Course Listing

For a snapshot of courses being offered by Harvard School of Engineering over the next four years, visit our Multi Year Course Planning tool.

Discrete Mathematics for Computer Science

COMPSCI 20
2024 Spring

Rebecca Nesson, Michael Mitzenmacher
Monday, Wednesday, Friday
9:45am to 11:00am

Widely applicable mathematical tools for computer science, including topics from logic, set theory, combinatorics, number theory, probability theory, and graph theory. Practice in reasoning formally and proving theorems.

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Computational Thinking and Problem Solving

COMPSCI 32
2024 Spring

Michael Smith
Monday, Wednesday
12:45pm to 2:00pm

An introduction to computational thinking, useful concepts in the field of computer science, and the art of computer programming using Python. Significant emphasis is placed on class meetings and learning to use computers to solve complex, real-world problems. Concepts and techniques are introduced as they are needed to help solve the problems confronting us. Students will learn how to go from an ambiguous problem description to a running solution and will leave the class knowing how to instruct computers to do what they want them to do. Prior experience in computer science or computer programming is not necessary.

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Introduction to Computer Science

COMPSCI 50
2024 Spring

David J. Malan, Carter Zenke
Tuesday
3:45pm to 6:30pm

This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches you how to solve problems, both with and without code, with an emphasis on correctness, design, and style. Topics include computational thinking, abstraction, algorithms, data structures, and computer science more generally. Problem sets inspired by the arts, humanities, social sciences, and sciences. More than teach you how to program in one language, this course teaches you how to program fundamentally and how to teach yourself new languages ultimately. The course starts with a traditional but omnipresent language called C that underlies today's newer languages, via which you'll learn not only about functions, variables, conditionals, loops, and more, but also about how computers themselves work underneath the hood, memory and all. The course then transitions to Python, a higher-level language that you'll understand all the more because of C. Toward term's end, the course introduces SQL, via which you can store data in databases, along with HTML, CSS, and JavaScript, via which you can create web and mobile apps alike. Course culminates in a final project. See https://cs50.harvard.edu/spring for advice, FAQs, syllabus, and what's new. Email the course's heads at heads@cs50.harvard.edu with questions.

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Introduction to Computer Science

COMPSCI 50
2024 Spring

David J. Malan, Carter Zenke
Tuesday
9:00am to 11:45am

This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches you how to solve problems, both with and without code, with an emphasis on correctness, design, and style. Topics include computational thinking, abstraction, algorithms, data structures, and computer science more generally. Problem sets inspired by the arts, humanities, social sciences, and sciences. More than teach you how to program in one language, this course teaches you how to program fundamentally and how to teach yourself new languages ultimately. The course starts with a traditional but omnipresent language called C that underlies today's newer languages, via which you'll learn not only about functions, variables, conditionals, loops, and more, but also about how computers themselves work underneath the hood, memory and all. The course then transitions to Python, a higher-level language that you'll understand all the more because of C. Toward term's end, the course introduces SQL, via which you can store data in databases, along with HTML, CSS, and JavaScript, via which you can create web and mobile apps alike. Course culminates in a final project. See https://cs50.harvard.edu/spring for advice, FAQs, syllabus, and what's new. Email the course's heads at heads@cs50.harvard.edu with questions.

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Introduction to Computer Science

COMPSCI 50
2024 Spring

David J. Malan, Carter Zenke
Wednesday
9:00am to 11:45am

This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches you how to solve problems, both with and without code, with an emphasis on correctness, design, and style. Topics include computational thinking, abstraction, algorithms, data structures, and computer science more generally. Problem sets inspired by the arts, humanities, social sciences, and sciences. More than teach you how to program in one language, this course teaches you how to program fundamentally and how to teach yourself new languages ultimately. The course starts with a traditional but omnipresent language called C that underlies today's newer languages, via which you'll learn not only about functions, variables, conditionals, loops, and more, but also about how computers themselves work underneath the hood, memory and all. The course then transitions to Python, a higher-level language that you'll understand all the more because of C. Toward term's end, the course introduces SQL, via which you can store data in databases, along with HTML, CSS, and JavaScript, via which you can create web and mobile apps alike. Course culminates in a final project. See https://cs50.harvard.edu/spring for advice, FAQs, syllabus, and what's new. Email the course's heads at heads@cs50.harvard.edu with questions.

