AI News, BOOK REVIEW: Computer Science, Advanced Artificial Intelligence, Second Cycle, 7 ... artificial intelligence

Centre for Doctoral Training in Data Science and Artificial Intelligence

The CDT recognises that if researchers in this area wish to be leaders in AI and shape the technology landscape, they must be deeply conversant in both data science and AI.

Almost every activity in science, society and commerce now relies on data-driven decision making --- from large data analytics in biology to small companies deploying data-collecting apps to millions of customers.

The great recent successes of modern AI, such as object recognition and game playing, are based on data-driven approaches rooted in machine learning and deep networks.

Our programme will allow you to specialise and perform advanced research at the interface of Data Science and AI and gain breadth and practical experience throughout the field.

2019-2020 Undergraduate Calendar - Computer Science

APPLIED COMPUTING COURSES *APCO 1P00 Introduction to Media Computation (also offered as IASC 1P00) Programming by example, encoding and manipulating pictures (such as grayscale and colour replacement), pixel manipulation (such as red eye and mirroring), designing and debugging, text manipulation with HTML, file processing, automatic generation and manipulation of web pages, and sound processing (such as encoding, volume manipulation and splicing).

Topics include representation of information, current hardware, software and network technologies, modelling with Excel, presentations with PowerPoint, Internet searching and basic web page development with HTML.

#APCO 1P30 Programming for Interactive Media (also offered as IASC 1P30) Introduction to contemporary programming syntax including for classes, functions, properties and events for developing interactive media applications.

*APCO 1P93 Applied Programming (also offered as IASC 1P93) Modern software techniques including problem solving and design of effective algorithms, structured program design methodology, subprogram library usage, documentation, correctness, floating-point arithmetic and error analysis.

Topics include CPUs, memory, video, input/output, networks, security, installation of operating systems and hands-on trouble shooting.

#APCO 2P60 Web 2.0 Content, Construction, Collaboration (also offered as IASC 2P60) Context and topics in web-based interactive environments, communities and social networks designed for sharing content, user interaction and collective intelligence.

Processing and management of images and other media assets, structuring websites, development tools and applications, web hosting and dissemination strategies.

Topics include XML and SGML, database connectivity and forms handling, basic animation, graphics optimization for the Web, scripting, advanced searching and Web design for accessibility.

Note: students may propose their own projects for departmental approval or may apply for a project proposed by a faculty member.

Prerequisite(s): two credits from APCO (minimum 60 percent), COSC (minimum 60 percent), IASC (minimum 60 percent) or permission of the instructor.

Topics include computer fundamentals, representation of information, problem solving and software development, programming language syntax and semantics, methods, input/output, control structures and data types.

Students with considerable prior programming experience in a high-level language such as Pascal, Java, C++ or Ada may be granted exemption from this course at the discretion of the Chair.

COSC 2P03 Advanced Data Structures Implementation and use of advanced data structures including trees, graphs, hash tables and advanced list structures, sorting and searching, recursion and traversals.

COSC 2P05 Programming Languages Fundamental concepts of programming languages including syntax, semantics, program translation, virtual machines, control, data types, multi-threading, exception handling and abstraction mechanisms.

Prerequisite(s): COSC 2P03 (minimum 60 percent) and COSC 2P12 (minimum 60 percent) for COSC (single or combined), BCB, CAST, CNET and NEUR neurocomputing majors;

Topics include XML and SGML, database connectivity and forms handling, basic animation, graphics optimization for the Web, scripting, advanced searching, Web design for accessibility.

Approaches to building models, using texturizing, lighting, cameras and rendering as well as basic animation techniques.

Relevant historical and theoretical perspectives on 3D and virtuality situating 3D within creative process and broader critical practices in cultural production.

Restriction: open to COSC (single or combined), IASC (single or combined), STAC, VISA (single or combined) and VISA (Honours)/BEd (Intermediate/Senior) majors until date specified in Registration guide.

Prerequisite(s): one of four COSC credits, IASC 1F01 (1F00), one credit from VISA 1P93 (minimum 60 percent), 1P94 (minimum 60 percent), 1P95 (minimum 60 percent), 1P96 (minimum 60 percent).

Topics include asymptotic notations, solving recurrences, order statistics, general algorithm design techniques such as divide-and-conquer, greedy algorithms, dynamic programming, backtracking and branch-and-bound.

COSC 3P91 Advanced Object-Oriented Programming Topics may include graphical user interfaces, animation, sound, music, networking, parallelism, client-server and XML using game design as an example.

COSC 3P92 Computer Architecture Topics include buses, internal and external memory, I/O and interfacing, computer arithmetic, instruction sets, RISCs, microprogrammed control, parallel organization.

Prerequisite(s): two credits from APCO (minimum 60 percent), COSC (minimum 60 percent), IASC (minimum 60 percent) or permission of the instructor.

COSC 3P98 Computer Graphics Topics include 2-D and 3-D graphics, curve and surface fitting, light and colour models, real time interfaces, animation and hardware issues (knowledge of C assumed).

