96 courses with the subject CSC, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
CSC 110Building Virtual Worlds3
A gentle introduction to programming with user-friendly software (Alice). Students will use 3D animated interactive virtual worlds to develop an understanding of basic programming constructs. Open to all students. Computer science majors may take this course to prepare for CSC 120. This course presupposes no previous programming experience.
A gentle introduction to computer science. Students will be introduced to basic programming constructs in a language such as Python. Open to all students. Computer science majors may take this course to prepare for CSC 120. This course presupposes no previous programming experience.
The course aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class uses the Python programming language.
Computer programming for beginners. Very little prior knowledge regarding how computers work is assumed. Learn how to write understandable computer programs in a programming language widely used on the Internet. Go beyond the routine skills of a computer user and learn the programming fundamentals: data, variables, selection, loops, arrays, input/output, methods and parameter passing, object and classes, abstraction. Take what is learned and write programs for use on the Internet. One hour per week of the course is a required laboratory.
The course covers intermediate programming techniques emphasizing advanced object oriented techniques including inheritance, polymorphism, and interfaces. Other topics include recursion, exception handling, design patterns, simple GUI programming, and dynamic containers such as linked lists, stacks, queues, and trees.
The course covers fundamental data structures, algorithms for manipulating and retrieving information from these data structures, and techniques for analyzing their efficiency in terms of space and time. The distinction between an Abstract Data Type and its implementation is emphasized. Topics include lists, vectors, trees (general trees, binary search trees, and balanced trees), priority queues, hashing, graphs, and various searching and sorting algorithms.
Overview of computer system organization, hardware, and communications. Introduction to combinational and sequential logic, arithmetic, CPU, memory, microprocessors, and interfaces. CISC vs. RISC processors. Assembly language programming, microarchitecture, and microprogramming on a variety of processors.
Topics include finite probability space, conditional probability, Bayes' theorem, permutations and combinations, statistics and sampling distributions, the Central Limit Theorem, hypothesis testing, correlation, regression analysis, data encoding, channel capacity, the Shannon coding theorem. Data analysis projects using an appropriate statistical package will be assigned.
This course covers the general principles underlying programming languages, including topics such as syntax and its specification, data types, data control, flow control, storage management, and support for design patterns. Examples will be drawn from a variety of programming paradigms, including functional, object-oriented, and procedural languages.
This course presents fundamental techniques for designing efficient computer algorithms and analyzing their running times. Topics include asymptotics, solving summations and recurrences, sorting and selection, graph algorithms (depth-first and breadth-first search, minimum spanning trees, and shortest paths), algorithm design techniques (divide-and-conquer, dynamic programming, and greedy algorithms), and introduction to NP- completeness.
What can you do with a degree in Mathematics, Computer Science, Information Technology, or Actuarial Science? Do you know how to search for an internship or a job? And, are you ready to apply for a position should the opportunity arise? Have you practiced your elevator pitch? This professional development seminar will enhance students' knowledge about internships and careers within their major and help them build practical skills through a series of steps and events throughout the semester. This one-credit course meets once a week through the semester to provide practical instruction and skills in areas that include internship search and application, resume/cover letter prep, professional communication, and networking/interviewing.
An overview of operating systems and the software required to integrate computer hardware into a functional system. Topics include operating systems structure, interrupt driven systems, concurrency, memory management, file systems and security, and system calls.
Principles of designing large programs, including issues of specification, documentation, design strategies, coding, testing and maintenance. Students work in small groups to design and implement a major software project.
The course aims to investigate the role and various architectures of transformers which rely heavily on the self-attention mechanism. Topics include text classification and generation, transformer anatomy, document analysis, fake text and image generation.
The course covers the evolution of cybercrimes and the evolution of the laws used to prosecute those who commit them. We will examine the fact-patterns of significant cybercrimes that have occurred in modern history, including notable prosecutions in hacking, illegal enterprise, and child exploitation. We will explore the (current) categories of cybercrimes and delve into the crimes that did not exist prior to the proliferation of the personal computer. We will explain the role of digital evidence in theses prosecutions and will also look closely at the laws (both at the federal and state levels) that are used to hold cybercriminals accountable.
Principles of designing large programs, including issues of specification, documentation, design strategies, coding, testing and maintenance. Students work in small groups to design and implement a major software project.
