program. Only some of these courses are offered (varies year by year). Both theoretical (computational-geometric) models, as well as practical case studies will be covered in the course. York University has introduced in 2018 a Specialization in Artificial Intelligence (AI) in its Master of Science of Computer Science program. Applicants seeking financial assistance should apply before February 15, but assistantships are sometimes awarded at other times. MSc Artificial Intelligence is a 2-year postgraduate course which is designed to teach the students the basics and applications of Artificial Intelligence. in Computer Science and Engineering with Specialization in Artificial Intelligence and Machine Learning Mission of the Department Mission Stmt - 1 To impart knowledge in cutting edge Computer Science and Engineering technologies in par with industrial standards. The Master of Science in Artificial Intelligence (AI) program is designed to give students a comprehensive framework for AI with specialization in one of five areas: vision, intelligent interaction, robotics and agent-based systems, machine learning, and knowledge management and reasoning. Mission Stmt - 2 Find A-Z • An advanced topics course in computer vision which covers selected topics in greater depth. We start with introducing a formal framework, and then introduce and analyze learning methods, such as Nearest Neighbors, Boosting, SVMs and Neural Networks. This course examines the problem of developing rigorous computational models for visual processing. Data analytics and visualization is an emerging discipline of immense importance to any data-driven organization. Find Faculty & Staff • Machine learning, speech and language processing, and computer vision, Profile Those interested in AI-based research in a thesis program should apply to the MSc in Computer Science program. This course is intended as a follow-on from a first course on Artificial Intelligence. Specifically, the graduates of this program will be Computer Science students who are not only proficient in machine learning, but also able to apply their knowledge to facilit… want to gain expertise in one of the most fascinating and fastest growing areas of computer science, artificial intelligence. Information Security 5. Topics in the AI concentration include knowledge representation and logical reasoning, robotics, machine learning, probabilistic modeling and inference, natural language processing, cognition, and applications in domains such as biology and text processing. Master of Science (MS), Computer Science (CS) & Artificial Intelligence (AI) - Salary - Get a free salary comparison based on job title, skills, experience and education. This course is intended for students with professional interest in the social and ethical Georgia Institute of Technology. The need for real-time response and dynamic-scene analysis will be covered, and recent developments in robotics systems from an Artificial Intelligence viewpoint will be discussed. A cumulative GPA of 3.000 or higher is required in the following core courses: 32 total semester hours required Minimum 3.000 GPA required, myNortheastern • Complete two courses from one of the following specializations: College of Professional Studies Undergraduate, University-​Wide Academic Policies and Procedures, Cloud Software Development, Graduate Certificate, College of Social Sciences and Humanities, Gordon Institute of Engineering Leadership, 2020-21 College of Professional Studies Undergraduate PDF, Artificial Intelligence for Human-Computer Interaction, Special Topics in Artificial Intelligence, Theory and Methods in Human Computer Interaction, Unsupervised Machine Learning and Data Mining, Understand representations, algorithms, and techniques used across works in AI and be able to apply and evaluate them in applications as well as develop their own, Understand the basic processes that an agent must perform, from perceiving its environment, making decisions on how to act and performing those actions, as well be able to develop and evaluate the technology that can be used to perform these processes, Understand and apply machine-learning techniques, in particular to draw inferences from data and help automate the development of AI systems and components, Understand the various ways and reasons humans are integrated into mixed human-AI environments, whether it is to improve overall integrated system performance, improve AI performance, or influence human performance and learning, Understand the ethical concerns in developing responsible AI technologies, Model human behavior, develop human-AI systems, and evaluate their performance, Demonstrate knowledge of the use of AI algorithms and processes in one of the specialization areas: robotics and agent-based systems, vision, intelligent interaction, machine learning, and knowledge representation and reasoning. Data mining, graph mining, machine learning, big data analytics, knowledge discovery, AI in precision medicine; Machine learning in image-guided therapeutics; Quantitative imaging and radiomics, Profile Bioinformatics 4. Finally, students present and discuss recent research papers. Vision and intelligent interfaces, Profile Specialization in Artificial Intelligence. This course explores both probabilistic learning and inference, in a range of application areas. 