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e-book
An introductory coverage of algorithms and data structures with application to graphics and geometry.
- Subjects:
- Computing
- Keywords:
- Algorithms Data structures (Computer science) Textbooks
- Resource Type:
- e-book
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e-book
Programming Fundamentals - A Modular Structured Approach using C++ is written by Kenneth Leroy Busbee, a faculty member at Houston Community College in Houston, Texas. The materials used in this textbook/collection were developed by the author and others as independent modules for publication within the Connexions environment. Programming fundamentals are often divided into three college courses: Modular/Structured, Object Oriented and Data Structures. This textbook/collection covers the first of those three courses. The learning modules of this textbook/collection were written as standalone modules. Students using a collection of modules as a textbook will usually view it contents by reading the modules sequentially as presented by the author of the collection. The learning modules of this textbook/collection were, for the most part, written without consideration of a speci??c programming language. In many cases the C++ language is discussed as part of the explanation of the concept. Often the examples used for C++ are exactly the same for the Java programming language. However, some modules were written speci??cally for the C++ programming language. This could not beavoided as the C++ language is used in conjunction with this textbook/collection by the author in teaching college courses.
- Subjects:
- Computing
- Keywords:
- Computer programming C++ (Computer program language) Programming languages (Electronic computers) Textbooks
- Resource Type:
- e-book
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e-book
The Little Book of Semaphores is a free (in both senses of the word) textbook that introduces the principles of synchronization for concurrent programming. In most computer science curricula, synchronization is a module in an Operating Systems class. OS textbooks present a standard set of problems with a standard set of solutions, but most students don't get a good understanding of the material or the ability to solve similar problems. The approach of this book is to identify patterns that are useful for a variety of synchronization problems and then show how they can be assembled into solutions. After each problem, the book offers a hint before showing a solution, giving students a better chance of discovering solutions on their own. The book covers the classical problems, including "Readers-writers," "Producer-consumer", and "Dining Philosophers." In addition, it collects a number of not-so-classical problems, some written by the author and some by other teachers and textbook writers. Readers are invited to create and submit new problems.
- Subjects:
- Computing
- Keywords:
- Computer programming Operating systems (Computers) Textbooks
- Resource Type:
- e-book
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e-book
Essentials of Geographic Information Systems integrates key concepts behind the technology with practical concerns and real-world applications. Recognizing that many potential GIS users are nonspecialists or may only need a few maps, this book is designed to be accessible, pragmatic, and concise. Essentials of Geographic Information Systems also illustrates how GIS is used to ask questions, inform choices, and guide policy. From the melting of the polar ice caps to privacy issues associated with mapping, this book provides a gentle, yet substantive, introduction to the use and application of digital maps, mapping, and GIS.
In today's world, learning involves knowing how and where to search for information. In some respects, knowing where to look for answers and information is arguably just as important as the knowledge itself. Because Essentials of Geographic Information Systems is concise, focused, and directed, readers are encouraged to search for supplementary information and to follow up on specific topics of interest on their own when necessary. Essentials of Geographic Information Systems provides the foundations for learning GIS, but readers are encouraged to construct their own individual frameworks of GIS knowledge. The benefits of this approach are two-fold. First, it promotes active learning through research. Second, it facilitates flexible and selective learning—that is, what is learned is a function of individual needs and interest.
Since GIS and related geospatial and navigation technology change so rapidly, a flexible and dynamic text is necessary in order to stay current and relevant. Though essential concepts in GIS tend to remain constant, the situations, applications, and examples of GIS are fluid and dynamic. Though this book is intended for use in introductory GIS courses, Essentials of Geographic Information Systems will also appeal to the large number of certificate, professional, extension, and online programs in GIS that are available today. In addition to providing readers with the tools necessary to carry out spatial analyses, Essentials of Geographic Information Systems outlines valuable cartographic guidelines for maximizing the visual impact of your maps. The book also describes effective GIS project management solutions that commonly arise in the modern workplace.