Computer vision is the science of analyzing images and videos in order to recognize or model 3D objects, persons, and environments. Topics include the underlying image formation principles, extracting simple features like prominent points or lines in images, projecting a scene to a picture, tracking features and areas in images and make a mosaic, making an image-based positioning system, obtaining 3D models from two or more images, and techniques to recognize simple patterns and objects. The class includes programming exercises and hands-on work with digital cameras and laser scanners.
Image Data Science is the science of analyzing images including video in order to recognize or model 3D objects, persons, and environments. Topics include the underlying image formation principles, extracting simple features like prominent points or lines in images, projecting a scene to a picture, tracking features and areas in images to make a mosaic, making an image-based positioning system, obtaining 3D models from two or more images, and techniques to recognize simple patterns and objects. The course includes programming projects.
This course will introduce students to the various aspects of data science such as data collection and integration, exploratory data analysis, predictive modeling, descriptive modeling, data product creation, evaluation, and effective communication. The focus in the treatment of these topics will be on breadth, rather than depth, and emphasis will be placed on integration and synthesis of concepts and their application to solving problems. To make the learning contextual, real datasets from a variety of disciplines will be used. Course includes programming projects in a Python and/or R.
The course introduces most recent tools for performing predictive analytics, data visualization, data wrangling, statistical inference, deep machine learning, and software engineering. The main focus of the course is to introduce students to most important aspects of data science by reinforcing writing efficient code, testing, and debugging while working with large software systems. The course includes several programming projects.
The course will present machine learning algorithms for supervised and unsupervised learning with an emphasis on recent advances in deep learning with neural networks, decision trees, and various stochastic models. Application areas in data science, computer vision, natural language understanding, and engineering optimization will reinforce the covered topics. The course includes several programming projects.
This course provides a comprehensive introduction to machine learning, covering fundamental concepts, algorithms, and practical applications. Students will learn the basics of supervised and unsupervised learning, including regression, classification, clustering, and dimensionality reduction. They will also explore advanced topics such as neural networks, deep learning, and reinforcement learning. Through hands-on programming projects and exercises, students will gain practical experience in implementing machine learning algorithms and analyzing real-world datasets.
The course will cover the concepts and structures necessary to design and implement a relational database system. Topics to be covered: entity-relationship and relational data models, relational algebra, SQL, normalization, file organization, indexing, hashing, and enterprise-wide web-based applications.
Topics include mathematical foundations of data communications, logical and physical organization of computer networks, the ISo and TCP/IP models, communication protocols, circuit and packet switching, the Internet, LAN/WAN, client/server communications via sockets, routing protocols, data encryption/decryption and network security issues.
This project-driven course focuses on the modern DevOps workflow for deploying and managing distributed Internet applications. Students will gain core skills in version control (Git), automating infrastructure using Infrastructure as Code (IaC), and implementing a delivery pipeline. A key focus is on leveraging Docker containerization for consistent application packaging and using an orchestration technique to manage high-scale, fault-tolerant deployments.
This course is designed for students who wish to start developing mobile applications on Android platforms, and through the process understand the concepts relating to Computer Science on a mobile platform. The course will include the basics of mobile and wireless technology with Android programming and will cover the most recent version of Android. Students will learn how to develop feature-rich Android applications using various development platforms and learn the basic concepts in Computer Science such as algorithmic thinking, abstractions, logic, flow control, and data representation, storage and manipulation. The primary language used in the course will be Java.
The number of smartphones, tablets, and PCs in use will reach about 7.3 billion units in the near future. In contrast, the IoT (Internet of Things) will have expanded at a much faster rate, resulting in a population of about 26 billion units at that time. The IoT is the network of physical objects that contains embedded technology to communicate and sense or interact with their internal states or the external environment. In this course, students will use two of the most popular IoT platforms (Arduino and Raspberry Pi) to develop their own "things."
This course explores the principles and practices of designing, building, and maintaining modern data pipelines for massive, real-time datasets. The course will move beyond traditional paradigms to focus on cloud-native and highly distributed systems.
The course introduces students on how to implement and enforce access and data protection measures for mobile applications using data encryption standards, VPN policies, and authentication. The focus of the course is on the integration between the mobile application and remote authentication services. The course include Android programming projects using security specific SDK's
Cloud Computing is concerned with the use and architecture of this model of computation. This course covers the services provided by clouds, their internal structure, and their possibilities and limitations. Topics include Infrastructure as a Service, Middleware (Platform) as a Service, Software as a Service, Service-oriented architectures, Web Services and standards, cloud security, reliability, governance, and wireless clouds.