2020-21 Graduate PDF Primarily a survey of current computational methods, we will begin by examining methods for measuring visual data (image based operators, edge detection, feature extraction), and low-level processes for feature aggregation (optic flow, segmentation, correspondence). CS 6475 Computational Photography; CS 6476 Computer Vision; CS 7499 3D Reconstruction M.Sc. Students will develop an understanding of knowledge representation and techniques associated with AI reasoning with uncertainty with the goal of solving current-day complex problems within an organization. program in AI at both Amritapuriand Coimbatore campuses to provide young engineers with a futuristic edge. Hardware acceleration for machine learning, Profile Computer Architecture 7. Prerequisites:MATH 115 and (CIS 150 or IMSE 150 or CCM 150) Description: This course presents techniques for the design, writing, testing, and debugging of medium-sized programs, and an introduction to data structures (stacks, queues, linked tests) using an object-oriented programming language. The course will begin with a study of the mechanics of manipulators and robot platforms. Elective courses consist of graduate courses offered in Khoury and other partner colleges, including CAMD, COE, COS,  CSSH, DMSB, and Law. Artificial Intelligence has the capacity to provide intelligent solutions that can help us to tackle many today’s greatest societal challenges. It mentions their areas of research interests within AI (many have other research interests as well) and provides a link to their personal homepage or research group for more information about their research. M3J 1P3 ), practical issues (algorithmic bias, labour automation, data privacy), and professional issues (tech industry social responsibility). Northeastern University’s Master of Science in Computer Scienceprogram explores both the principles of computing and the many ways these principles are applied to various roles in the computer science discipline. The emphasis will be on the compromises involved in providing a useful but tractable representation and reasoning service to a knowledge-based system. Keele Campus information about MS in Artificial Intelligence program. Machine learning in computer security, Profile Below is a list of faculty members who are part of the Graduate Program in Electrical Engineering and Computer Science at York University. Overview of MS in Computer Science (Artificial Intelligence) course at York U, i.e., York University, Toronto with upcoming application deadlines, average profile of … ON Canada Students have to complete three courses from the following list. Whereas such first courses focus on the important foundations of AI, such a Knowledge Representation or Reasoning, this course will examine how these separate foundational elements can be integrated into real systems. Note that the AI specialization is meant as a targeted preparation to apply AI concepts in the workplace, but being non-thesis it is not suitable to further pursue doctoral studies. Database 3. This requires probabilistic models to represent complex relationships between random variables (learning) as well as algorithms that produce good estimates and decisions based on these models (inference). At least one course must be from each of the following three Groups: Group 1 - Theory of Computing & Scientific Computing (EECS 6127), Group 2 - Artificial Intelligence & Interactive Systems (EECS 5323, EECS 5324, EECS 5326, EECS 5327, EECS 6322, EECS 6323, EECS 6325, EECS 6327, EECS 6328, EECS 6332, EECS 6333, EECS 6340, EECS 6390A, EECS 6390D), Group 3 - Systems: Hardware & Software (EECS 6412, EECS 6414), No more than two courses can be integrated with undergraduate courses (first digit is 5). CSE 6140 Computational Science and Engineering Algorithms; And pick one of: CS 6601 Artificial Intelligence; CS 7641 Machine Learning; Electives (9 hours) Pick three (3) courses from Perception and Robotics, with at least one course from each. in Artificial Intelligence is a program offered at School of Engineering, Amrita Vishwa Vidyapeetham, Amritapuri campus. The main objective of this course is to ensure that students will have a solid understanding of the fundamentals of Artificial Intelligence as well as Machine Learning in theory and practice. Prerequisites: an introductory course on database systems and an introductory course on probability. This is a project-focused course that provides students with knowledge on tools for data mining and visualization and practical experience working with data mining and machine learning algorithms for analysis of very large amounts of data. Search, 360 Huntington Ave., Boston, Massachusetts 02115 • 617.373.2000 • TTY 617.373.3768 © 2020-2021 Northeastern University. The program a… Reinforcement learning for finding bugs in software. The topics may include: formal models of knowledge and belief, systems of limited reasoning, languages of limited expressive power, defaults and exceptions, meta-level representation and reasoning, reasoning about action, and theories of rational agency. The introductory