Online courses directory (548)

Lecture - 24 GraphsrnLecture Series on Data Structures and Algorithms by Dr. Naveen Garg, Department of Computer Science

Lecture Series on Database Management System by Prof.D.Janakiram, Department of Computer Science and Engineering, IIT Ma

Lecture Series on Design & Analysis of Algorithms by Prof.Abhiram Ranade, Department of Computer Science Engineering

CS101 teaches the essential ideas of Computer Science for a zero-prior-experience audience. The course uses small coding experiments in the browser to play with the nature of computers, understanding their strengths and limitations. Sign up for the "To be announced" session to be notified by email when the class is next run, and sign up for "Self-Study" to start browsing the class materials right away. Self-Study mode makes all the videos and assignments available to be done at your own pace, but without a certificate of completion at the end.

Introduction to Computer Science for a zero-prior-experience audience. Play with little phrases of code to understand what computers are all about.

The CS 61 series is an introduction to computer science, with particular emphasis on software and on machines from a pro

Learn how to design secure systems and write secure code.

6.823 is a course in the department's "Computer Systems and Architecture" concentration. 6.823 is a study of the evolution of computer architecture and the factors influencing the design of hardware and software elements of computer systems. Topics may include: instruction set design; processor micro-architecture and pipelining; cache and virtual memory organizations; protection and sharing; I/O and interrupts; in-order and out-of-order superscalar architectures; VLIW machines; vector supercomputers; multithreaded architectures; symmetric multiprocessors; and parallel computers.

This course covers topics on the engineering of computer software and hardware systems: techniques for controlling complexity; strong modularity using client-server design, virtual memory, and threads; networks; atomicity and coordination of parallel activities; recovery and reliability; privacy, security, and encryption; and impact of computer systems on society. Case studies of working systems and readings from the current literature provide comparisons and contrasts. Two design projects are required, and students engage in extensive written communication exercises.

This course delivers a systematic overview of computer vision, emphasizing two key issues in modeling vision: space and meaning. We will study the fundamental theories and important algorithms of computer vision together, starting from the analysis of 2D images, and culminating in the holistic understanding of a 3D scene.

In this course, we will study the concepts and algorithms behind some of the remarkable successes of computer vision - capabilities such as face detection, handwritten digit recognition, reconstructing three-dimensional models of cities and more.

This course introduces abstraction as an important mechanism for problem decomposition and solution formulation in the biomedical domain, and examines computer representation, storage, retrieval, and manipulation of biomedical data. As part of the course, we will briefly examine the effect of programming paradigm choice on problem-solving approaches, and introduce data structures and algorithms. We will also examine knowledge representation schemes for capturing biomedical domain complexity and principles of data modeling for efficient storage and retrieval. The final project involves building a medical information system that encompasses the different concepts taught in the course.

Computer science basics covered in the first part of the course are integral to understanding topics covered in the latter part, and for completing the assigned homework.

This course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods.

Information Technology (IT) is everywhere. Every aspect of human activity depends on it. All IT processes, whether they drive mobile phones, the Internet, transportation systems, enterprise systems, publishing, social networks or any other application, rely on software.

In this new and improved version of the course, you will learn to write software with a progressive hint system for first time programmers. The core skill is programming; not just the ability to piece together a few “lines of code,” but writing quality programs, which will do their job right, and meet the evolving needs of their users. Anyone can write a program; this course teaches you to write good programs.

The course starts from the basics of computing and takes you through a tour of modern object-oriented programming, including classes, objects, control structures, inheritance, polymorphism, and genericity.

Throughout the course, you will have the opportunity to learn the principles of programming as well as the techniques for designing correct and reliable programs by using the Eiffel programming language and notation. You will be trying out example problems to provide your solution, and see it immediately compiled and tested from within your browser. To this end, we are using the Codeboard;web-based IDE, developed at the Chair of Software Engineering (ETH Zurich). 

Beyond programming, you will also get a glimpse at theoretical computer science, the set of mathematical techniques that underlie computation and makes today’s IT-based world possible.

In this third edition of the course we specifically focus on helping students with little or no programming experience. To this end, we have improved the introductory material about the Eiffel language, and we have implemented a progressive hint system students can use to get guidance on how to solve the programming exercises.

"Really good course. Followed it with a couple of experienced colleagues all of them having a computer science background. They really liked the concepts and programming in Eiffel a lot. Many thanks to the team making this course available! Can not wait to start with the advanced course!" --Previous CAMSx Participant

Previous edition course evaluation:

Overall course rating (1: worst grade, 6: best grade):

Grade Resp.   %Resp
1          1          2%
2          0          2%
3          3          6%
4          9        18%
5          20       40%
6          17       34%

Total respondents: 50
Average: 4.96

Modéliser un problème, concevoir un algorithme de résolution et en proposer une implémentation correcte. Du problème à sa solution, ce cours combine approches pragmatique, pratique et théorique de l'informatique.

Explore key ideas in game design, programming, architecture, game engines, player experience and game AI.

This course focuses on laws, approximations and relations of continuum electromechanics. Topics include mechanical and electromechanical transfer relations, statics and dynamics of electromechanical systems having a static equilibrium, electromechanical flows, and field coupling with thermal and molecular diffusion. Also covered are electrokinetics, streaming interactions, application to materials processing, magnetohydrodynamic and electrohydrodynamic pumps and generators, ferrohydrodynamics, physiochemical systems, heat transfer, continuum feedback control, electron beam devices, and plasma dynamics.

Acknowledgements

The instructor would like to thank Xuancheng Shao and Anyang Hou for transcribing into LaTeX the problem set solutions and exam solutions, respectively.

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

This class explores interaction with mobile computing systems and telephones by voice, including speech synthesis, recognition, digital recording, and browsing recorded speech. Emphasis on human interface design issues and interaction techniques appropriate for cognitive requirements of speech. Topics include human speech production and perception, speech recognition and text-to-speech algorithms, telephone networks, and spatial and time-compressed listening. Extensive reading from current research literature.

This course will focus on fundamental subjects in convexity, duality, and convex optimization algorithms. The aim is to develop the core analytical and algorithmic issues of continuous optimization, duality, and saddle point theory using a handful of unifying principles that can be easily visualized and readily understood.