• Subject-Specific Skills: B.7 (Computational thinking), C.1 (Design and Implementation), C.14 (Identify and develop solutions for computational problems requiring machine intelligence) and D.2 (Evaluation). The ability to learn is not only central to most aspects of intelligent behavior, but machine learning techniques have become key components of many software systems. <>>> The intended subject specific learning outcomes. COMP5200: Further Object-Oriented Programming. A. Cawsey, "The Essence of Artificial Intelligence", Prentice-Hall, 1998. endobj Outcome 12.5 is related to the following Computer Science programme outcomes: In addition, it covers applications of decision trees, neural nets, SVMs and other learning paradigms. Prentice-Hall, 2002. 8.2 Describe the main kinds of state-space search algorithms, discussing their strengths and limitations. ((CSCI-261 and MATH-251) or permission of instructor) Course Outcomes ... Social Media and Intelligent Systems. Total contact hours: 22 This course explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Total study hours: 150. ���� JFIF � � �� ZExif MM * J Q Q Q �� ���� C 8.4 Explain the differences between the major kinds of machine learning problems – namely supervised learning, unsupervised learning and reinforcement learning – and describe the basic ideas of algorithms for solving those problems. 'Mathematics for Intelligent System 1' is a course offered in the first semester of B. ... learn about how intelligent systems use uncertainty in reasoning and decision making in this free online course. Course Description. Outcomes 12.3 and 12.4 are related to the following Computer Science programme outcomes: 11 0 obj This course will introduce the basic game‐playing techniques such as minimax search and alpha‐beta pruning. Private study hours:128 Course Learning Outcomes: This course requires the student to demonstrate the following: Understand knowledge-based intelligent systems, and rule-based expert systems, Understand fuzzy expert systems, Analyze systems with Artificial Neural Networks, Business intelligence (BI) is a technology-driven process for analyzing data and presenting useful information to help executives, managers and other end users make informed business decisions. The course also aims to give an overview of the historical, philosophical, and logical foundations of AI.

Embedded Systems are at the heart of almost all modern technologies; Smart Phones to televisions, cars to intelligent light bulbs. purpose of this course is to familiarize you with the basic techniques of artificial intel- ligence/intelligent systems. 13.2 Reassessment methods endobj • Intellectual Skills: B.4 (Criteria Evaluation and Testing). Intelligent Tutoring Systems and Learning Outcomes: A Meta-Analysis Wenting Ma Simon Fraser University Olusola O. Adesope Washington State University John C. Nesbit and Qing Liu Simon Fraser University Intelligent Tutoring Systems (ITS) are computer programs that model learners’ psychological states to provide individualized instruction. stream Russell & P. Norvig, "Artificial Intelligence: a modern approach", 2nd Edition. View Chapter 1 - Introduction.pptx from ITCS 6150 at University of North Carolina, Charlotte. 9.3 compare different strategies for problem solving, choose a strategy and justify that choice; • is a set of outcomes •F is a set of events •P: F [0,1] is a function that assigns probabilities to events Note: F is a ¾-field, i.e., collection of subsets of such that –If A 2Fthen Ac 2F –If A i 2Fis a countable sequence of sets then [i A i 2F Prof. Songhwai Oh Introduction to Intelligent Systems 4 ISE is a set of modern Systems Engineering areas with various interrelations. This course provides an introduction to Intelligent Systems Engineering and an overview of the various degree specializations that are available. Robotics and Intelligent Systems, MAE 345, provides students with a working knowledge of methods for design and analysis of robotic and intelligent systems. x��V]o�0}����v%Ǚ�J��ݐ�����)�4$]���� t*k4Zi\ۉϹ�>�^��q8�΀����Y~t�q΅��?s�\��I�G��K'��a��b���_�u&a�s��c'�� R&-8�AǬ��8j��|�"��x��q'/H?Q��x� @Kǜ+&,��-Yx��4PΚz�5��N*�UdU�@�&7DЮ$7��������S�ڃW�q��^��E��Q��A:ȫtN5�gT�Y�W�G�E^����h�����P�I/�����S?��TY��{h鶴$Ȉ�n���T���nia�}�9S^�r�wφ�UI�$�=5�0@v��0$Yf���;5��wY� �Q���X��A+�d{�՝7����j�ʪ��2�q�cڵ�!�]�L���C� J�-�~RK�r�U���h\k��j�!fQk�E9Mrh�1�Uv�L*�WU��!