courses are not counted as credit toward the degree but are included in the student’s cumulative grade-point average. This course takes a foundational perspective on machine learning and covers some of its underlying mathematical principles. This will be accomplished by detailing some general overall concepts that form the basis of intelligent systems in the real world, and then presenting a number of in-depth cases studies of a variety of systems from several applications domains. Due to both this positive career outlook and the required skill set for jobs in this field, many employers seek candidates with a master’s degree in computer science to fill these high-paying jobs. This course introduces the student to machine learning concepts and techniques applied to a pattern recognition problem in a diversity of application areas. York University has introduced in 2018 a Specialization in Artificial Intelligence (AI) in its Master of Science of Computer Science program. Students will also be given the opportunity to build on the core knowledge of AI by taking a variety of elective courses, selected from colleges throughout campus, to explore key contextual areas or more complex technical applications. degree program is offered by the interdisciplinary Institute for Artificial Intelligence. Prerequisites: EECS 5323. Software analytics and software performance engineering, Profile Trajectory and course planning, environmental layout and sensing will be discussed. The Master of Science in Artificial Intelligence (MSAI) program provides a comprehensive framework of theory and practice in the emerging field of AI. Machine learning, probabilistic methods, computer vision and computational biology, Profile Adaptive software and autonomic computing, Profile The Master of Science in Artificial Intelligence is comprised of eight courses: five core courses, two electives to be chosen from one of five specialization areas, and one elective. Prerequisites: introductory courses in algorithms, probability theory, linear algebra, and programming. For a Master of Science in Computer Science, Specialization in Machine Learning (15 hours), students must select from the following: *The following is a complete look at the courses that may be selected to fulfill the Machine Learning specialization, regardless of campus; only courses listed with bold titles are offered through the online program. This course introduces the basic concepts associated with Artificial Intelligence (AI) including heuristic search procedures associated with general graphs. The Master of Science in Computer Science program with concentration in Artificial Intelligence program at South College is designed to prepare students with a computer science background with a strong foundation in software system design, implementation, management, and maintenance. This course introduces fundamental concepts of data mining. Computational strategies may draw upon techniques in statistical inference, signal processing, optimization theory, graph theory and distributed computation. Admission is possible in every semester, but Fall admission is preferable. Emergency Information • Every year, new technology completely changes some aspect of modern life, and no technological innovation seems to be as disruptive as artificial intelligence. Students will engage in an extensive core intended to develop depth in all core concepts that build a foundation for AI theory and practice. It presents various data mining technologies, algorithms and applications. Program graduates will be well-positioned to attain research and development positions in a rapidly growing field or to progress into doctoral-degree-related fields. 4700 Keele Street, Toronto B.Tech. This is the list of 15 Major Specializations in MS CS (Computer Science) offered by various US Universities. Machine learning is the study of algorithms that learn how to perform a task from prior experience. The Master of Science in Artificial Intelligence (M.S.A.I.) Data mining, machine learning, information retrieval, and AI, Profile This course covers the theory and practice of neural networks. This course will be an in-depth treatment of one or more specific topics within the field of artificial intelligence. Only the General Test of the GRE is required for the M.S.A.I. In addition, students conduct a research project that applies AI to a practical problem under the supervision of faculty members and in collaboration with partners in the private or public sector. For the past one year, I have been researching about the universities in the United States that offer Master of Science (MS) in Data Science or MS in Computer Science with Data Science specialization. With this knowledge, our graduates will be positioned to successfully deploy AI methodologies across many sectors. Perception. The more practical programming courses are aided by several courses in pure and applied mathematics and theoretical computer science courses throughout the curriculum. Here are some universities, that I know of, who offer a specialisation in Artificial Intelligence : University of California, San Diego. AI-based materials and process development, Profile in Artificial Intelligence Stream In addition