The course covers fundamental concepts such as production systems, uniformed and informed search techniques, the role of heuristics, and adversarial game playing. Additional topics include machine learning techniques such as reinforcement learning, natural language processing, and neural networks.
Introduction to formal models of languages and computation. Topics covered include finite automata, regular languages, context-free languages, pushdown automata, Turing machines, computability, and NP- completeness.
This course is a broad introduction to the field of Digital Forensics. It covers various fundamental topics necessary for digital forensics investigation, and a variety of hardware and software tools that are commonly used during the investigation. The course begins with foundations of electronic evidence including cybercrime laws, the 4th Amendment, compliance and requirements, collection and handling, analysis, and reporting. The course also covers fundamentals of file systems with specific details pertaining to Microsoft FAT file systems. Students will learn two important forensics techniques -file recovery and file carving-among other things. In addition, basic techniques used in Network-based digital forensics will also be covered. Finally, Anti-forensics will also be discussed. Hands-on lab activities familiarize students with several relevant investigation techniques.
This course introduces students to the basic principles and techniques used in penetration testing, also known as Ethical Hacking. The course covers the methods used in penetration testing process and the corresponding remedial techniques while emphasizing the key factors that differentiate a malicious attacker from an ethical hacker, stressing the importance of being within legal confines. Students will develop a broad understanding of current cybersecurity problems by completing projects on the topic of Ethical Hacking.
An information security management system (ISMS) is a documented management system that consists of a set of security controls that protect the confidentiality, availability, and integrity of company/business assets from threats and vulnerabilities. The course covers the importance of an ISMS to any given organization in light of the multiple cybersecurity threats in the world today. It also explains the components of an ISMS, the methods used to create one, and complete exercises that show the relationship between technical cybersecurity skills; and, what makes those skills of value to businesses and other organizations
The course introduces students to recent theoretical or practical topics of interest in computer science. Content and structure of the course are determined by the course supervisor. The special topic(s) for a given semester will be announced prior to registration.
This course provides an introduction to the field of Game AI using the Unity Engine and C#. Students will learn how to create intelligent game agents that exhibit complex behaviors such as pathfinding, decision making, and goal-oriented behavior. Through hands-on projects and assignments, students will gain practical experience implementing AI algorithms in Unity, preparing them to design and develop interactive game experiences. No prior experience with Unity or C# is required.
An information security management system (ISMS) is a documented management system that consists of a set of security controls that protect the confidentiality, availability, and integrity of company/business assets from threats and vulnerabilities. The course covers the importance of an ISMS to any given organization in light of the multiple cybersecurity threats in the world today. It also explains the components of an ISMS, the methods used to create one, and the complete exercises that show the relationship between technical cybersecurity skills; and, what makes those skills of value to businesses and other organizations.
The course goals are: to gain first-hand experience of the daily activities of professionals in computer science and related fields, to verify an interest in a particular area of computer science, to develop and hone skills required for computer science professions, to establish contacts outside the academic community who will facilitate a career in computer science. An internship journal and a report are also required.
Supervised independent research mentored by a faculty member. Students must complete the application form for independent study (available in the Dean’s Office) and have the approval of the department chair, Associate Dean, and Honors Program Director to register.
A one- or two-semester, independent research project on a topic selected by the student and a faculty research advisor, and approved by the department. The student may undertake the two-semester option to graduate with departmental honors, in which case he/she must notify the department by spring of his/her junior year. Students need to complete the application form for independent study (available in the Dean's Office), meet the GPA and other requirements, and have the approval of the Computer Science Department chair and Associate Dean in order to register.
A one- or two-semester, independent research project on a topic selected by the student and a faculty research advisor, and approved by the department. The student may undertake the two-semester option to graduate with departmental honors, in which case he/she must notify the department by spring of his/her junior year. Students need to complete the application form for independent study (available in the Dean's Office), meet the GPA and other requirements, and have the approval of the Computer Science Department chair and Associate Dean in order to register.
Students need to complete the application form for independent study (available in the Dean's Office) and have the approval of the Department Chair, Associate Dean and the Honors Program Director in order to register.
Students need to complete the application form for independent study (available in the Dean's Office) and have the approval of the Department Chair, Associate Dean and the Honors Program Director in order to register.
Mathematics needed for Computer Science. Topics covered include: functions, relations, propositional and first order predicate logic, set theory, proofs and their construction, counting and elementary probability. The course will use a declarative language as a tool to support concrete implementations of the mathematical ideas.