- Subjects:
- Land Surveying and Geo-Informatics and Computing
- Keywords:
- Geographic information systems Textbooks
- Resource Type:
- e-book
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e-book
We set out to design an introductory course governed by four themes: Give students a good idea of what a career in MIS looks like by doing MIS. Enhance the professionalism of deliverables by teaching design and usability concepts. Promote creativity by assigning projects that demand it. Teach students about cloud computing by having them do cloud computing. Students in an introductory Management Information Systems (MIS) course often ask what a career in MIS looks like. Lacking a clear vision, they make their own assumptions. Often they assume the career involves programming with little human interaction. That MIS is a technical field could not be further from the truth. MIS job descriptions typically require candidates to be able to collaborate, communicate, analyze needs and gather requirements. They also list the need for excellent written and communication skills. In other words, MIS workers are constantly interacting with other people both inside and outside the organization. They are coming up with creative solutions to business problems. This course is designed to help students get a feel for what a career in MIS would be like. Our students report that they learn more about information systems from their internships than from their IS courses. Consequently, we designed a course that looks very much like an internship—an introduction to the field followed by a substantial project. Chapter 1 begins by introducing the information systems landscape. Here we discuss all the usual suspects: the information systems triangle, the systems development life cycle, transaction systems (ERP, SCM, CRM), collaboration systems, and business intelligence systems. Other aspects of the landscape such as usability, outsourcing, database concepts and so forth are introduced throughout chapter in Chapter 2 where they fit in naturally with the flow of the project. Chapter 2 is the substantial project which runs over a number of chapters. Over the course of the semester, students plan, build, and develop a proposal for an iPhone application. They develop a very realistic mockup. They also build a website to help market and support the app. Students are engaged because the project is fun and feels real. However, they are simultaneously learning business concepts and MIS skills. Prior to the existence of this course, we were only able to give such an interesting project at the senior level. Now, even as freshmen, students have a real experience of MIS in operation. A by product of creating an engaging course is increased enrollment in the MIS major. Even students who have never heard of MIS become excited about the major and either switch majors or add it as a double major or minor. Many other books have students study tools and then do a case. By contrast, most of this book is a case. Much like the real world, we introduce tools when needed, and only to the extent needed, to get at each part of the case.
- Subjects:
- Industrial and Systems Engineering and Computing
- Keywords:
- Business information services Management information systems Textbooks Application software -- Development
- Resource Type:
- e-book
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e-book
Think Python is a concise introduction to software design using the Python programming language. Intended for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. This textbook has been used in classes atBard College,Olin College of Engineering, University of California, Santa Barbara, University of Maine, University of Northern Colorado.
- Subjects:
- Computing
- Keywords:
- Computer programming Python (Computer program language) Textbooks Programming languages (Electronic computers)
- Resource Type:
- e-book
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e-book
Information Systems: A Manager's Guide to Harnessing Technology is intended for use in undergraduate and/or graduate courses in Management Information Systems and Information Technology. The teaching approach in Information Systems: A Manager's Guide to Harnessing Technology can change this. The text offers a proven approach that has garnered student praise, increased IS enrollment, and engaged students to think deeper and more practically about the space where business and technology meet. Every topic is related to specific business examples, so students gain an immediate appreciation of its importance. Rather than lead with technical topics, the book starts with strategic thinking, focusing on big-picture issues that have confounded experts but will engage students. And while chapters introduce concepts, cases on approachable, exciting firms across industries further challenge students to apply what they've learned, asking questions like: Why was Netflix able to repel Blockbuster and WalMart? How did Harrah's Casino's become twice as profitable as comparably-sized Caesar's, enabling the former to acquire the latter? How does Spain's fashion giant Zara, a firm that shuns the sort of offshore manufacturing used by every other popular clothing chain, offer cheap fashions that fly off the shelves, all while achieving growth rates and profit margins that put Gap to shame? Why do technology markets often evolve into winner-take-all or winner take-most scenarios? And how can managers compete when these dynamics are present? Why is Google more profitable than Disney? How much is Facebook really worth? The teaching approach in this text encourages students to think deeper and more practically about the space where business and technology meet. Every topic is related to specific business examples, so students gain an immediate appreciation of its importance. Rather than starting with technical topics, the book starts with strategic thinking, focusing on big-picture issues that interest students.