to the Program Requirements for the Master of Science in Computer Science, i.e., both Computer Science (MSc) (with and without Co-op), students participating in the Artificial Intelligence Stream must satisfy the following conditions. Theoretical and practical issues of calibration, correspondence/matching and interpretation will be considered. AI-based algorithms for decoding a physiological/neurological function, Profile Prerequisites: EECS 5323. Artificial intelligence is changing our homes, workplaces and lifestyles. Image source: FT US Healthcare & Life Sciences Summit. M. Tech. The focus of this course is on robot motion planning in known and unknown environments. This course examines some of the techniques used to represent knowledge in artificial intelligence, and the associated methods of automated reasoning. Machine learning for bioinformatics, Profile Recent advances flow from the development of deep learning methods, which are neural networks with many hidden layers. The MS degree in Computer Science (Artificial Intelligence), is one of the first programs of its type in the nation, and provides students with rigorous training in the theories and applications of deep learning and artificial intelligence. University of Massachusetts, Amherst. Topics range from well-established results in learning theory to current research challenges. The Master of Computer Science, Concentration in Applied Artificial Intelligence program combines theory, research and applied skills to facilitate a graduate’s entry into a wide range of careers. The Master of Science specialization in cyber security is a graduate program within the Computer Science department, in which students are trained to work in this increasingly important field, which encompasses cryptographic methods, data and information security, fault-tolerant computing, network security, privacy and anonymity, software safety, and system security. As we see a tech revolution in all facets of life powered by Artificial Intelligence, Amrita Vishwa Vidyapeetham offers an M. Tech. This course considers how multiple images of a scene, as captured by multiple stationary cameras, single moving cameras or their combination, can be used to recover information about the viewed scene (e.g., three-dimensional layout, camera and/or scene movement). Topics include theoretical issues (could AI ever have moral rights? The equivalent of a senior-level course in the area of theoretical computer science. Become part of this exciting development by joining our one-year MSc in Computer Science—Artificial Intelligence. Topics covered will vary from year to year depending on the interests of the class and instructor. Minimum English language test scores (if required): TOEFL(iBT) 90, IELTS 7, or York English Language Test 4. Students have to complete the following course. Students have to complete two other courses from the following list. MS in Artificial Intelligence Artificial Intelligence (AI) is an area of study that explores how to create computer programs that learn to make decisions, reason about data, and communicate with humans. The Online Master of Science in Computer Science with Artificial Intelligence Specialization is a practical degree that teaches students how to implement effective artificial intelligence and machine learning solutions in their organizations. robotics, and computer vision. Software Engineering 2. Intelligent systems must make effective judgments in the face of uncertainty. Topics include association rule mining, classification models, sequential pattern mining and clustering. The core courses are designed and developed by Khoury College faculty. 2020-21 College of Professional Studies Undergraduate PDF The Master of Science in Artificial Intelligence (AI) program is designed to give students a comprehensive framework for AI with specialization in one of five areas: vision, intelligent interaction, robotics and agent-based systems, machine learning, and knowledge management and reasoning. Game theory, large-scale optimization and distributed control for enabling adaptive, sustainable and resilient power grid operations, Profile It will be the student's responsibility to secure an internship for their research project. Applicants must include a completed application form, three letters of recommendation, official transcripts, Graduate Record Examinations (GRE) scores, and a sample of your scholarly writing on any subject (in English). Machine intelligence approach for virtual environments, Profile Automated reasoning and propositional satisfiability, Profile This admission requirement can also be fulfilled by successful completion of Introduction to Programming for Data Science (DS 5010) and Introduction to Linear Algebra and Probability for Data Science (DS 5020). Introducing the latest technologies in speech and language processing, including speech and recognition and understanding, keyword spotting, spoken language processing, speaker identification and verification, statistical machine translation, information retrieval, and other interesting topics. Prerequisites: a foundational course in machine learning including, but not limited to, EECS 5327 or EECS 6327. Finally, we will consider some issues