Courses

The listing of a course description here does not guarantee a course’s being offered in a particular term. Please refer to the published schedule of classes on the MyBU Student Portal for confirmation a class is actually being taught and for specific course meeting dates and times.

• CAS CS 538: Fundamentals of Cryptography
  Undergraduate Prerequisites: (CASCS131 & CASCS237 & CASCS357) or consent of instructor. - Graduate Prerequisites: (CASCS332) - Basic Algorithms to guarantee confidentiality and authenticity of data. Definitions and proofs of security for practical constructions. Topics include perfectly secure encryption, pseudorandom generators, RSA and Elgamal encryption, Diffie-Hellman key agreement, RSA signatures, secret sharing, block and stream ciphers.
• CAS CS 541: Applied Machine Learning
  Undergraduate Prerequisites: CS111 (CS112 recommended); CS132 or MA242 (or EK103); CS237 or MA581 ( or EK381.) CS365 is recommended. - Covers practical skills in machine learning including techniques for clustering, classification, regression, feature selection, and model compression. Emphasizes hands-on application of methods via programming on real- world datasets.
• CAS CS 542: Principles of Machine Learning
  Undergraduate Prerequisites: (CASCS365) - Introduction to modern machine learning concepts, techniques, and algorithms. Topics include regression, kernels, support vector machines, feature selection, boosting, clustering, hidden Markov models, and Bayesian networks. Programming assignments emphasize taking theory into practice, through applications on real-world data sets.
• CAS CS 543: Algorithmic Techniques for Taming Big Data
  Undergraduate Prerequisites: exposure to basic data structures and algorithms or consent of instruc tor. - Growing amounts of available data lead to significant challenges in processing them efficiently. In many cases, it is no longer possible to design feasible algorithms that can freely access the entire data set. Instead of that we often have to resort to techniques that allow for reducing the amount of data such as sampling, sketching, dimensionality reduction, and core sets. Also explores scenarios in which large data sets are distributed across several machines or even geographical locations and the goal is to design efficient communication protocols or MapReduce algorithms. Includes a final project and programming assignments in which we explore the performance of our techniques when applied to publicly available data sets. Effective Fall 2021, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning II, Creativity/Innovation.
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  • Creativity/Innovation
  • Quantitative Reasoning II
• CAS CS 544: Multimodal Machine Learning
  Prerequisite: CASCS 542. - This course introduces methods for fusing multiple data sources to perform downstream tasks, covering machine learning and statistical techniques to understand relationships between modalities. Students also explore challenges like data scarcity, positive-unlabeled learning, structured prediction, and system evaluation.
• CAS CS 548: Advanced Cryptography
  Undergraduate Prerequisites: (CASCS 538) or consent of instructor. - Continuation of CASCS 538. Advanced techniques to preserve confidentiality and authenticity against active attacks, zero-knowledge proofs; Fiat-Shamir signature schemes; non-malleable public-key encryption; authenticated symmetric encryption; secure multiparty protocols for tasks ranging from Byzantine agreement to mental poker to threshold cryptography.
• CAS CS 549: Spark! Machine Learning X-Lab Practicum
  Undergraduate Prerequisites: (CASCS505 OR CASCS542 OR CASCS585) or consent of instructor. Consent provided upon successful completion of pass/fail diagnostic test that will assess student readiness to tak e the course. - The Spark! Practicum offers students in computing disciplines the opportunity to apply their knowledge in algorithms, inferential analytics, and software development by working on real-world projects provided from partnering organizations within BU and from outside. The course offers a range of project options where students can improve their technical skills, while also gaining the soft skills necessary to deliver projects aligned to the partner's goals. These include teamwork and communications skills and software development processes. All students participating in the course are expected to complete a project focused on an application of inferential analytics or machine learning, including a final presentation to the partner organization. Effective Spring 2022, this course fulfills a single unit in each of the following BU Hub areas: Ethical Reasoning, Research and Information Literacy, Teamwork/Collaboration.
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  • Ethical Reasoning
  • Research and Information Literacy
  • Teamwork/Collaboration
• CAS CS 551: Streaming and Event-driven Systems
  Prerequisites: CASCS 350 or CASCS 351. - CASCS 460 is recommended. Fundamentals of stream processing and event-driven systems. Topics include Pub/Sub systems; Distributed streaming systems; Dataflow programming; Fault-tolerance and processing guarantees; State management; Windowing semantics; Complex event processing; Microservice architectures; Serverless functions; Examines current and emerging architectures and use-cases.
• CAS CS 552: Introduction to Operating Systems
  Undergraduate Prerequisites: (CASCS 112 & CASCS 210) and competency with C/C++. CASCS 350 is recommended, or consent of instructor. - Examines process synchronization; I/O techniques, buffering, file systems; processor scheduling; memory management; virtual memory; job scheduling, resource allocation; system modeling; and performance measurement and evaluation.