- Subjects:
- Computing
- Keywords:
- Information resources management Management information systems Information technology Textbooks
- Resource Type:
- e-book
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Video
Statistics, Machine Learning and Data Science can sometimes seem like very scary topics, but since each technique is really just a combination of small and simple steps, they are actually quite simple. My goal with StatQuest is to break down the major methodologies into easy to understand pieces. That said, I don't dumb down the material. Instead, I build up your understanding so that you are smarter.
- Course related:
- HTI34016 Introduction to Clinical Research
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Statistics Mathematical analysis Data mining Machine learning
- Resource Type:
- Video
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Courseware
Stanford Engineering Everywhere (SEE) expands the Stanford experience to students and educators online and at no charge. A computer and an Internet connection are all you need. The SEE course portfolio includes one of Stanford's most popular sequences: the three-course Introduction to Computer Science, taken by the majority of Stanford’s undergraduates, as well as more advanced courses in artificial intelligence and electrical engineering.
- Course related:
- EE1D01 Electrical Science for Everyone
- Subjects:
- Electronic and Information Engineering, Biomedical Engineering, Mechanical Engineering, and Computing
- Keywords:
- Engineering Computer science
- Resource Type:
- Courseware
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Others
The elements of the C language library are also included as a subset of the C++ Standard library. These cover many aspects, from general utility functions and macros to input/output functions and dynamic memory management functions
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing
- Keywords:
- C++ (Computer program language) C (Computer program language)
- Resource Type:
- Others
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Others
Welcome! Are you completely new to programming? If not then we presume you will be looking for information about why and how to get started with Python. Fortunately an experienced programmer in any programming language (whatever it may be) can pick up Python very quickly. It's also easy for beginners to use and learn, so jump in!
- Course related:
- EIE3343 Computer System Principles
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
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Others
Scikit Learn provide simple and efficient tools for predictive data analysis. Assessible to everybody, and reusable in various contexts. It built on NumPy, SciPy, and matplotlib. It is open sources, commercially usable under the BSD License.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
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Video
This youtube playlist included the topic of deep learning for human language processing, linear algebra, deep reinforcement learning, generative adversarial network, deep learning theory, structured learning, and machine learning.
- Course related:
- LGT6801 Guided Study in Logistics I
- Subjects:
- Computing
- Keywords:
- Machine learning Natural language processing (Computer science)
- Resource Type:
- Video
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Others
SQL is a standard language for storing, manipulating and retrieving data in databases.Our SQL tutorial will teach you how to use SQL in: MySQL, SQL Server, MS Access, Oracle, Sybase, Informix, Postgres, and other database systems.
- Course related:
- COMP5112 Data Structures and Database Systems
- Subjects:
- Computing
- Keywords:
- SQL (Computer program language)
- Resource Type:
- Others
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Others
GitHub is a development platform inspired by the way you work. From open source to business, you can host and review code, manage projects, and build software alongside 50 million developers. GitHub brings teams together to work through problems, move ideas forward, and learn from each other along the way. You can write better code, manage your chaos, and find the right tools in GitHub.
- Course related:
- EIE6811 Guided Study in Electronic and Information Engineering I/II/III and EE4006A Individual Project
- Subjects:
- Computing
- Keywords:
- Computer software -- Development Git (Computer file) Software engineering
- Resource Type:
- Others
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Others
W3Schools is optimized for learning, testing, and training. Examples might be simplified to improve reading and basic understanding. Tutorials, references, and examples are constantly reviewed to avoid errors, but we cannot warrant full correctness of all content.