Course Website

Introduction to Computer Science

COMPSCI 50
2024 Spring

David J. Malan, Carter Zenke
Wednesday
6:00pm to 8:45pm

This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches you how to solve problems, both with and without code, with an emphasis on correctness, design, and style. Topics include computational thinking, abstraction, algorithms, data structures, and computer science more generally. Problem sets inspired by the arts, humanities, social sciences, and sciences. More than teach you how to program in one language, this course teaches you how to program fundamentally and how to teach yourself new languages ultimately. The course starts with a traditional but omnipresent language called C that underlies today's newer languages, via which you'll learn not only about functions, variables, conditionals, loops, and more, but also about how computers themselves work underneath the hood, memory and all. The course then transitions to Python, a higher-level language that you'll understand all the more because of C. Toward term's end, the course introduces SQL, via which you can store data in databases, along with HTML, CSS, and JavaScript, via which you can create web and mobile apps alike. Course culminates in a final project. See https://cs50.harvard.edu/spring for advice, FAQs, syllabus, and what's new. Email the course's heads at heads@cs50.harvard.edu with questions.

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Abstraction and Design in Computation

COMPSCI 51
2024 Spring

Stuart Shieber
Tuesday, Thursday
12:45pm to 2:00pm

Fundamental concepts in the design of computer programs, emphasizing the crucial role of abstraction. The goal of the course is to give students insight into the difference between programming and programming well. To emphasize the differing approaches to expressing programming solutions, you will learn to program in a variety of paradigms -- including functional, imperative, and object-oriented. Important ideas from software engineering and models of computation will inform these different views of programming.

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Abstraction and Design in Computation

COMPSCI 51
2024 Spring

Stuart Shieber
Tuesday, Thursday
3:45pm to 5:00pm

Fundamental concepts in the design of computer programs, emphasizing the crucial role of abstraction. The goal of the course is to give students insight into the difference between programming and programming well. To emphasize the differing approaches to expressing programming solutions, you will learn to program in a variety of paradigms -- including functional, imperative, and object-oriented. Important ideas from software engineering and models of computation will inform these different views of programming.

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Case Studies in Public and Private Policy Challenges of Artificial Intelligence

COMPSCI 90NDR
2024 Spring

Jonathan Zittrain
Monday, Tuesday
3:45pm to 5:15pm

The use of machine learning has skyrocketed in recent years, becoming embedded retail and wholesale across society without substantial reflection on its implications. Through engagement with those building some of the most provocative models and tools – many of which have become part of the public imagination – we will see what gives their builders pause; reflect on possible solutions or mitigations; and develop suggestions about what they might be missing in their own canvassing of the ethical and policy terrain.

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Supervised Reading and Research

COMPSCI 91R
2024 Spring

Stephen Chong, Adam Hesterberg

Supervised individual study of advanced topics in computer science. A student wishing to enroll in Computer Science 91r must be accepted by a faculty member who will supervise the course work. Additional information and a form are available via https://harvardcs.info/forms/#cs-91r-form. The form must be filled out and signed by the student and faculty supervisor. Students writing theses may enroll in this course while conducting thesis research and writing.

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Data Science 2: Advanced Topics in Data Science

COMPSCI 109B
2024 Spring

Pavlos Protopapas, Alex Young
Monday, Wednesday, Friday
9:45am to 11:00am

Data Science 2 is the second half of a one-year introduction to data science. Building upon the material in Data Science 1, the course introduces advanced methods for statistical modeling, representation, and prediction. Topics include multiple deep learning architectures such as CNNs, RNNs, transformers, language models, autoencoders, and generative models as well as basic Bayesian methods, and unsupervised learning. Students are strongly encouraged to enroll in both the fall and spring course within the same academic year. Part two of a two-part series.

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Data Structures and Algorithms

COMPSCI 124
2024 Spring

Madhu Sudan, Sitan Chen
Monday, Wednesday
2:15pm to 3:30pm

Design and analysis of efficient algorithms and data structures. Algorithm design methods, graph algorithms, approximation algorithms, and randomized algorithms are covered.

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Convex Optimization and Applications in Machine Learning

COMPSCI 128
2024 Spring

Yiling Chen
Monday, Wednesday
9:45am to 11:00am

This course focuses on recognizing, formulating, and solving convex optimization problems. We will introduce basic convex analysis, discuss convex optimization theory, introduce algorithms for solving convex optimization problems, and touch on some advanced topics. We will explore all these in the context of machine learning applications as almost every machine learning problem can be formulated as an optimization problem. The objective is to give students the theoretical training to recognize and formulate convex optimization problems and provide students with the tools and methods to solve the problems of interest.