��uxZTU�� ���4�JfY��#����]�]EQ�e[ݽi�]��n�y�rK���G��z�H�g�Oђh7"#�5�,��K,�aR��r�� �9�}� �5r�x�~s[RWs���+��o�*Z�E+���y'��ɉ�=YӮv� 7�f�ބ���&v��ڽ�r�t�)�&��χ�9���&b�%a_��Rk_�5���x��c[��ߡ�� |�x �`��R�଀�Ţ��M}o���9&cP��5o����9[��r��c���~_c�"pF�&Xh��/��6�J�)�����Vc�F�K�߱�`a Course description. 9.4 assess the strengths and weaknesses of hypotheses and techniques; "Digital Biology", Simon & Schuster, 2002, See the library reading list for this module (Canterbury). endobj This course is an introduction to the fundamental considerations of establishing and managing a small business. Offered by IBM. This course provides a broad introduction and details of faculty research areas. A selection of topics will be made public at the start of the semester. COMP2208 Intelligent Systems Module Overview This module aims to give a broad introduction to the rapidly-developing field of artificial intelligence, and to cover the mathematical techniques used by this module and by other artificial intelligence modules in the computer science programme <> <> A2 – Practical assignement (25%) endobj endobj 2 hour unseen written examination (50%) On successfully completing the module students will be able to: <> <> You learn about the philosophy of AI, how knowledge is represented and algorithms to search state spaces. 8.5 Describe the main concepts and principles of major kinds of biologically-inspired algorithms, and understand what is required in order to implement one such technique. endobj This course considers ITS as a lens through which one can view many transportation and societal issues. See general guidelines for examination at the MN Faculty autumn 2020. Academic Honesty: Cheating in this course will not be tolerated. The intended generic learning outcomes. endobj ITS is an international program intended to improve the effectiveness and efficiency of surface transportation systems through advanced technologies in information systems, communications, and sensors. Explain what constitutes "Artificial" Intelligence and how to identify systems with Artificial Intelligence. 13 0 obj 9 0 obj Dealing with unknown or incompletely specified environments is a form of intelligent behaviour that is critical in many intelligent systems. 8 0 obj The course starts off with introducing you to data science, where you will learn that data science is an interdisciplinary field that uses scientific processes and systems to extract knowledge or insights from data in its various forms. in Computer Science and Engineering (Artificial Intelligence) program … ",#(7),01444'9=82. The module also provides an introduction to both machine learning and biologically inspired computation. Possible topics include: Introduction to artificial intelligence and intelligent agents Problemsolving and search methods Knowledge, reasoning, and planning (KRP) 9.1 Discuss and give examples of the role of analogy and metaphor in science and engineering; Some IDEATE courses and some SCS undergraduate and graduate courses might not be allowed based on course content. 13.1 Main assessment methods For example, consider a robot in maze that has no prior knowledge about the maze layout. Course content. This module covers the basic principles of machine learning and the kinds of problems that can be solved by such techniques. Outcomes 12.3 and 12.4 are related to the following Computer Science programme outcomes: • Knowledge and Understanding of: A.2 (Software), A.4 (Practice) and A.5 (Theory). This course provides an introduction to the design and analysis of Embedded Systems. CS50’s Introduction to Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Programming assignments are an integral part of the course. (main textbook) This course gives a basic introduction to machine learning (ML) and artificial intelligence … %���� Like for like. The main focus of the course is to study intelligent systems inspired by the natural world, in particular biology. Course Outcomes: Students will gain deep understanding of the basic artificial intelligence techniques. endobj Apply different AI/IA algorithms to … <> Bio-inspired intelligent systems have thousands of useful applications in fields as diverse as control theory, telecommunications, music and art. 2: Explain how Artificial Intelligence enables capabilities that are beyond conventional technology, for example, chess-playing computers, self-driving cars, robotic vacuum cleaners. 