- Subjects:
- Computing
- Keywords:
- Web publishing Web site development Web sites -- Design
- Resource Type:
- Others
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Others
This Linux tutorial is divided into 13 sections. In general I recommend you work through them in order but if you've come here just to learn about a specific topic then feel free to just go straight to that one. You can now jump into section 1 and get started or keep reading below to learn a little more about this tutorial. 1.The Command Line - What is it, how does it work and how do I get to one. 2.Basic Navigation - An introduction to the Linux directory system and how to get around it. 3.More About Files - Find out some interesting characteristics of files and directories in a Linux environment. 4.Manual Pages - Learn how to make the most of the Linux commands you are learning. 5.File Manipulation - How to make, remove, rename, copy and move files and directories. 6.Vi Text Editor - Discover a powerful Linux based text editor. 7.Wildcards - Also referred to as globbing, this is a means to refer to several files in one go. 8.Permissions - Learn to identify and change the permissions of files and directories and what the consequences of these are. 9.Filters - An introduction to various commands that allow us to mangle data in interesting and useful ways. 10.Grep and Regular Expressions - Master a powerful pattern matching language that is useful for analysing and processing data. 11.Piping and Redirection - Join commands together in powerful combinations. 12.Process Management - See what is currently running on your Linux system and what state the system is in, learn how to kill programs that have hung and put jobs in the background. 13.Scripting - Be happy. Get the computer to do tedious and repetitive tasks for you. 14.Cheat Sheet - A quick reference for the main points covered in this tutorial.
- Subjects:
- Computing
- Keywords:
- Linux Operating systems (Computers)
- Resource Type:
- Others
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MOOC
Data science has critical applications across most industries, and is one of the most in-demand careers in computer science. Data scientists are the detectives of the big data era, responsible for unearthing valuable data insights through analysis of massive datasets. And just like a detective is responsible for finding clues, interpreting them, and ultimately arguing their case in court, the field of data science encompasses the entire data life cycle. That starts with capturing lots of raw data using data collection techniques, and then building and maintaining data pipelines and data warehouses that efficiently “clean” the data and make it accessible for analysis at scale. This data infrastructure allows data scientists to efficiently process datasets using data mining and data modeling skills, as well as analyze these outputs with sophisticated techniques like predictive analysis and qualitative analysis. Finally, these findings must be presented using data visualization and data reporting skills to help business decision makers. Depending on the size of the company, data scientists may be responsible for this entire data life cycle, or they might specialize in a particular portion of the life cycle as part of a larger data science team
- Subjects:
- Computing
- Keywords:
- Machine learning Data mining Big data
- Resource Type:
- MOOC
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MOOC
The Elements of AI is a series of free online courses created by Reaktor and the University of Helsinki. We want to encourage as broad a group of people as possible to learn what AI is, what can (and can’t) be done with AI, and how to start creating AI methods. The courses combine theory with practical exercises and can be completed at your own pace.
- Course related:
- COMP4431 Artificial Intelligence
- Subjects:
- Computing
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
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MOOC
If you want to break into AI, this Specialization will help you do so. Deep Learning is one of the most highly sought after skills in tech. We will help you become good at Deep Learning. In five courses, you will learn the foundations of Deep Learning, understand how to build neural networks, and learn how to lead successful machine learning projects. You will learn about Convolutional networks, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, and more. You will work on case studies from healthcare, autonomous driving, sign language reading, music generation, and natural language processing. You will master not only the theory, but also see how it is applied in industry. You will practice all these ideas in Python and in TensorFlow, which we will teach. You will also hear from many top leaders in Deep Learning, who will share with you their personal stories and give you career advice. AI is transforming multiple industries. After finishing this specialization, you will likely find creative ways to apply it to your work. We will help you master Deep Learning, understand how to apply it, and build a career in AI.