• CAS CS 561: Data Systems Architectures
  Undergraduate Prerequisites: CAS CS 210 or equivalent and CAS CS 460/660. - Discusses the design of data systems that can address the modern challenges of managing and accessing large, ever-growing, diverse sets of data, often streaming from heterogenous sources, in the context of continuously evolving hardware and software. We use examples from several data management areas including relational systems, distributed database systems, key value stores, newSQL and NoSQL systems, data systems for machine learning (and machine learning for data systems), interactive analytics, and data management as a service. Effective Spring 2021, this course fulfills a single unit in each of the following BU Hub areas: Oral and/or Signed Communication, Research and Information Literacy.
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  • Oral and/or Signed Communication
  • Research and Information Literacy
• CAS CS 562: Advanced Database Applications
  Undergraduate Prerequisites: (CASCS460) or consent of instructor. - Research issues in the design and implementation of modern database systems. Spatial, temporal, and spatiotemporal index structures. Indexing methods for image and multimedia databases and data warehouses. New data analysis techniques for large databases, clustering and rule discovery for very large datasets.
• CAS CS 565: Algorithmic Data Mining
  Undergraduate Prerequisites: (CASCS 112 & CASCS 330 & CASCS 365). - Introduction to data mining concepts and techniques. Topics include association and correlation discovery, classification and clustering of large datasets, outlier detection. Emphasis on the algorithmic aspects as well as the application of mining in real-world problems.
• CAS CS 581: Computational Fabrication
  Undergraduate Prerequisites: CAS CS 112 and CAS CS 132 or CAS MA 242; CAS 480/GRS CS 680 recommende d. - Introduces 3D printing technology and computational methods for creating physical prototypes from geometric models. Student-led paper presentations cover research from prominent Computer Graphics and Human Computer Interaction conferences. Culminates in a design project involving a computational component and physical prototyping.
• CAS CS 582: Geometry Processing
  Undergraduate Prerequisites: CAS CS 112 (or equivalent), CAS CS 132 or CAS MA 242 (or equivalent), CAS MA 225 (or equivalent). - Algorithms and data structures for digital processing of triangle meshes and point clouds. Topics include: surface smoothing, parametrization, and deformation; half- edge data structures; discretized curvature measures; and spectral analysis of surfaces. Numerical methods for linear algebra and optimization also discussed.
• CAS CS 585: Image and Video Computing
  Undergraduate Prerequisites: (CASCS132 OR CASMA242) and CASCS112 or equivalent programming experience and familiarity with calculus. - Introduction to images and video as multimedia data types and algorithms for image and video understanding based on color, shading, stereo, and motion. Topics include face recognition, human-computer interfaces, animal and vehicle tracking, and medical image analysis.
• CAS CS 586: Advanced Topics in Computer Vision
  Prerequisites: CASCS 541 or CASCS 542; and CASCS 585. - This seminar course covers current computer vision and machine learning papers, focusing on deep learning, generative models, multimodal learning, 3D vision, fairness, safety, and reinforcement learning. It emphasizes analyzing methods, understanding challenges, and exploring future research directions.
• CAS CS 598: Advanced Topics in Computer Science - LEC DIS Version
  Various advanced topics in computer science that vary semester to semester. Please contact the CAS Computer Science Department for detailed descriptions.
• CAS CS 599: Advanced Topics in Computer Science
  Various advanced topics in computer science that vary semester to semester. Please contact the CAS Computer Science Department for detailed descriptions.
• CAS EC 101: Introductory Microeconomic Analysis
  The first semester of a standard two-semester sequence for those considering further work in management or economics. Coverage includes economics of households, business firms, and markets; consumer behavior and the demand for commodities; production, costs, and the supply of commodities; price determination; competition and monopoly; efficiency of resource allocation; governmental regulation; income distribution; and poverty. Effective Fall 2018, this course fulfills a single unit in each of the following BU Hub areas: Social Inquiry I, Critical Thinking. In 2019-20 this course fulfills a single unit in each of the following BU Hub areas: Social Inquiry I, Ethical Reasoning, Critical Thinking.
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  • Critical Thinking
  • Ethical Reasoning
  • Social Inquiry I
• CAS EC 102: Introductory Macroeconomic Analysis
  The second semester of a standard two-semester sequence for those considering further work in management or economics. National economic performance; the problems of recession, unemployment, and inflation; money creation, government spending, and taxation; economic policies for full employment and price stability; and international trade and payments. Carries social science divisional credit in CAS. Effective Fall 2018, this course fulfills a single unit in the following BU Hub area: Social Inquiry I. Effective Fall 2019, this course fulfills a single unit in each of the following BU Hub areas: Social Inquiry I, Global Citizenship and Intercultural Literacy.
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  • Global Citizenship and Intercultural Literacy
  • Social Inquiry I