user interfaces.

Social Computing systems connect us to our closest friends, and globally to people all over the world. In recent decades, companies like Facebook, Snapchat, and even Amazon, have reshaped our social environments. All of these systems, at their core, are designed to facilitate interactions between people. What design decisions shape these systems? Students will learn the theoretical foundations of Social Computing drawn from the Social Sciences, and will learn software prototyping and design techniques to create new systems. This class will explore topics such as identity, anonymity, reputation, moderation, crowdsourcing, and social algorithms. Students will work in teams to design, prototype, and build social computing systems.

What is the “cloud”? What is a distributed system? This course is for students interested in understanding the fundamental concepts and algorithms underlying existing distributed systems. By the end of this course, students will have the basic knowledge needed to work with and build distributed systems, such as peer-to-peer systems and cloud computing systems. Topics include MapReduce, Spark, communication models, synchronization, distributed file systems, coordination algorithms, consensus algorithms, fault-tolerance, and security.

Enrollment in this course is by permission of the instructor only. Interested students should fill out this Google Form.