- Course related:
- AMA564 Deep Learning
- Subjects:
- Computing
- Keywords:
- Machine learning Neural networks (Computer science) Artificial intelligence
- Resource Type:
- MOOC
-
Courseware
In this course, you will walk away with an up-to-date examination of the maturing FinTech industry and an understanding of the technologies set to shape the future of finance. Insight into who is currently adopting and driving financial technology innovation and the potential for partnerships between incumbents, start-ups and investors. The ability to critically assess the future of the financial services industry, through exploring complex real-world problems and how FinTech can be used to find solutions.A strategic framework to apply within your own role, and the opportunity to share this with like-minded professionals at an additional conference week.
- Course related:
- COMP4142 E-Payment and Cryptocurrency and COMP5521 Distributed Ledger Technology
- Subjects:
- Finance and Computing
- Keywords:
- Financial services industry -- Technological innovations Finance -- Technological innovations
- Resource Type:
- Courseware
-
MOOC
Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
- Course related:
- EIE6207 Theoretical Fundamental and Engineering Approaches for Intelligent Signal and. Information Processing and COMP4434 Big Data Analytics
- Subjects:
- Computing
- Keywords:
- Artificial intelligence Machine learning
- Resource Type:
- MOOC
-
MOOC
This is CS50x , Harvard University's introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, CS50x teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. The on-campus version of CS50x , CS50, is Harvard's largest course.
- Course related:
- COMP1011 Programming Fundamentals
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science
- Resource Type:
- MOOC
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Others
freeCodeCamp is a proven path to your first software developer job. More than 40,000 people have gotten developer jobs after completing this – including at big companies like Google and Microsoft. If you are new to programming, we recommend you start at the beginning and earn these certifications in order. To earn each certification, build its 5 required projects and get all their tests to pass.You can add these certifications to your résumé or LinkedIn. But more important than the certifications is the practice you get along the way.If you feel overwhelmed, that is normal. Programming is hard. Practice is the key. Practice, practice, practice. And this curriculum will give you thousands of hours of hands-on programming practice. And if you want to learn more math and computer science theory, we also have thousands of hours of video courses on freeCodeCamp's YouTube channel. If you want to get a developer job or freelance clients, programming skills will be just part of the puzzle. You also need to build your personal network and your reputation as a developer. You can do this on Twitter and GitHub, and also on the freeCodeCamp forum. Happy coding.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Coding theory
- Resource Type:
- Others
-
Others
Symbolab is an advanced math education tool. It allows users to learn, practice and discover math topics using mathematical symbols and scientific notations as well as text. Symbolab provides automated step by step solutions to algebraic, trigonometric and calculus topics covering from middle school through college. Symbolab offers a wealth of smart calculators including: equations, simultaneous equations, inequalities, integrals, derivatives, limits , tangent line, trigonometric equations, functions and more. The stated goal of the site is to make scientific content universally accessible by expanding the searchable data space onto scientific notations, expressions, equations and formulas. This is done by applying proprietary machine learning algorithms in order to understand the meaning and context of the queries. Symbolab, making math simpler.
- Course related:
- AMA1007 Calculus and Linear Algebra
- Subjects:
- Computing
- Keywords:
- Matrices Matrices -- Computer programs Mathematics -- Computer programs
- Resource Type:
- Others
-
Video
We are on a mission to provide free and subsidized education. We believe that the real world exists beyond the walls of costly institutions. We are here to help you in all the possible ways. A small step to educate the world. Join us and be a part of our creative community. "Every individual is different and talented, what you need are passion and curiosity."
- Course related:
- EE4004A Power Systems, EE2003A Electronics, EE3008A Linear Systems and Signal Processing, and EE3001A Analogue and Digital Circuits
- Subjects:
- Electronic and Information Engineering, Electrical Engineering, and Computing
- Keywords:
- Engineering Engineering -- Data processing Computer science
- Resource Type:
- Video
-
MOOC
This course covers a wide variety of topics in machine learning and statistical modeling. While mathematical methods and theoretical aspects will be covered, the primary goal is to provide students with the tools and principles needed to solve the data science problems found in practice. This course also serves as a foundation on which more specialized courses and further independent study can build. This course was designed as part of the core curriculum for the Center for Data Science's Masters degree in Data Science. Other interested students who satisfy the prerequisites are welcome to take the class as well. Note that class is intended as a continuation of DS-GA-1001 Intro to Data Science, which covers some important, fundamental data science topics that may not be explicitly covered in this DS-GA class (e.g. data cleaning, cross-validation, and sampling bias).