This course provides students with the necessary background in programming for the graduate program. Students will learn general principles of program design at first by using libraries of predefined program units, and later by constructing complete programs. Intermediate programming techniques including the use of recursion are covered. An introduction to encapsulated data structures and algorithm efficiency.
This course provides students, who have minimal or no prior knowledge of computational environments, with an understanding of modern computers and operating systems. Students will also learn general principles of programming design in an appropriate computational environment such as Python. Emphasis is on developing techniques for program design that lead to correct and secure programs.
The course combines a strong emphasis on Object-Oriented Design principles and design patterns with the study of data structures. Fundamental Abstract Data Types, their implementations and techniques for analyzing their efficiency will be covered. Students will design, build, test, debug and analyze medium-size software systems and learn to use relevant tools.
Concepts of program complexity; basic approaches to complexity reduction: data structures and techniques; worst cases and expected complexity. Topics to be covered may include sorting, set manipulation, graph algorithms, matrix multiplication, and finite Fourier transforms, polynomial arithmetic, and pattern matching.
Overview of computer system organization, hardware components, and communications. Introduction to Boolean algebra, combinational and sequential logic, arithmetic, the CPU, memory, microprocessors, and interfaces. CISC vs. RISC processors. Practical assembly language programming will be the emphasis with an introduction to micro architecture and microprogramming on a variety of processors.
An overview of the software required to integrate computer hardware into a functional system. The following topics are covered. Operating systems as resource managers and as virtual machines. System calls, in particular those required for process and file management; interrupt driven systems; concurrency; memory management; file systems and security.
The purpose of this class is to teach the process of developing software. It combines a study of methods, tools, and techniques for creating and evolving software products, with the practical skills needed to deliver high- quality software products on schedule. The methods that are studied include requirements, specification, design, implementation, testing, and maintenance. The course includes a substantial group project.
This project-driven course focuses on the modern DevOps workflow for deploying and managing distributed Internet applications. Students will gain core skills in version control (Git), automating infrastructure using Infrastructure as Code (IaC), and implementing a delivery pipeline. A key focus is on leveraging Docker containerization for consistent application packaging and using an orchestration technique to manage high-scale, fault-tolerant deployments.
This course covers the concepts and structures necessary to design and implement a database management system. Topics to be covered: data models (entity-relationship and relational), SQL, normalization, storage structures, enterprise applications and database integrity.
Topics include stored procedures, triggers, query processing and optimization, web-based enterprise data applications, transaction management, concurrency control, distributed databases, data mining and web mining. The course includes programming projects involving SQL.
Topics include mathematical foundations of data communications, logical and physical organization of computer networks, the ISO and TCP/IP models, communication protocols, circuit and packet switching, the Internet, LAN/WAN, client/server communications via sockets, routing protocols, data encryption/decryption and network security issues.
Topics include classical cryptosystems, public and symmetric cryptography, key management, digital signatures, cipher techniques, authentication and federated identity management. Course also covers concepts relating to cryptovirology, malware, viruses, Trojan horses, worms and other types of infectors as they relate to network security. Course includes programming projects.
This course is designed for students who wish to start developing mobile applications on Android platforms, and through the process understand the concepts relating to Computer Science on a mobile platform. The course will include the basics of mobile and wireless technology with Android programming and will cover the most recent version of Android. Students will learn how to develop feature-rich Android applications using various development platforms and learn the basic concepts in Computer Science such as algorithmic thinking, abstractions, logic, flow control, and data representation, storage and manipulation. The primary language used in the course will be Java.
The course provides an introduction to the principles of computer graphics. The emphasis will be placed on understanding how various elements that underlie computer graphics interact in the design of graphics software systems. Topics include pipeline architecture, graphics programming, 3D geometry and transformations, modeling, viewing, clipping and projection, lighting, shading and texture mapping and visibility determination. A standard graphics API will be used to reinforce concepts and the study of basic graphics algorithms. Students need some proficiency in C language and basic concepts from Linear Algebra.
Computer vision is the science of analyzing images and videos in order to recognize or model 3D objects, persons, and environments. Topics include the underlying image formation principles, extracting simple features like prominent points or lines in images, projecting a scene to a picture, tracking features and areas in images and make a mosaic, making an image-based positioning system, obtaining 3D models from two or more images, and techniques to recognize simple patterns and objects. The class includes programming exercises and hands-on work with digital cameras and laser scanners.
