Computer Science: Artificial Intelligence, Robotics, Vision

 

 


 


Master Computer Science on Coursera




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Dec 5th 2016

Case Studies: Analyzing Sentiment & Loan Default Prediction
In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank.

Average: 8 (3 votes)
Dec 5th 2016

¿Te interesa la visión por computador? ¿Te gustaría conocer qué métodos puedes utilizar para detectar y reconocer objetos en una imagen? En este curso te introducirás en los principios básicos de cualquier sistema automático de detección y reconocimiento de objetos en imágenes. A lo largo del curso analizaremos diferentes métodos de representación y clasificación que te permitirán abordar casos de aplicación de complejidad creciente.

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Dec 5th 2016

An introduction to data integration and statistical methods used in contemporary Systems Biology, Bioinformatics and Systems Pharmacology research. The course covers methods to process raw data from genome-wide mRNA expression studies (microarrays and RNA-seq) including data normalization, differential expression, clustering, enrichment analysis and network construction. The course contains practical tutorials for using tools and setting up pipelines, but it also covers the mathematics behind the methods applied within the tools.

Average: 5.3 (3 votes)
Nov 28th 2016

Explore how to integrate works of art into your classroom with inquiry-based teaching methods originally developed for in-gallery museum education.

Average: 9 (5 votes)
Nov 28th 2016

How can robots determine their state and properties of the surrounding environment from noisy sensor measurements in time? In this module you will learn how to get robots to incorporate uncertainty into estimating and learning from a dynamic and changing world. Specific topics that will be covered include probabilistic generative models, Bayesian filtering for localization and mapping.

Average: 1 (2 votes)
Nov 21st 2016

Control of Mobile Robots is a course that focuses on the application of modern control theory to the problem of making robots move around in safe and effective ways. The structure of this class is somewhat unusual since it involves many moving parts - to do robotics right, one has to go from basic theory all the way to an actual robot moving around in the real world, which is the challenge we have set out to address through the different pieces in the course.

Average: 5.7 (3 votes)
Nov 21st 2016

How can robots use their motors and sensors to move around in an unstructured environment? You will understand how to design robot bodies and behaviors that recruit limbs and more general appendages to apply physical forces that confer reliable mobility in a complex and dynamic world. We develop an approach to composing simple dynamical abstractions that partially automate the generation of complicated sensorimotor programs.

Average: 6.7 (3 votes)
Nov 21st 2016

Discover the world of mobile robots - how they move, how they interact with the world, and how to build them! From the surface of Mars to your living room floor, mobile robots can be found in some surprising places. Together we’ll explore how and why. We’ll look at how robots move, how they sense the world around them and how they make decisions. Then we’ll put all this together and apply what we’ve learned to build our own mobile robot.

Average: 6.6 (8 votes)
Nov 21st 2016

Robotic systems typically include three components: a mechanism which is capable of exerting forces and torques on the environment, a perception system for sensing the world and a decision and control system which modulates the robot's behavior to achieve the desired ends. In this course we will consider the problem of how a robot decides what to do to achieve its goals.

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Nov 21st 2016

How can we create agile micro aerial vehicles that are able to operate autonomously in cluttered indoor and outdoor environments? You will gain an introduction to the mechanics of flight and the design of quadrotor flying robots and will be able to develop dynamic models, derive controllers, and synthesize planners for operating in three dimensional environments.

Average: 9 (2 votes)
Nov 21st 2016

This course provides an introduction to basic computational methods for understanding what nervous systems do and for determining how they function. We will explore the computational principles governing various aspects of vision, sensory-motor control, learning, and memory.

Average: 7.8 (4 votes)
Nov 21st 2016

Explore key ideas in game design, programming, architecture, game engines, player experience and game AI. There are lots of different skills that go into game development. This subject is about key technical concepts in game development, and has been developed for people of many different backgrounds and skills. Some programming experience would be nice but is not required. We start by looking at the central role of game design and common development processes used in the industry. You will see how game software can be broken into parts that work together, and in particular the idea of game engines. We’ll explore the relationship between game design, balance and player experience. Lastly we’ll look at enhancing player experience though the use of AI techniques.

Average: 7.7 (10 votes)
Nov 21st 2016

About this course: Popularized by movies such as "A Beautiful Mind", game theory is the mathematical modeling of strategic interaction among rational (and irrational) agents. Over four weeks of lectures, this advanced course considers how to design interactions between agents in order to achieve good social outcomes. Three main topics are covered: social choice theory (i.e., collective decision making and voting systems), mechanism design, and auctions.

Average: 6 (4 votes)
Nov 14th 2016

Learn the fundamentals of digital signal processing theory and discover the myriad ways DSP makes everyday life more productive and fun.

Average: 7 (3 votes)
Nov 14th 2016

¿Te gustaría construir un robot y controlarlo a través de tu celular? ¡Estás en el curso indicado! Aquí podrás armar y animar un robot además de controlarlo con tu teléfono móvil, aún cuando te encuentres lejos de éste.

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Nov 14th 2016

本課程有兩大課程目標: 1. 使同學了解如何以搜尋達成人工智慧 2. 使同學能將相關技術應用到自己的問題上

Average: 10 (1 vote)
Nov 7th 2016

How do you feel about robots? Learn how robotics is used today and explore how it might help solve the big issues of our time. Once only found in fiction, robots are being applied in an increasing array of ways in society, from mechanisation of industrial tasks to exploring places humans can’t go. This course starts with your perceptions of robotics, describes different types of robots, and leads into a discussion of the future: knowing we can use robots, should we?

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Self-Paced

Is AI humanity's savior, or do the threats outweigh its benefits? Best-selling author and Data Editor of The Economist Kenneth Cukier uncovers how to be prepared for the next phase of human evolution.

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Oct 3rd 2016

Tired of solving Sudokus by hand? This class teaches you how to solve complex search problems with discrete optimization, including constraint programming, local search, and mixed-integer programming.

Average: 10 (1 vote)
Oct 3rd 2016

How can we make robots see like we do? Learn how we make robots perceive the world around them in this exciting six-week course, delivered by Professor Peter Corke. Robotic Vision introduces you to the field of computer vision and the mathematics and algorithms that underpin it. You'll learn how to interpret images to determine the colour, size, shape and position of objects in the scene.We'll work with you to build an intelligent vision system that can recognise objects of different colours and shapes.

Average: 9.8 (4 votes)

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