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Computing Hardware

COMPSCI 141
2024 Spring

Vijay Janapa Reddi
Monday, Wednesday
11:15am to 12:30pm

This course introduces fundamentals in designing and building modern information devices and systems that interface with the real world. It focuses on digital devices and systems, and it complements ENG-SCI 152, which focuses on devices and systems that use analog electronics. Topics include: combinational and sequential logic; computer architecture; machine code; and altogether the infrastructure and computational framework composing a MIPS processor. Consideration is given in design to interactions between hardware and software systems. Students will design application specific hardware for an embedded system.

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Networking at Scale

COMPSCI 145
2024 Spring

Minlan Yu
Tuesday, Thursday
9:45am to 11:00am

This course studies computer network topics including Layer 2/Layer 3 topology, routing, transport protocols, traffic engineering, network functions, programmable switches, and software-defined networking. Modern networks have grown to large scale (connecting millions of servers) and high speed (terabits per second) to meet the needs of cloud applications in business and society. Thus, in addition to learning the conventional concepts in networking, we will also discuss how to adapt these concepts to large-scale networks. These discussions will hopefully help deepen our understanding of networking technologies. This course includes lectures and system programming projects. More information can be found at https://github.com/minlanyu/cs145-site.

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Computer Architecture

COMPSCI 146
2024 Spring

David Brooks
Friday
9:00am to 11:45am

Review of the fundamental structures in modern processor design. Topics include computer organization, memory system design, pipelining, and other techniques to exploit parallelism. Discussion of modern topics including GPU architectures, datacenter architecture, mobile/embedded SoC architectures, and machine learning acceleration as time permits. Emphasis on a quantitative evaluation of design alternatives and an understanding of performance and energy consumption issues.

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Design of VLSI Circuits and Systems

COMPSCI 148
2024 Spring

Gage Hills
Monday, Wednesday
2:15pm to 3:30pm

Presentation of concepts and techniques for the design and fabrication of VLSI systems and digital MOS integrated circuits. Topics include: basic semiconductor theory; MOS transistors and digital MOS circuits design; synchronous machines, clocking, and timing issues; high-level description and modeling of VLSI systems; synthesis and place and route design flows; and testing of VLSI circuits and systems. Various CAD tools for design, simulation, and verification are extensively used.

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Programming Languages

COMPSCI 152
2024 Spring

Nada Amin
Tuesday, Thursday
11:15am to 12:30pm

Comprehensive introduction to the principal features and overall design of both traditional and modern programming languages, including syntax, formal semantics, abstraction mechanisms, modularity, type systems, naming, polymorphism, closures, continuations, and concurrency. Provides the intellectual tools needed to design, evaluate, choose, and use programming languages.

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Operating Systems

COMPSCI 161
2024 Spring

Eddie Kohler
Monday, Wednesday
2:15pm to 3:30pm

This course focuses on the design and implementation of modern operating systems. The course discusses threads, processes, virtual memory, schedulers, and the other fundamental primitives that an OS uses to represent active computations. An exploration of the system call interface explains how applications interact with hardware and other programs which are concurrently executing. Case studies of popular file systems reveal how an OS makes IO efficient and robust in the midst of crashes and unexpected reboots. Students also learn how virtualization allows a physical machine to partition its resources across multiple virtual machines. Class topics are reinforced through a series of intensive programming assignments which use a real operating system.

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Computer Graphics

COMPSCI 175
2024 Spring

Steven Gortler
Tuesday, Thursday
12:45pm to 2:00pm

This course covers the fundamentals of 3D computer graphics using a modern shader-based version of OpenGL. Main topics include: geometric coordinate systems and transformations, keyframe animation and interpolation, camera simulation, triangle rasterization, material simulation, texture mapping, image sampling and color theory. The course also touches on ray tracing, geometric modeling and simulation-based animation.

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Engineering Usable Interactive Systems

COMPSCI 178
2024 Spring

Elena Glassman
Monday, Wednesday
3:45pm to 5:00pm

In this course, students learn critical techniques, concepts, and technologies for building usable interactive systems, alone and in pairs. Assignments provide hands-on experiences with different modern frameworks, platforms, and libraries while conceptual commonalities and distinctions are annotated and explained. Lectures cover relevant basic and advanced topics, such as human cognitive capabilities, iterative prototyping, and human-AI interaction. The final project will require both front-end and back-end development, iterative prototyping with humans, and a final evaluation with target users. Designed for advanced undergraduates.

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Machine Learning

COMPSCI 181
2024 Spring

Finale Doshi-Velez, David Alvarez Melis
Tuesday, Thursday
9:45am to 11:00am

Introduction to machine learning, providing a probabilistic view on artificial intelligence and reasoning under uncertainty. Topics include: supervised learning, ensemble methods and boosting, neural networks, support vector machines, kernel methods, clustering and unsupervised learning, maximum likelihood, graphical models, hidden Markov models, inference methods, and computational learning theory. Students should feel comfortable with multivariate calculus, linear algebra, probability theory, and complexity theory. Students will be required to produce non-trivial programs in Python.