in “high-level” vision systems. AI for computer games and virtual humans, Profile Topics include machine learning, statistics, computer vision, natural language processing, and robotics. Knowledge representation and reasoning, autonomous agents and multi-agent systems, and cognitive robotics, Profile Circuits and systems for embedded AI and neuromorphic computing, Profile Algorithms & Data Structure 6. Graduate students who successfully complete the MS degree will be able to: Complete all courses and requirements listed below unless otherwise indicated. Successful completion of the program will prepare graduates with strong analytical skills that are able to effectively work in a variety of settings. This course will introduce concepts in Robotics. AI planning, planning in hybrid systems, knowledge representation including causality, reinforcement learning for planning, Profile MTech in CS with specialization in AI may be done with a thesis or without a thesis (with Capstone Project). Master of Science in Engineering in Robotics with a Specialization in Artificial Intelligence and Machine Learning UPenn has continued to develop the field of Computer Science through: Institute for Research in Cognitive Science in 1990 Prerequisites: introductory courses in artificial intelligence. An honors degree in Computer Science or equivalent, with at least a B+ average in the last two years of study. The PDF will include all information unique to this page. This course will introduce the basic concepts in Computer Vision. Data Science, MS Artificial Intelligence Specialization Advances in machine learning algorithms, growth in computer processing power, and access to large volumes of data make artificial intelligence possible. 1. The Graduate Record Examination (GRE) general test is strongly recommended, especially for applicants who did their work outside of Canada and/or the United States. Programming CIS 200 Computer Science II. implications of AI. Prerequisites: an introductory course on first-order logic. It also focuses on methods and models for efficient communication of data results through data visualization. 2020-21 Undergraduate PDF Artificial Intelligence includes the study of AI principles and techniques, as well as foundational material on topics such as logic, probability, and language. The program delivers the foundational knowledge you’ll need to explore both key contextual areas and complex technical applications of AI systems. Overview of MCS in Computer Science (Applied Artificial Intelligence) course at U Ottawa, i.e., University of Ottawa with upcoming application deadlines, average profile of … Artificial Intelligence (AI) Artificial intelligence (AI) is the most sought after specialization in Computer Science today because it enables computers to perform human tasks such as visual perception, voice recognition, cognitive decision making, pattern recognition et al. To ensure that all students have the foundation necessary to be successful in this program, each incoming student must either complete two introductory courses at Northeastern or complete two placement exams administered one week prior to the beginning of the semester. While AI-based research is still pursued in the general stream of the program, students in this specialization take six graduate courses, of which at least five are within the area of AI, in their first two terms. The main objective of artificial intelligence is to program computers to use example data or experience to solve a given problem.This course discusses AI methods in different fields, including neural networks, signal processing, control, and data mining, in order to present a unified treatment of machine learning problems and solutions. Profile A seminar course that examines statistical approaches to visual motion analysis, including 3-D structure and motion estimation, optical flow, segmentation and tracking using tools like Maximum Likelihood Estimation, Maximum A Posteriori, Least Squares and Expectation Maximization. (416) 736-2100, Students admitted to the Specialization in AI are in the position to apply for institutional and government scholarships, as well as the, Graduate Program in Electrical Engineering & Computer Science, Department of Electrical Engineering and Computer Science, Vector Scholarships in Artificial Intelligence, Three courses from the following list: EECS 5326, EECS 5327, EECS 6127, EECS 6327, EECS 6412, Two other courses from the following list: EECS 5323, EECS 5324, EECS 5326, EECS 5327, EECS 6127, EECS 6322, EECS 6323, EECS 6325, EECS 6327, EECS 6328, EECS 6332, EECS 6333, EECS 6340, EECS 6390A, EECS 6390D, EECS 6412, EECS 6414, A research project that applies AI to a practical problem under the supervision of faculty members and in collaboration with partners in the private or public sector. Our course lets you explore this subject with optional modules in user experience design, autonomous systems, and machine learning. The two exams cover fundamentals of computer science and programming skills and basic statistics, probability, and linear algebra. In the MS in AI degree program, students learn to apply creative thinking, algorithmic design, and coding skills to build modern AI systems.