Online courses directory (10358)

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

Lectures by Prof. Kamala Krithivasan,rnDepartment of Computer Science and Engineering,rnIIT Madras

Lecture Series on Internet Tecnologies by Prof. I. Sengupta, Department of Computer Science Engineering, IIT Kharagpur.

Lectures by Prof.Prem Kalra Department of Computer Science Engineering IIT Delhi

Lectures by Prof. Deepak GuptarnDepartment of Computer Science and Engineering rnIIT Kanpur

Lecture Series on Programming Languages by Dr.S.Arun Kumar, Department of Computer Science & Engineering ,IIT Delhi.

Lecture Series on Software Engineering by Prof.N.L. Sarda, Prof. Umesh Bellur, Department of Computer Science & Engi

Lectures by Prof. V Rajaraman Department of Super Computer Education and Research IISC Bangalore

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.

In this computer science course, you will learn advanced concepts underpinning the design of today’s multicore-based computers. Additionally, you will learn how design decisions affect energy efficiency and performance.

Overall, topics include fundamentals on exploiting parallelism among instructions such as out-of-order execution, branch prediction, exception handling and advanced concepts of memory systems including prefetching and cache coherency. These concepts are fundamental for future computer systems to maximize compute efficiency.

You will also engage with a community of learners with similar interests to share knowledge.

The course is derived from Chalmers’s advanced graduate course in computer architecture. Prospective students should have a foundation in basic computer design, as offered by, for example, in “Computer System Design - Improving Energy Efficiency and Performance.“

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.

In order to be competitive in the computer science field, it’s imperative to understand the basic building blocks of a modern computer and how they directly impact the speed and efficiency of a program. Whether you work with embedded systems, mobile computer-based systems, or cloud systems, performance and energy efficiency are key drivers of usability and competitiveness of computerized products.

In this course, you will learn how to design modern multicore-based computers, and how the design choices you make affect performance and energy consumption. You will explore design principles governing modern microprocessors, such as pipelining and cache memories, as well as methods for determining the impact of your design on execution time and energy efficiency.

These skills can make a difference for practicing engineers for the purpose of building highly competitive products. Take, for instance, a smartphone with limited battery capacity. By adding value to end users through new or improved functionality, this can lead to significantly shorter operation time between battery charges, thus utilizing the already limited resources of a smartphone far more efficiently.

With this skillset, you can become an expert in computer system performance and energy efficiency - knowledge that is in high demand when designing computerized embedded products. With trends towards IoT (Internet of Things), autonomous systems and mobile computers, such a skillset will be critical in a career in systems engineering.

This course is derived from a Chalmers senior undergraduate course in computer system design. It assumes basic knowledge in computer organization.

6.858 Computer Systems Security is a class about the design and implementation of secure computer systems. Lectures cover threat models, attacks that compromise security, and techniques for achieving security, based on recent research papers. Topics include operating system (OS) security, capabilities, information flow control, language security, network protocols, hardware security, and security in web applications.

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.