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Classics of Computer Science

COMPSCI 191
2024 Spring

Harry Lewis
Tuesday, Thursday
2:15pm to 3:30pm

Papers every computer scientist should have read, from all areas of the field and dating from its origins to the present.

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Designing K–12 Computer Science Learning Experiences

COMPSCI 196
2024 Spring

Karen Brennan
Wednesday
9:00am to 11:45am

From computational thinking to workforce arguments, there is considerable interest in and excitement about including computer science education for all K–12 students. Yet, unlike other disciplines with a much longer history in formal schooling, the interest in computer science education is not yet supported by commensurate attention to research and teacher practice. In this course, we will examine the state of K–12 computing education: questioning its value, examining its history, and imagining and contributing to its potential. The course will be organized as both a reading group and a lab, building a community of people who are committed to K–12 CS education. Each week you will read classic and current research, and write accompanying memos to document your evolving understandings of the field. Throughout the course, either individually or with partners, you will develop an independent project that explores the design of K–12 computer science learning experiences. Some examples of possible projects include: designing CS-standalone or cross-curricular learning activities and curriculum, building a programming language for novices, developing an annotated bibliography, critically analyzing policy documents such as curriculum frameworks and standards from around the world, or contributing to current K–12 CS education research initiatives.

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High Performance Computing for Science and Engineering

COMPSCI 205
2024 Spring

Ignacio Becker Troncoso, Boris Kozinsky
Tuesday, Thursday
2:15pm to 3:30pm

With manufacturing processes reaching the limits in terms of transistor density on today’s computing architectures, efficient modern code must exploit parallel execution to maintain scaling of available hardware resources. The use of computers in academia, industry and society is a fundamental tool for solving (scientific) problems while the "think parallel" mindset of code developers is still lagging behind. The aim of this course is to introduce the student to the fundamentals of parallel programming and its relationship on computer architectures. Various forms of parallelism are discussed and exploited through different programming models with focus on shared and distributed memory programming. The learned techniques are tried out by means of homework, lab sessions and a term project.

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Topics in Theory for Society: The Theory of Algorithmic Fairness

COMPSCI 226R
2024 Spring

Cynthia Dwork
Monday, Wednesday
12:45pm to 2:00pm

As algorithms reach ever more deeply and broadly into our lives there is increasing interest that they be fair, despite a lack of consensus on the meaning of the term. The theory of algorithmic fairness is a still-new discipline exploring notions of fairness and their consequences: which fairness goals can be simultaneously achieved? How do various notions compose – are systems made up of parts that are fair in isolation also fair in toto? How can we move beyond fairness-as-correctness in the current, flawed, world, to fairness in a better world? The course will start with basics and move to highlights from a recent explosion of research showing broad applicability to problems in machine learning even when fairness is not a concern, as well as deep connections to notions in pseudorandomness.

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Optimized Democracy

COMPSCI 238
2024 Spring

Ariel Procaccia
Monday, Wednesday
11:15am to 12:30pm

The course examines the mathematical and algorithmic foundations of democracy, running the gamut from theory to applications. The goal is to provide students with a rigorous perspective on, and a technical toolbox for, the design of better democratic systems. Topics include computational social choice (identifying optimal voting rules), fair division with applications to political redistricting (avoiding gerrymandering) and apportionment (allocating seats on a representative body), sortition (randomly selecting citizens' assemblies), liquid democracy (transitively delegating votes), and weighted voting games (analyzing legislative power through cooperative game theory).

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Advanced Computer Architecture

COMPSCI 246
2024 Spring

David Brooks
Friday
9:00am to 11:45am

Review of the fundamental structures in modern processor design. Topics include computer organization, memory system design, pipelining, and other techniques to exploit parallelism. Discussion of modern topics including GPU architectures, datacenter architecture, mobile/embedded SoC architectures, and machine learning acceleration as time permits. Emphasis on a quantitative evaluation of design alternatives and an understanding of performance and energy consumption issues.

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Advanced Design of VLSI Circuits and Systems

COMPSCI 248
2024 Spring

Gage Hills
Monday, Wednesday
2:15pm to 3:30pm

Presentation of concepts and techniques for the design and fabrication of VLSI systems and digital MOS integrated circuits. Topics include: basic semiconductor theory; MOS transistors and digital MOS circuits design; synchronous machines, clocking, and timing issues; high-level description and modeling of VLSI systems; synthesis and place and route design flows; and testing of VLSI circuits and systems. Various CAD tools for design, simulation, and verification are extensively used.