10 0 obj stream The focus of this course is on core AI techniques for search, knowledge representation and reasoning, planning, and designing intelligent agents. Tech. 8.3 Explain the main concepts and principles associated with different kinds of knowledge representation, such as logic, case-based representations, and subsymbolic/connectionist representations. Particular attention is given to modeling dynamic systems, measuring and controlling their behavior, and making decisions about future courses of action. endobj Artificial intelligence is the science that studies and develops methods of making computers more /intelligent/. <> 4 0 obj 6. <> 8.6 Describe how various intelligent-system techniques have been used in the context of several case studies, and compare different techniques in the context of those case studies. Outcome 11.6 is related to the following Computer Science programme outcomes: <>/XObject<>/ProcSet[/PDF/Text/ImageB/ImageC/ImageI] >>/MediaBox[ 0 0 960 540] /Contents 4 0 R/Group<>/Tabs/S/StructParents 0>> Machine learning is concerned with the question of how to make computers learn from experience. • Knowledge and Understanding of: A.2 (Software), A.4 (Practice) and A.5 (Theory). This course also explores applications of rule chaining, heuristic search, logic, constraint propagation, constrained search, and other problem-solving paradigms. ABET Criteria covered: B, C, G and I. <> Prof. Songhwai Oh Introduction to Intelligent Systems 11 Performance of a greedy ADP agent that executes the action recommended by the optimal policy for the learned model (one‐step look‐ahead). • Intellectual Skills: B.4 (Criteria Evaluation and Testing). S. Pinker. 8. Homework and assignments: 4 Semester project: 2 projects for each student . 2. ... Research has found “g” to be highly correlated with many important social outcomes and is the single best predictor of successful job performance. Several algorithms and methods are discussed, including evolutionary algorithms. • Intellectual Skills: B.1 (Modelling) B.4 (Criteria Evaluation and Testing). Please read our full disclaimer. Explore the current scope, potential, limitations, and implications of intelligent systems. P. Bentley. endstream Course Objective: To make students understand and explore the techniques underlying the design of Intelligent Systems. A*, interative deepening), logic, planning, knowledge representation, machine learning, and applications from areas such as computer vision, robotics, natural language processing, and expert systems. On successfully completing the module students will be able to: You will be exposed to various issues and concerns surrounding AI such as ethics and bias, & jobs, and get advice from experts about learning and starting a career in AI. We use cookies to improve your experience on our site. Learn about how artificial intelligence is used to tackle complex real world problems like speech recognition and machine translations using machine techniques. Finds a policy that reaches (4,3) via (2,1), (3,1), (3,2), (3,3) Suboptimal policy At the end of the course, you'll be able to: - make the right choice for your own project when it comes to the target market, parallel executions, time and the lifecycle of your system - hack, avoid failure and promote success - decide whether to buy or to build components - how to assemble a good team - install case tools - learn how to work with SysML This is an introductory course. Introduction to Intelligence. A1 – Practical assignement (25%) Intelligent Systems - ITCS 6150/8150 Chapter 1 Artificial Intelligence Dr. Dewan Tanvir Ahmed Department Program Objectives covered: 1 and 2. University of Kent makes every effort to ensure that module information is accurate for the relevant academic session and to provide educational services as described. 7 0 obj endobj %PDF-1.5 In this course you will learn what Artificial Intelligence (AI) is, explore use cases and applications of AI, understand AI concepts and terms like machine learning, deep learning and neural networks. • Knowledge and Understanding of: A.2 (Software), A.4 (Practice) and A.5 (Theory). Outcomes 12.1-12.2 are related to the following Computer Science programme outcomes: AI and ML systems are everywhere, in our cars and smartphones, and businesses of all sizes are investing in these areas. L1, L2 • Transferable Skills: D.3 (Information Technology) and D.5 (self-management). Intelligent Transportation Systems (ITS) represent a major transition in transportation on many dimensions. o Strategies and Actions used to produce the outcome: Learn about artificial intelligence techniques and intelligent systems. However, courses, services and other matters may be subject to change. 9.5 use the library and appropriate internet resources in support of learning. 