This is a technology-based course that uses the latest computer games technology to teach advanced programming, mathematics, and software development. The course is ideal for students with an interest in computer games who plan to seek employment in one of the country's more profitable industries, or students looking for a career in new technologies or software development. The interactive entertainment industry in the US and throughout the world is entering a new phase. New technology platforms are forcing existing development firms to diversify. There are many aspects of game design, development, production, finance, and the distribution process.
Image Data Science is the science of analyzing images including video in order to recognize or model 3D objects, persons, and environments. Topics include the underlying image formation principles, extracting simple features like prominent points or lines in images, projecting a scene to a picture, tracking features and areas in images to make a mosaic, making an image-based positioning system, obtaining 3D models from two or more images, and techniques to recognize simple patterns and objects. The course includes programming projects.
This course explores the principles and practices of designing, building, and maintaining modern data pipelines for massive, real-time datasets. The course will move beyond traditional paradigms to focus on cloud-native and highly distributed systems.
The course introduces students on how to implement and enforce access and data protection measures for mobile applications using data encryption standards, VPN policies, and authentication. The focus of the course is on the integration between the mobile application and remote authentication services. The course include Android programming projects using security specific SDK's
This course introduces students to the basic principles and techniques used in penetration testing, also known as Ethical Hacking. The course covers the methods used in penetration testing process and the corresponding remedial techniques while emphasizing the key factors that differentiate a malicious attacker from an ethical hacker, stressing the importance of being within legal confines. Students will develop a broad understanding of current cybersecurity problems by completing projects on the topic of Ethical Hacking.
The number of smartphones, tablets, and PCs in use will reach about 7.3 billion units in the near future. In contrast, the IoT (Internet of Things) will have expanded at a much faster rate, resulting in a population of about 26 billion units at that time. The IoT is the network of physical objects that contains embedded technology to communicate and sense or interact with their internal states or the external environment. In this course, students will use two of the most popular IoT platforms (Arduino and Raspberry Pi) to develop their own "things."
This course is a broad introduction to the field of Digital Forensics. It covers various fundamental topics necessary for digital forensics investigation, and a variety of hardware and software tools that are commonly used during the investigation. The course begins with foundations of electronic evidence including cybercrime laws, the 4th Amendment, compliance and requirements, collection and handling, analysis, and reporting. The course also covers fundamentals of file systems with specific details pertaining to Microsoft FAT file systems. Students will learn two important forensics techniques -file recovery and file carving-among other things. In addition, basic techniques used in Network-based digital forensics will also be covered. Finally, Anti-forensics will also be discussed. Hands-on lab activities familiarize students with several relevant investigation techniques.
An information security management system (ISMS) is a documented management system that consists of a set of security controls that protect the confidentiality, availability, and integrity of company/business assets from threats and vulnerabilities. The course covers the importance of an ISMS to any given organization in light of the multiple cybersecurity threats in the world today. It also explains the components of an ISMS, the methods used to create one, and complete exercises that show the relationship between technical cybersecurity skills; and, what makes those skills of value to businesses and other organizations.
This course will explain the core components of creating a successful Computer Security Incident Response Plan (CSIRP) and maintaining it in response to changes at the organization. It will also detail how a well-maintained CSIRP can mitigate and offset the losses to an organization and lessen their legal liabilities in the event of a breach. The student will learn the hardware and software resources that exist to assist organizations in preventing incidents, and that collect data to properly investigate such incidents. The student will also learn how to properly execute the procedures within a CSIRP, and see how the plan will dictate information flow to the critical parties within the organization. Lastly, the program will connect Incident Response Management to an Information Security Management System.
The course introduces the core terminology and concepts regarding the proper preservation of digital evidence. It will explain Locard's Exchange Principle, the importance of precise chain-of-custody and detailed documentation during the data collection efforts, the importance of proper metadata preservation and the investigative use of that metadata. The course will transition to hands-on work using actual digital forensic tools. The students will collect pre-created evidence (email and file system), document their work with the tools and in their own notes. They will perform basic analyses, they will complete chain-of-custody forms, supply the logs generated by their use of the tools, and then answer questions on the evidence, their findings, and these processes over the course of the semester.
Cloud Computing is concerned with the use and architecture of this model of computation. This course covers the services provided by clouds, their internal structure, and their possibilities and limitations. Topics include Infrastructure as a Service, Middleware (Platform) as a Service, Software as a Service, Service-oriented architectures, Web Services and standards, cloud security, reliability, governance, and wireless clouds.