The contents and course requirements are similar to those of Computer Science 148, with the exception that students enrolled in Computer Science 248 are expected to do a substantial design project and paper discussions on advanced topics.

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Formal Methods for Computer Security

COMPSCI 254
2024 Spring

Stephen Chong
Tuesday, Thursday
11:15am to 12:30pm

This course explores formal methods for computer security, including formal security models, relationships between security properties/policies and enforcement mechanisms, principled techniques and tools to specify, analyze, and construct secure computer systems. Specific topics include properties, hyperproperties, side channels, reasoning about cryptographic protocols, information flow, authorization logics, and verification techniques. Assessment will include homeworks and/or small projects during the semester as well as a final, larger project that is open-ended and driven by student interests.

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Systems Security

COMPSCI 263
2024 Spring

James Mickens
Tuesday, Thursday
12:45pm to 2:00pm

This course explores practical attacks on modern computer systems, explaining how those attacks can be mitigated using careful system design and the judicious application of cryptography. The course discusses topics like buffer overflows, web security, information flow control, and anonymous communication mechanisms such as Tor. The course includes several small projects which give students hands-on experience with various offensive and defensive techniques; the final, larger project is open-ended and driven by student interests.

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Big Data Systems

COMPSCI 265
2024 Spring

Stratos Idreos
Tuesday, Thursday
9:45am to 11:00am

Big data is everywhere. A fundamental goal across numerous modern businesses and sciences is to be able to utilize as many machines as possible, to consume as much information as possible and as fast as possible. The big challenge is how to turn data into useful knowledge. This is a moving target as both the underlying hardware and our ability to collect data evolve. In this class, we discuss how to design data systems, data structures, and algorithms for key data-driven areas, including relational systems, distributed systems, graph systems, noSQL, newSQL, machine learning, and neural networks. We see how they all rely on the same set of very basic concepts and we learn how to synthesize efficient solutions for any problem across these areas using those basic concepts.

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Topics in Data Visualization

COMPSCI 271
2024 Spring

Johanna Beyer
Monday, Wednesday
9:45am to 11:00am

This course covers advanced topics in data visualization. Over the course of the semester, we will examine seminal works and recent state-of-the-art research in information visualization, scientific visualization and visual analytics. Students will work on a semester-long visualization project that will allow them to visualize their own data sets and write a short paper about their project. We will employ peer-feedback and formal design critiques to analyze each other's work.

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Design, Technology, and Social Impact

COMPSCI 276
2024 Spring

Krzysztof Gajos
Tuesday, Thursday
9:45am to 11:00am

The course explores major areas of research and practice at the intersection of design, technology, and social impact. Specifically, we will explore the current state of research and interesting real-world examples related to the design, evaluation, and implementation of interventions comprising of technical, social, and organizational elements. We will also explore leading theories and methods for anticipating broader, indirect societal impacts of such intervention. Course activities will involve discussion of primary literature, some guided instruction, assignments, and a major research project.

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AI for Social Impact

COMPSCI 288
2024 Spring

Milind Tambe
Monday, Wednesday
3:45pm to 5:00pm

Recent years have seen AI successfully applied to societal challenge problems. Indeed, recognizing the potential of AI for tremendous social impact in the future, "AI for social impact" is growing as a subdiscipline within AI. In this course, we will discuss successful case studies of  use of AI for public health, environmental sustainability, public safety and public welfare. Simultaneously, we will discuss key foundations of the area of AI for social impact. To that end, among other topics, we will focus on challenges in AI for Social Impact, what makes projects successful, how to investigate project impact in the field and ethical considerations for such projects. A key part of this course will be AI4SI projects with non-profits.

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Seminar on Effective Research Practices and Academic Culture

COMPSCI 290B
2024 Spring

Martin Wattenberg, John Girash
Friday
9:45am to 11:45am

This is a reading and discussion-based seminar designed for entering Computer Science Ph.D. students. This course prepares students to manage the difficult and often undiscussed challenges of Ph.D. programs through sessions on research skill building (e.g. paper reading, communication), soft skill building (e.g. managing advising relationships, supporting your peers), and academic culture (e.g. mental health in academia, power dynamics in scientific communities), as well as research and professional-oriented discussions. 

This is a full-year, 4-unit course, meeting once a week in each of the fall and the spring. Students must complete both terms of this course (parts A and B) within the same academic year to receive credit.

 

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Special Topics in Computer Science

COMPSCI 299R
2024 Spring

Krzysztof Gajos

Supervision of experimental or theoretical research on acceptable problems in computer science and supervision of reading on topics not covered by regular courses of instruction.

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