Additional components typically include a site visit, a work term report and an employer performance evaluation.

Topics include team organization, software project management, software life-cycle, software development and management tools, and design notations.

Team project including application of organizational paradigm, management model, life-cycle model, tools, design notation, implementation, testing and debugging of a major software system.

Restriction: open to COSC (single or combined), BCB, CAST and CNET majors with a minimum 75 percent major average, a minimum 10.0 overall credits and permission of project co-ordinator.

Topics include process and thread management, interprocess communication, synchronization and scheduling, multiprocessing, device drivers, kernel memory management, distributed and advanced file systems and STREAMS (knowledge of C assumed).

COSC 4P14 Computer Networks Advanced topics in computer networking, including computer network security, wireless and high-speed networking, computer network management and performance evaluation.

Topics include all data types, type inference, pattern-matching, recursion, polymorphism, higher-order functions, lazy vs eager evaluation, modules and monads.

Topics include algebraic specifications, semantics of programming languages, Hoare/dynamic logic, specification languages, program transformation.

*COSC 4P61 Theory of Computation (also offered as MATH 4P61) Regular languages and finite state machines: deterministic and non-deterministic machines, Kleene's theorem, the pumping lemma, Myhill-Nerode Theorem and decidable questions.

Context-free languages: generation by context-free grammars and acceptance by pushdown automata, pumping lemma, closure properties, decidability.

Prerequisite(s): COSC 2P03 (minimum 60 percent), 2P05 (minimum 60 percent) and 2P12 (minimum 60 percent) or permission of the instructor.

COSC 4P76 Machine Learning Fundamental machine learning techniques with emphasis on using these techniques to design and implement small practical learning systems.

Topics include learning as a search, inductive bias, concept learning, computational learning, explanation-based learning and reinforcement learning.

Topics include robot components and subsystems, sensors and perception, object location and manipulation, mobile robot navigation, task planning, control architectures, adaptive and social behaviour.

Formal systems such as propositional modal logics and grammars, models of probability, Bayesian reasoning, fuzzy sets, rough sets, concept lattices and knowledge structures.

COSC 4P98 Topics in Computer Media and Digital Audio Fractals, digital audio fundamentals, Fourier analysis, MIDI, computer composition, music and sound processing and user interfaces.

COSC 2C01 Co-op Reflective Learning and Integration I Provide student with the opportunity to apply what they've learned in their academic studies through career-oriented work experiences at employer sites.

Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.

COSC 2C02 Co-op Reflective Learning and Integration II Provide student with the opportunity to apply what they've learned in their academic studies through career-oriented work experiences at employer sites.

Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.

COSC 2C03 Co-op Reflective Learning and Integration III Provide student with the opportunity to apply what they've learned in their academic studies through career-oriented work experiences at employer sites.

Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.

COSC 2C04 Co-op Reflective Learning and Integration IV Provide student with the opportunity to apply what they've learned in their academic studies through career-oriented work experiences at employer sites.

Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.

COSC 2C05 Co-op Reflective Learning and Integration V Provide student with the opportunity to apply what they've learned in their academic studies through career-oriented work experiences at employer sites.

Note: students will be required to prepare learning objectives, participate in a site visit, write a work term report and receive a successful work term performance evaluation.

Center for the Governance of AI - Future of Humanity Institute

Our focus is on the political challenges arising from transformative AI: advanced AI systems whose long-term impacts may be as profound as the industrial revolution.

The Center seeks to guide the development of AI for the common good by conducting research on important and neglected issues of AI governance, and advising decision makers on this research through policy engagement.

The Center produces research which is foundational to the field of AI governance, for example mapping crucial considerations to direct the research agenda, or identifying distinctive features of the transition to transformative AI and corresponding policy considerations.

How smart is today's artificial intelligence?

Current AI is impressive, but it's not intelligent. Subscribe to our channel! Sources: ..

The 7 Steps of Machine Learning (AI Adventures)

How can we tell if a drink is beer or wine? Machine learning, of course! In this episode of Cloud AI Adventures, Yufeng walks through the 7 steps involved in ...

What is Artificial Intelligence (or Machine Learning)?

What is AI? What is machine learning and how does it work? You've probably heard the buzz. The age of artificial intelligence has arrived. But that doesn't mean ...

Best Laptop for Machine Learning

What kind of laptop should you get if you want to do machine learning? There are a lot of options out there and in this video i'll describe the components of an ...

11. Introduction to Machine Learning

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: Instructor: Eric Grimson ..

Alan Turing: Crash Course Computer Science #15

Today we're going to take a step back from programming and discuss the person who formulated many of the theoretical concepts that underlie modern ...

Overcome cybersecurity limitations with artificial intelligence

The evolution of cybersecurity threats are limited by two factors. Learn how the augmentation of security operations by artificial intelligence can create ...

What is machine learning and how to learn it ?

Machine learning is just to give trained data to a program and get better result for complex problems. It is very close to data ..