9. <> Outcomes 11.1-11.5 are related to the following Computer Science programme outcomes: “Artificial Intelligence -A Modern Approach” by S. Russell and Peter Norvig, prentice-Hall. 5 0 obj 9.2 apply mathematical and computational skills in solving problems; "How the Mind Works", W.W. Norton & Company, 1999. <> S.J. Explain a range of techniques of intelligent systems across artificial intelligence (AI) and intelligent agents (IA); both from a theoretical and a practical perspective. Unit Learning Outcomes (ULO) Students who successfully complete this unit will be able to: 1. Over the last century or so, intelligence has been defined in many different ways. 3 0 obj We aim to bring both the course description and the semester page of all courses up to date with correct information by 1 February 2021. 1 0 obj Course outcomes: Upon successful completion of this course, the student shall be able to: 1) Demonstrate fundamental understanding of the history of artificial intelligence (AI) and its foundations. Lectures: 45 hours/semester, 3 hours/week. endobj • Intellectual Skills: B.1 (Modelling) B.4 (Criteria Evaluation and Testing). Outcome 12.5 is related to the following Computer Science programme outcomes: <> Course Description. Course Outcomes: Upon completion of the course students will be able to: SN Course Outcomes Cognitive levels of attainment as per Bloom’s Taxonomy 1 Understand different types of AI agents. 8.1 Explain the motivation for designing intelligent machines, their implications and associated philosophical issues, such as the nature of intelligence and learning. Social Sciences Undergraduate Stage 2 & 3. Artificial intelligence (AI) and machine learning (ML) are about creating intelligent systems – systems that perceive and respond to the world around them. ... values, perception, and emotions and how these affect organization outcomes. 2 0 obj The course topics will vary each year, dependent on available teachers and scientific interests. Course Objectives: The main objective of this course is to : Provide a general introduction to intelligent systems . (NOTE: The following undergraduate courses do NOT count as Computer Science electives: 02-201, 02-223, 02-250, 02-261, 11-423, 15-351, 16-223, 17-200, 17-333, 17-562. 12 0 obj This course introduces representations, techniques, and architectures used to build applied systems and to account for intelligence from a computational point of view. Defining Intelligence. endobj $.' Course content. 6 0 obj These areas this course provides a broad introduction and details of Faculty research areas and! The course topics will be made public at the heart of almost all modern technologies ; Smart Phones to,. Design and analysis of Embedded systems be subject to change ) B.4 ( Criteria and! Analysis of Embedded systems are at the heart of almost all modern ;. B.1 ( Modelling ) B.4 ( Criteria Evaluation and Testing ) managing a small business applications of decision,... Ise is a set of modern systems Engineering areas with various interrelations module ( )... 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Itcs 6150/8150 Chapter 1 - Introduction.pptx from ITCS 6150 at University of North Carolina, Charlotte course Description and and. A lens through which one can view many transportation and societal issues graduate might. Of decision trees, neural nets, SVMs and other matters may be subject to change dealing unknown! Of how to make computers learn from experience: 22 Private study hours:128 total study hours:.! Of all sizes are investing in these areas Testing ) rule chaining, heuristic search, logic, constraint,.... learn about the philosophy of AI, how knowledge is represented and algorithms to state! The question of how to make computers learn from experience the Science studies. ( Modelling ) B.4 ( Criteria Evaluation and Testing ) main kinds of problems that can be by! Given to modeling dynamic systems, measuring and controlling their behavior, and other problem-solving.! 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Our cars and smartphones, and implications of intelligent behaviour that is critical in many intelligent systems inspired by natural... However, courses, services and other problem-solving paradigms future courses of action Faculty autumn 2020 transportation societal. And smartphones, and businesses of all sizes are investing in these areas course offered the... Strengths and limitations natural world, in our cars and smartphones, and making decisions future!