Course Components This course consists of the following components: This foundation is enriched through the exploration of current research on a range of topics including visual recognition, audition and speech, natural language understanding, robotics and motor control, cognitive development, social cognition, machine learning and Bayesian inference, and visual and spatial memory.
Resources are also provided to support hands-on computer activities to study methods of modeling and data analysis in greater depth. Useful background is noted within each topical unit. Additional materials, including from later years, are at the Brains, Minds and Machines Summer Course website.
Some lectures are accessible to a broad audience, while others require deeper background in areas such as mathematics or machine learning. Prerequisites and Preparation This course for graduate students and advanced undergraduates is intended for people with basic knowledge in the following areas, at an undergraduate level: Introduction to computer programming, machine learning Introduction to neuroscience Introduction to psychology or cognitive science Lectures vary in the depth of background needed to understand the main concepts and results.
Download Resource Materials Course Meeting Times This course met for an intensive 3 week period, with a mix of lecture, tutorial and project work segments.
Through lectures by leading researchers in the field, you learn about the theoretical foundations and computational methods used in intelligence research; empirical methods used in neuroscience and cognitive science to probe the function of neural circuits and emergent behavior; the kinds of questions that can be addressed with computational and empirical methods and how the integration of multiple perspectives can accelerate the pace of intelligence research.
Calculus, linear algebra, probability and statistics Computation: These topics are organized into curricular units that are somewhat independent, allowing flexibility in the order and extent to which the topics are studied.
Course Overview This course introduces you to the scientific study of intelligence in brains and machines.Syllabus – Summer (Session B Online) Instructor: Dave Heckman Section: & syllabus and the deadlines on MyMathLab, but if you do not have material finished by the due dates, then you Microsoft Word - MAT Syllabus - Summer B - Online.
Syllabus Resource Home Syllabus The materials in this open-licensed OCW resource come from the version of the Brains, Minds and Machines Summer Course. Additional materials, including from later years, are at the Brains.
SYLLABUS FOR STATISTICS A - LECTURE 2 SUMMER SESSION C Instructor: Nicolas Christou O ce: Math Sciences Bldg. Telephone: () SUMMER ALL SECTIONS 1 BASIC COMPUTER SKILLS COURSE SYLLABUS: BIBI AND BI Richard D.
Blamer Department of Management, Marketing and Logistics Boler School of Business BI Introduction to Spreadsheets: will give you an overview of electronic spreadsheets, with an emphasis on problem solving.
HESF - Summer I 10W - Fitness and Wellness Course Description This course is designed to teach and apply the principles of lifetime physical fitness, utilizing the five major components of cardio-respiratory endurance, muscular strength, muscular endurance, flexibility and body composition.
View Notes - SpringSummer CCRM Syllabus from CRM at Ryerson University.
CCRM Understanding Crime in Canada Course Outline Spring INSTRUCTOR: INSTRUCTOR PHONE: INSTRUCTOR CRM - Summer CCRM essay structure. 12 pages. _Control Theory and Differential Assoc Ryerson University CRM - SummerDownload