For all intents and purposes, this show is the fourth edition of the textbook Computer Organization and Design Fundamentals by David Tarnoff. Since the first edition came out in 2005, the PDFs have been made free for download to anyone interested in computer organization. With the trend toward audio and video instructional material, it was time for an update.

The presentation of the material in this series will be similar to that of the original textbook. In the first third, we will discuss the mathematical foundation and design tools that address the digital nature of computers. This will include an introduction to the differences between the physical world and the digital world, how those differences affect the way the computer represents and manipulates data, and the use and design of digital logic and logic gates. In the second third, the fundamentals of the digital logic and design will be used to design common circuits such as binary adders, describe checksums and cyclic redundancy checks, network addressing, storage devices, and state machines. The final third will examine the top-level view of the computer. This will include a discussion of the memory hierarchy and its components, the components of a CPU, and maybe even a discussion of assembly language along with some examples.

Students are introduced to the concepts of evolution by natural selection and digital evolution software. They learn about the field of evolutionary computation, which applies the principles of natural selection to solve engineering design problems. They learn the similarities and differences between natural selection and the engineering design process.

Delftse Foundations of Computation is a textbook for a one quarter introductory course in theoretical computer science. It includes topics from propositional and predicate logic, proof techniques, set theory and the theory of computation, along with practical applications to computer science. It has no prerequisites other than a general familiarity with computer programming.

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.

Developed by the NYCDOE CS education team, the Introduction to Physical Computing course is a 54-hour long introductory computer science course that guides students to explore fundamental CS concepts through tinkering with the micro:bit, a simple programmable computer device. Each unit of the course guides students through the learning process with three practices: analyzing computer applications around them based on a given issue; prototyping a project that reflects the result of the analysis plus their interest; and communicating about their projects, including the functionality of a project, a project development process, influence from other projects and their contribution to a project when working in a group. The curriculum and support sessions assist educators in discovering the most effective way of facilitating this course for their own classroom, while helping them to become comfortable with the main tool, the micro:bit.

The first video in Lesson 02: Computer Hardware. This video takes a quick look at the categories of computer hardware: processing, storage, input, and output.

Think Java is an introduction to Java programming for beginners. It is tailored for students preparing for the Computer Science Advanced Placement (AP) Exam, but it is for anyone who wants to learn Java.

The text, labs, and review questions in this book are designed as an introduction to the applied topic of computer security (cybersecurity). With these resources students will learn ways of preventing, identifying, understanding, and recovering from attacks against computer systems. This text also presents the evolution of computer security, the main threats, attacks and mechanisms, applied computer operation and security protocols, main data transmission and storage protection methods, cryptography, network systems availability, recovery, and business continuation procedures.

Short Description:
Intro to Computer Applications or Business Computers for Office 365

Word Count: 40014

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

Lecture #6 for the course: CSCI 49378: Intro to Distributed Systems and Cloud Computing - "Cloud Computing Concepts". Delivered at Hunter College in Spring 2020 by Bonan Liu as part of the Tech-in-Residence Corps program.

This course is designed to familiarize students with basic computer architecture and operating systems and the relationships between hardware and operating systems will be explored. A student who successfully completes this course will also be able to gain strong foundation in the core fundamentals of digital technology. Basic concepts are reinforced by exercises, and hand-on applications. Students will also program and run simple macros in Linux shell. Employability skills, such as Problem solving, Teamwork, Communications and Critical Thinking are integrated into the course work.
4 hours’ lecture.
All course content created by Syeda Ferdous Arar Begum. Content added to OER Commons by Joanna Gray.

This is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. It has a hands-on emphasis on understanding the realities and myths of what is possible on the world’s fastest machines. We will make prominent use of the Julia Language, a free, open-source, high-performance dynamic programming language for technical computing.

Short Description:
Now available in print at Amazon.com and via the OSU Press! Data Dashboard

Long Description:
A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the “natural environment” of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful “pipe” operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.

Word Count: 111597

(Note: This resource's metadata has been created automatically by reformatting and/or combining the information that the author initially provided as part of a bulk import process.)

This course covers the algorithmic and machine learning foundations of computational biology combining theory with practice. We cover both foundational topics in computational biology, and current research frontiers. We study fundamental techniques, recent advances in the field, and work directly with current large-scale biological datasets.

This video contains module wise discussion about fundamentals of computer and its application. Some assignments are also there for practice

This course provides introduction to computer graphics algorithms, software and hardware. Topics include: ray tracing, the graphics pipeline, transformations, texture mapping, shadows, sampling, global illumination, splines, animation and color. This course offers 6 Engineering Design Points in MIT’s EECS program.

16.225 is a graduate level course on Computational Mechanics of Materials. The primary focus of this course is on the teaching of state-of-the-art numerical methods for the analysis of the nonlinear continuum response of materials. The range of material behavior considered in this course includes: linear and finite deformation elasticity, inelasticity and dynamics. Numerical formulation and algorithms include: variational formulation and variational constitutive updates, finite element discretization, error estimation, constrained problems, time integration algorithms and convergence analysis. There is a strong emphasis on the (parallel) computer implementation of algorithms in programming assignments. The application to real engineering applications and problems in engineering science is stressed throughout the course.

6.844 is a graduate introduction to programming theory, logic of programming, and computability, with the programming language Scheme used to crystallize computability constructions and as an object of study itself. Topics covered include: programming and computability theory based on a term-rewriting, “substitution” model of computation by Scheme programs with side-effects; computation as algebraic manipulation: Scheme evaluation as algebraic manipulation and term rewriting theory; paradoxes from self-application and introduction to formal programming semantics; undecidability of the Halting Problem for Scheme; properties of recursively enumerable sets, leading to Incompleteness Theorems for Scheme equivalences; logic for program specification and verification; and Hilbert’s Tenth Problem.

This lesson teaches students about how computers interpret high-level source code languages such as HTML, CSS, and JavaScript by converting them into low-level binary code (i.e., machine code).  Students will act out the process of a web developer building a website by playing the roles of developer, compiler, and binary code.

A computational camera attempts to digitally capture the essence of visual information by exploiting the synergistic combination of task-specific optics, illumination, sensors and processing. In this course we will study this emerging multi-disciplinary field at the intersection of signal processing, applied optics, computer graphics and vision, electronics, art, and online sharing through social networks. If novel cameras can be designed to sample light in radically new ways, then rich and useful forms of visual information may be recorded — beyond those present in traditional photographs. Furthermore, if computational process can be made aware of these novel imaging models, them the scene can be analyzed in higher dimensions and novel aesthetic renderings of the visual information can be synthesized.
We will discuss and play with thermal cameras, multi-spectral cameras, high-speed, and 3D range-sensing cameras and camera arrays. We will learn about opportunities in scientific and medical imaging, mobile-phone based photography, camera for HCI and sensors mimicking animal eyes. We will learn about the complete camera pipeline. In several hands-on projects we will build physical imaging prototypes and understand how each stage of the imaging process can be manipulated.