- Course related:
- LGT6801 Guided Study in Logistics I
- Subjects:
- Computing and Mathematics and Statistics
- Keywords:
- Big data Data mining Machine learning Mathematical statistics -- Data processing
- Resource Type:
- MOOC
-
Others
The mission of Papers With Code is to create a free and open resource with Machine Learning papers, code and evaluation tables.We believe this is best done together with the community and powered by automation.
- Course related:
- COMP5121 Data Mining and Data Warehousing Applications, COMP5212 Software Design and Architecture, COMP5123 Intelligent Information Systems, COMP5222 Software Testing and Quality Assurance, and COMP5131 Introduction to Information Systems
- Subjects:
- Computing
- Keywords:
- Machine learning Artificial intelligence
- Resource Type:
- Others
-
Others
Datavisualization.ch is a resource for data visualization and infographics. You'll find articles about events, tools, datasets, and showcases.
- Course related:
- LSGI2B01 Map Reading and Interpretation and SD1105 Digital Literacy for Designers
- Subjects:
- Visualisation, Land Surveying and Geo-Informatics, and Computing
- Keywords:
- Information visualization
- Resource Type:
- Others
-
Courseware
ArchiStar Academy has world class software and training for architects, engineers and universities students.
- Subjects:
- Computing
- Keywords:
- Design Technology
- Resource Type:
- Courseware
-
MOOC
Video games as a medium go back more than 50 years to mainframe computers. Even the central design of video games can be traced back to the first games themselves. To be a good game designer, it's essential to have an understanding of the video game design industry's fascinating history. We've partnered with The Strong National Museum of Play to give you a unique look into the history of all things video game. The International Center for the History of Electronic Games at The Strong is the largest and most comprehensive public assemblage of video games and related materials in the world. The staff are celebrated experts in the field and the ICHEG is visited by scholars of video games from around the world. You'll gain amazing insight into the history of video games with a guided exploration of key artifacts from the collection of more than 100,000 electronic games and materials.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Video games -- Design History
- Resource Type:
- MOOC
-
MOOC
Game designers work with a wide range of asset creators, programmers, producers, and others to bring a video game from concept to product. In this course, you will learn about the different types of teams a game designer is a member of, both large and small.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Video games -- Design
- Resource Type:
- MOOC
-
MOOC
Modern video games are incredibly complex multimedia productions involving still and motion graphics, code, audio, interface elements, narrative elements and much more. In this course, you will learn how and where all these pieces come from, who's in charge of each piece and the different stages of the game design process. We will also show you how everything is brought together to create a final product.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Video games
- Resource Type:
- MOOC
-
Video
A series of video that introduce various topics, including Node.js, Java, C programming, HTML, JavaScript, Python, PHP, and C++ programming.
- Subjects:
- Computing
- Keywords:
- Computer games -- Programming Computer programming Web sites -- Design Graphic arts Computer networks
- Resource Type:
- Video
-
Video
A series of video that cover various computing topics, for example, C++ programming, C# programming, Python, and Java.
- Subjects:
- Computing
- Keywords:
- Computer programming
- Resource Type:
- Video
-
Others
Learn to Code for Free. We're here to make coding more accessible, so everyone can learn the skills they need to upgrade their careers. For example, you can learn Python, HTML, CSS, and JavaScript.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers)
- Resource Type:
- Others
-
Others
Algorithm Visualizer is an interactive online platform that visualizes algorithms from code. Learning an algorithm gets much easier with visualizing it.
