Now we'll pull everything together and explore how we calculate the position of a particle over time (frame by frame).

Learn how to use jQuery to show, hide, and toggle elements with animation effects.

Phenomenological approach to superconductivity, with emphasis on superconducting electronics. Electrodynamics of superconductors, London's model, and flux quantization. Josephson Junctions and superconducting quantum devices, equivalent circuits, and high-speed superconducting electronics. Quantized circuits for quantum computing. Overview of type II superconductors, critical magnetic fields, pinning, the critical state model, superconducting materials, and microscopic theory of superconductivity. Alternate years.

Este libro está dirigido, principalmente, a Estudiantes y Docentes que quieren aprender a programar como forma de fortalecer sus capacidades cognoscitivas y así obtener un beneficio adicional de su computador para lograr un mejor provecho de sus estudios. Dada la orientación del libro respecto a programar para resolver problemas asociados a las Ciencias e Ingenierías, el requisito mínimo de matemáticas que hemos elegido para presentar el contenido del mismo se cubre, normalmente, en el tercer año del bachillerato. No obstante, el requisito no es obligatorio para leer el libro en su totalidad y adquirir los conocimientos de programación obviando el contenido matemático.

Pamela shows how to store arrays of objects - a very powerful tool for your programs.

Courses on Artificial Intelligence (AI) and Librarianship in ALA-accredited Masters of Library and Information (MLIS) degrees are rare. We have all been surprised by ChatGPT and similar Large Language Models. Generative AI is an important new area for librarianship. It is also developing so rapidly that no one can really keep up. Those trying to produce AI courses for the MLIS degree need all the help they can get. This book is a gesture of support. It consists of about 95,000 words on the topic, with a 3-400 item bibliography.

An introduction to the main techniques of Artifical Intelligence: state-space search methods, semantic networks, theorem-proving and production rule systems. Important applications of these techniques are presented. Students are expected to write programs exemplifying some of techniques taught, using the LISP lanuage.

This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence. Upon completion of 6.034, students should be able to develop intelligent systems by assembling solutions to concrete computational problems, understand the role of knowledge representation, problem solving, and learning in intelligent-system engineering, and appreciate the role of problem solving, vision, and language in understanding human intelligence from a computational perspective.

This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power.

Software testing gets a bad rap for being difficult, time-consuming, redundant, and above all – boring. But in fact, it is a proven way to ensure that your software will work flawlessly and can meet release schedules.

In a two-course series, we will teach you automated software testing in an inspiring way. We will show you that testing is not as daunting a task as you might think, and how automated testing will make you a better developer who programs excellent software.

This second course builds upon the first course’s material. It covers more advanced tools and techniques and their applications, now utilizing more than just JUnit. Key topics include Test-Driven Development, state-based and web testing, combinatorial testing, mutation testing, static analysis tools, and property-based testing.

This is a highly practical course. Throughout the lessons, you will test various programs by means of different techniques. By the end, you will be able to choose the best testing strategies for different projects.

If you've ever spent hours renaming files or updating hundreds of spreadsheet cells, you know how tedious tasks like these can be. But what if you could have your computer do them for you?

In Automate the Boring Stuff with Python, you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand-no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to:

Search for text in a file or across multiple files
Create, update, move, and rename files and folders
Search the Web and download online content
Update and format data in Excel spreadsheets of any size
Split, merge, watermark, and encrypt PDFs
Send reminder emails and text notifications
Fill out online forms

Step-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.

Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in Automate the Boring Stuff with Python.

Graduate-level introduction to automatic speech recognition. Provides relevant background in acoustic theory of speech production, properties of speech sounds, signal representation, acoustic modeling, pattern classification, search algorithms, stochastic modeling techniques (including hidden Markov modeling), and language modeling. Examines approaches of state-of-the-art speech recognition systems. Introduces students to the rapidly developing field of automatic speech recognition. Its content is divided into three parts. Part I deals with background material in the acoustic theory of speech production, acoustic-phonetics, and signal representation. Part II describes algorithmic aspects of speech recognition systems including pattern classification, search algorithms, stochastic modelling, and language modelling techniques. Part III compares and contrasts the various approaches to speech recognition, and describes advanced techniques used for acoustic-phonetic modelling, robust speech recognition, speaker adaptation, processing paralinguistic information, speech understanding, and multimodal processing.

6.270 is a hands-on, learn-by-doing class, in which participants design and build a robot that will play in a competition at the end of January. The goal for the students is to design a machine that will be able to navigate its way around the playing surface, recognize other opponents, and manipulate game objects. Unlike the machines in Introduction to Design (2.70), 6.270 robots are totally autonomous, so once a round begins, there is no human intervention. The goal of 6.270 is to teach students about robotic design by giving them the hardware, software, and information they need to design, build, and debug their own robot.

Management Information Systems (MIS) is a formal discipline within business education that bridges the gap between computer science and well-known business disciplines such as finance, marketing, and management. In spite of this, most students will only take one or two MIS courses as part of their undergraduate program.
The term Management Information Systems has several definitions that might depend on where you look or who you ask. Common among these many definitions is that MIS represents a collection of technologies, people, and processes that manage the information and communication resources of an organization.

Even if you do not realize it, you use MIS every day. If you use email, you are using MIS since email is an information system (though you, the user, only see one end of it). If you log into a computer every morning and access or edit data on corporate servers, you are using information systems. In general terms, information systems encompass any interactions between organized data and people. MIS can be the means by which information is transmitted (such as the Internet), the software that displays the information (such as Microsoft Excel), or the systems that manage the data. In this course, you will learn about the components of management information systems and how to leverage them in business.

What is this course all about? To give you a basic level of computer application literacy primarily, Spreadsheets, and database Excel

Learning objectives:
- Gain an understanding of information competency, the Information Processing Cycle, Basic Components of the - Personal Computer, and Technology used in the Workplace.
- Demonstrate the ability to Create and Edit Workbooks and Charts which utilize Functions and Formulas.
- Understand and applying the fundamental database concepts to spreadsheet development such as Importing,Creating Tables, Sorting and Filtering, and using Conditional Formatting.
- Use advanced spreadsheet concepts such as Working with Multiple Worksheets and Workbooks, applying Advanced Functions, Setting Validation, and Protecting Workbooks.
- Develop an understanding and exposure to new and emerging technologies
- Gain the ability to serve as an informed purchaser of technology (personal, commercial)
- Prepare a capstone project which applies concepts and principles of course to a unique series of problems.