The course covers the evolution of cybercrimes, and the evolution of the laws used to prosecute those who commit them. We will examine the fact-patterns of significant cybercrimes that have occurred in modern history, including notable prosecutions in hacking, illegal enterprise, and child exploitation. We will explore the (current) categories of cybercrimes and delve into the crimes that did not exist prior to the proliferation of the personal computer. We will explain the role of digital evidence in these prosecutions and we will also look closely at the laws (both at the federal and state levels) that are used to hold cybercriminals accountable.
This course discusses Information Governance (IG) and the policies and procedures needed within an organization to avert risk and stay compliant. The objectives of this course are to help students look at Information Governance in theory, practice, and policy. This is one of the primary drivers behind an organization’s cybersecurity program and efforts is the goal of proper Information Governance.
This course is intended to orient the student on the ten core domains in the practice of cybersecurity. These domains were defined by the International Information System Security Certification Consortium, Inc. for their CISSP certification (Certified Information Systems Security Professional). The content presented in this course will offer a successful student the dual-benefit of being prepared for further study and possible certification as a CISSP, and also will provide them broad background knowledge on the technical and business needs that drive the practice of cybersecurity.
The course introduces students to recent theoretical or practical topics of interest in computer science. Content and structure of the course are determined by the course supervisor. The special topics for a given semester will be announced prior to registration. With permission of the Graduate Director the course may be taken more than once.
Candidates will learn subject-specific standards for competencies based upon the Computer Science Teachers Association (CSTA) standards. The CSTA academic standards detail a core set of learning objectives providing the foundation for a rigorous K-12 computer science curriculum. The standards introduce the foundation concepts of computer science making them accessible for all learners. Topics will include the following: Algorithms and Programming, Computing Systems, Data and Analysis, Impacts of Computing, Networks and the Internet and Pedagogy.
This course provides a comprehensive introduction to machine learning, covering fundamental concepts, algorithms, and practical applications. Students will learn the basics of supervised and unsupervised learning, including regression, classification, clustering, and dimensionality reduction. They will also explore advanced topics such as neural networks, deep learning, and reinforcement learning. Through hands-on programming projects and exercises, students will gain practical experience in implementing machine learning algorithms and analyzing real-world datasets.
This course provides an introduction to the field of Game AI using the Unity Engine and C#. Students will learn how to create intelligent game agents that exhibit complex behaviors such as pathfinding, decision making, and goal-oriented behavior. Through hands-on projects and assignments, students will gain practical experience implementing AI algorithms in Unity, preparing them to design and develop interactive game experiences. No prior experience with Unity or C# is required.
The course covers fundamental concepts such as production systems, uniformed and informed search techniques, the role of heuristics, and adversarial game playing. Additional topics include machine learning techniques such as reinforcement learning, natural language processing, and neural networks.
This course covers the general principles underlying programming languages, including topics such as syntax and its specification, data types, data control, flow control, storage management, and support for design patterns. Examples will be drawn from a variety of programming paradigms, including functional, object-oriented, and procedural languages.
P and NP problems; NP-complete classes; concrete complexity and the P class of combinatorial problems; complexity reduction on graph and string problems; complexity of algebraic computations.
The course will present machine learning algorithms for supervised and unsupervised learning with an emphasis on recent advances in deep learning with neural networks, decision trees, and various stochastic models. Application areas in data science, computer vision, natural language understanding, and engineering optimization will reinforce the covered topics. The course includes several programming projects.
The course covers the fundamental concepts in data science including mathematical tools needed to analyze large data sets, data visualization, inferential techniques, cloud computation, and applying analytical methods to real-world business and industry data.
The course introduces most recent tools for performing predictive analytics, data visualization, data wrangling, statistical inference, deep machine learning, and software engineering. The main focus of the course is to introduce students to most important aspects of data science by reinforcing writing efficient code, testing, and debugging while working with large software systems. The course includes several programming projects.
The course aims to investigate the role and various architectures of transformers which rely heavily on the self-attention mechanism. Topics include text classification and generation, transformer anatomy, document analysis, fake text and image generation.
Supervised independent research mentored by a graduate faculty member. Students must have a GPA of 3.5 and permission of the Graduate Director to enroll in this course.
Supervised independent research mentored by a graduate faculty member. Students must have a GPA of 3.5 and permission of the Graduate Director to enroll in this course.
Supervised independent research mentored by a graduate faculty member. Students must have a GPA of 3.5 and permission of the Graduate Director to enroll in this course.
