Courses tagged with "Computer Science" (11)

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Starts : 2016-06-13
No votes
edX Free Engineering English Computer Science EdX ETHx Math Science

Robots are rapidly evolving from factory workhorses, which are physically bound to their work-cells, to increasingly complex machines capable of performing challenging tasks in our daily environment. The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is put on mobile robot locomotion and kinematics, environment perception, probabilistic map based localization and mapping, and motion planning. The lectures and exercises of this course introduce several types of robots such as wheeled robots, legged robots and drones.

This lecture closely follows the textbook Introduction to Autonomous Mobile Robots by Roland Siegwart, Illah Nourbakhsh, Davide Scaramuzza, The MIT Press, second edition 2011.

Starts : 2015-05-05
No votes
edX Free Engineering English Computer Science EdX TUMx

In recent years, flying robots such as miniature helicopters or quadrotors have received a large gain in popularity. Potential applications range from aerial filming over remote visual inspection of industrial sites to automatic 3D reconstruction of buildings. Navigating a quadrotor manually requires a skilled pilot and constant concentration. Therefore, there is a strong scientific interest to develop solutions that enable quadrotors to fly autonomously and without constant human supervision. This is a challenging research problem because the payload of a quadrotor is uttermost constrained and so both the quality of the onboard sensors and the available computing power is strongly limited. 

In this course, we will introduce the basic concepts for autonomous navigation for quadrotors. The following topics will be covered:

  • 3D geometry,
  • probabilistic state estimation,
  • visual odometry, SLAM, 3D mapping,
  • linear control.

In particular, you will learn how to infer the position of the quadrotor from its sensor readings and how to navigate it along a trajectory.

The course consists of a series of weekly lecture videos that we be interleaved by interactive quizzes and hands-on programming tasks. For the flight experiments, we provide a browser-based quadrotor simulator which requires the students to write small code snippets in Python.

This course is intended for undergraduate and graduate students in computer science, electrical engineering or mechanical engineering. This course has been offered by TUM for the first time in summer term 2014 on EdX with more than 20.000 registered students of which 1400 passed examination. The MOOC is based on the previous TUM lecture “Visual Navigation for Flying Robots” which received the TUM TeachInf best lecture award in 2012 and 2013.


Do I need to buy a textbook?

No, all required materials will be provided within the courseware. However, if you are interested, we recommend the following additional materials:

  1. This course is based on the TUM lecture Visual Navigation for Flying Robots. The course website contains lecture videos (from last year), additional exercises and the full syllabus:
  2. Probabilistic Robotics. Sebastian Thrun, Wolfram Burgard and Dieter Fox. MIT Press, 2005.
  3. Computer Vision: Algorithms and Applications. Richard Szeliski. Springer, 2010.

Do I need to build/own a quadrotor?

No, we provide a web-based quadrotor simulator that will allow you to test your solutions in simulation. However, we took special care that the code you will be writing will be compatible with a real Parrot Ardrone quadrotor. So if you happen to have a Parrot Ardrone quadrotor, we encourage you to try out your solutions for real.

Starts : 2014-09-20
115 votes
Coursera Free Closed [?] Computer Sciences English Computer Science Engineering Systems & Security

In this course, you will learn to design the computer architecture of complex modern microprocessors.

13 votes
Udemy Free Closed [?] Engineering Computer Architecture Computer Science Systems & Security Technology

Lecture Series on Computer Architecture by Prof. Anshul Kumar, Department of Computer Science & Engineering ,IIT Del

Starts : 2014-01-20
106 votes
Coursera Free Closed [?] Computer Sciences English Artificial Intelligence Computer Science Engineering

Learn about how to make mobile robots move in effective, safe, predictable, and collaborative ways using modern control theory.

5 votes Free Closed [?] Engineering Computer Architecture Computer Science Systems & Security Technology

Modern computer technology requires an understanding of both hardware and software, as the interaction between the two offers a framework for mastering the fundamentals of computing. The purpose of this course is to cultivate an understanding of modern computing technology through an in-depth study of the interface between hardware and software. In this course, you will study the history of modern computing technology before learning about modern computer architecture and a number of its important features, including instruction sets, processor arithmetic and control, the Von Neumann architecture, pipelining, memory management, storage, and other input/output topics. The course will conclude with a look at the recent switch from sequential processing to parallel processing by looking at the parallel computing models and their programming implications.

Starts : 2015-10-19
100 votes
Coursera Free Engineering English Artificial Intelligence Computer Science Mathematics

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

Starts : 2016-01-04
116 votes
Coursera Free Closed [?] Computer Sciences English Artificial Intelligence Computer Science Engineering Mathematics

In this class you will look behind the scenes of image and video processing, from the basic and classical tools to the most modern and advanced algorithms.

Starts : 2017-02-20
No votes
edX Free Engineering English Computer Science EdX Electronics TsinghuaX

Principles of Electric Circuits (20220214x) is one of the kernel courses in the broad EECS subjects. Almost all the required courses in EECS are based on the concepts learned in this course, so it’s the gateway to a qualified EECS engineer.

The main content of this course contains linear and nonlinear resistive circuits, time domain analysis of the dynamic circuits, and the steady state analysis of the dynamic circuits with sinusoidal excitations. Important concepts, e.g. filters, resonance, quiescent point, etc., cutting-edge elements, e.g. MOSFETs and Op Amps, etc., systematic analyzing tools, e.g. node method and phasor method, etc., and real-world engineering applications, e.g. square wave generator and pulse power supply for railgun, etc., will be discussed in depth.

In order to facilitate the learning for students with middle school level, we prepare the necessary knowledge for calculus and linear algebra in week 0. With your effort, we can show you the fantastic view of electricity.

Starts : 2014-06-30
102 votes
Coursera Free Computer Sciences English Computer Science Systems & Security

Examines key computational abstraction levels below modern high-level languages. From Java/C to assembly programming, to basic processor and system organization.

Starts : 2015-02-02
118 votes
Coursera Free Computer Sciences English Computer Science Engineering Systems & Security

A modern VLSI chip has a zillion parts -- logic, control, memory, interconnect, etc.  How do we design these complex chips?  Answer: CAD software tools.  Learn how to build these tools in this class.