- Subjects:
- Computing
- Keywords:
- Algorithms Information visualization
- Resource Type:
- Others
-
Others
C is a general-purpose, imperative computer programming language, supporting structured programming, lexical variable scope and recursion, while a static type system prevents many unintended operations. C was originally developed by Dennis Ritchie between 1969 and 1973 at Bell Labs, and used to re-implement the Unix operating system. It has since become one of the most widely used programming languages of all time, with C compilers from various vendors available for the majority of existing computer architectures and operating systems. The best way we learn anything is by practice and exercise questions. We have started this section for those (beginner to intermediate) who are familiar with C programming. Hope, these exercises help you to improve your C programming coding skills. Currently, following sections are available, we are working hard to add more exercises.
- Subjects:
- Computing
- Keywords:
- Programming languages (Electronic computers) C (Computer program language)
- Resource Type:
- Others
-
Others
A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and games.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer science Data structures (Computer science) Programming languages (Electronic computers) Computer networks Computer algorithms
- Resource Type:
- Others
-
MOOC
Virtual reality is changing the way we interact with the world. But how does it work, what hardware is involved, and how is software written for it? In this course, part of the Virtual Reality Professional Certificate program, we will explore the foundations of user-friendly virtual reality app development for consumers, as well as enterprise solutions. Both hardware and software aspects will be discussed. You will learn to evaluate devices necessary for virtual reality applications, what their differences are, how you write interactive applications for virtual reality, and we will discuss the most frequent problems you are going to need to solve to write virtual reality software. In this course, you will explore the basics of virtual reality software through copying and modifying JavaScript to explore tradeoffs in VR application design. Extensive programming experience is not required. By the end of this course, you will understand what is important for successful virtual reality software and learn how to write simple virtual reality programs themselves with WebVR. This course is taught by an instructor with almost two decades of experience in virtual reality who leads the Immersive Visualization Laboratory at UC San Diego.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Computer simulation Virtual reality Human-computer interaction
- Resource Type:
- MOOC
-
Video
With so many new users picking up virtual reality headsets for the 2019 holiday season, it's time for a 2020 beginners guide to virtual reality. Let's dive into PC Specs, recommended headsets, setup, comfort, locomotion, motion sickness, free games and a lot more.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Computer simulation Virtual reality Human-computer interaction
- Resource Type:
- Video
-
Video
A tutorial on setting up clothing to low poly character.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Blender (Computer file) Three-dimensional display systems Computer animation Computer graphics
- Resource Type:
- Video
-
Video
A video demonstrate the modelling in MAYA, illustrate with the example of a disney character, Anna. Modeling - The modeling was done using mainly edge modeling - The eye is a low polygon sphere and then a flat polygon plane to start off, then extrude the edges and edit them into place
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Maya (Computer file) Computer animation
- Resource Type:
- Video
-
Video
A Virtual Reality introduction for Unity using HTC Vive for beginers. We will implement hand presence, teleportation and object grabbing in only 7 minutes without any line of code.
- Subjects:
- Interactive and Digital Media and Computing
- Keywords:
- Unity (Electronic resource) Computer simulation Virtual reality Human-computer interaction
- Resource Type:
- Video
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Others
Extract human-understandable insights from any machine learning model.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Machine learning
- Resource Type:
- Others
-
Others
Take your SQL skills to the next level.
- Subjects:
- Computing
- Keywords:
- Database management SQL (Computer program language)
- Resource Type:
- Others
-
Others
Make great data visualizations. A great way to see the power of coding!
- Subjects:
- Computing
- Keywords:
- Information visualization Python (Computer program language)
- Resource Type:
- Others
-
Others
Learn to handle missing values, non-numeric values, data leakage and more. Your models will be more accurate and useful.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language) Machine learning
- Resource Type:
- Others
-
Others
Learn the most important language for data science.
- Subjects:
- Computing
- Keywords:
- Python (Computer program language)
- Resource Type:
- Others
-
Others
Learn SQL for working with databases, using Google BigQuery to scale to massive datasets.
- Subjects:
- Computing
- Keywords:
- Database management SQL (Computer program language)
- Resource Type:
- Others