Course in Computing

Top Course Studies in Computing

Computing

Adding a course in computing to your curriculum is a great way to make your skill set more appealing to employers. Most fields incorporate some form of computer usage now, so studying it will be very advantageous.

What is a course in computing? That is a very broad question. Computing is a large area; it includes computer sciences, programming, research, maintenance and many other areas. While it is very wise to take at least one course in computing regardless of your focus, it is entirely possible to pursue your entire educational experience within this area. Students will learn both theory and practice to gain a wide variety of skills.

There are many benefits to taking a course in computing, most of which are specific to the course. The programs in this area are very advanced and graduates may become experts in their field. Additionally, all programs will encourage a common set of skills, most notably critical thinking, project management, communication and problem solving.

The cost associated with your program depends on the area you choose to focus on, as well as the university and country you choose for your education. There are many factors and students should thoroughly investigate all of them before enrolling.

The career opportunities for graduates of a computing program are very diverse because so many different fields are included. The aspect they all have in common is demand. Almost every company in existence has a need for computer specialists, so the demand will only rise. You could choose to work in support and be an IT professional or administrator, or you could get into developmental work and put your programming skills to use. There is also a need for analysts to collect and interpret computing information.

If you are interested in computing programs, decide what you want to focus on and start researching your options. Search for your program below and contact directly the admission office of the school of your choice by filling in the lead form.

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Course in Machine Learning (Intermediate)

Coursera
Online Part time 8 months Open Enrollment USA USA Online

This Specialization provides a case-based introduction to the exciting, high-demand field of machine learning. You’ll learn to analyze large and complex datasets, build applications that can make predictions from data, and create systems that adapt and improve over time. [+]

Best Course Studies in Computing 2017. This Specialization provides a case-based introduction to the exciting, high-demand field of machine learning. You’ll learn to analyze large and complex datasets, build applications that can make predictions from data, and create systems that adapt and improve over time. In the final Capstone Project, you’ll apply your skills to solve an original, real-world problem through implementation of machine learning algorithms. Courses Machine Learning Foundations: A Case Study Approach Do you have data and wonder what it can tell you? Do you need a deeper understanding of the core ways in which machine learning can improve your business? Do you want to be able to converse with specialists about anything from regression and classification to deep learning and recommender systems? In this course, you will get hands-on experience with machine learning from a series of practical case-studies. At the end of the first course you will have studied how to predict house prices based on house-level features, analyze sentiment from user reviews, retrieve documents of interest, recommend products, and search for images. Through hands-on practice with these use cases, you will be able to apply machine learning methods in a wide range of domains. This first course treats the machine learning method as a black box. Using this abstraction, you will focus on understanding tasks of interest, matching these tasks to machine learning tools, and assessing the quality of the output. In subsequent courses, you will delve into the components of this black box by examining models and algorithms. Together, these pieces form the machine learning pipeline, which you will use in developing intelligent applications. Learning Outcomes: By the end of this course, you will be able to: - Identify potential applications of machine learning in practice. - Describe the core differences in analyses enabled by regression, classification, and clustering. - Select the appropriate machine learning task for a potential application. - Apply regression, classification, clustering, retrieval, recommender systems, and deep learning. - Represent your data as features to serve as input to machine learning models. - Assess the model quality in terms of relevant error metrics for each task. - Utilize a dataset to fit a model to analyze new data. - Build an end-to-end application that uses machine learning at its core. - Implement these techniques in Python. Machine Learning: Regression Case Study - Predicting Housing Prices In our first case study, predicting house prices, you will create models that predict a continuous value (price) from input features (square footage, number of bedrooms and bathrooms,...). This is just one of the many places where regression can be applied. Other applications range from predicting health outcomes in medicine, stock prices in finance, and power usage in high-performance computing, to analyzing which regulators are important for gene expression. In this course, you will explore regularized linear regression models for the task of prediction and feature selection. You will be able to handle very large sets of features and select between models of various complexity. You will also analyze the impact of aspects of your data -- such as outliers -- on your selected models and predictions. To fit these models, you will implement optimization algorithms that scale to large datasets. Learning Outcomes: By the end of this course, you will be able to: - Describe the input and output of a regression model. - Compare and contrast bias and variance when modeling data. - Estimate model parameters using optimization algorithms. - Tune parameters with cross validation. - Analyze the performance of the model. - Describe the notion of sparsity and how LASSO leads to sparse solutions. - Deploy methods to select between models. - Exploit the model to form predictions. - Build a regression model to predict prices using a housing dataset. - Implement these techniques in Python. Machine Learning: Classification Case Studies: Analyzing Sentiment & Loan Default Prediction In our case study on analyzing sentiment, you will create models that predict a class (positive/negative sentiment) from input features (text of the reviews, user profile information,...). In our second case study for this course, loan default prediction, you will tackle financial data, and predict when a loan is likely to be risky or safe for the bank. These tasks are an examples of classification, one of the most widely used areas of machine learning, with a broad array of applications, including ad targeting, spam detection, medical diagnosis and image classification. In this course, you will create classifiers that provide state-of-the-art performance on a variety of tasks. You will become familiar with the most successful techniques, which are most widely used in practice, including logistic regression, decision trees and boosting. In addition, you will be able to design and implement the underlying algorithms that can learn these models at scale, using stochastic gradient ascent. You will implement these technique on real-world, large-scale machine learning tasks. You will also address significant tasks you will face in real-world applications of ML, including handling missing data and measuring precision and recall to evaluate a classifier. This course is hands-on, action-packed, and full of visualizations and illustrations of how these techniques will behave on real data. We've also included optional content in every module, covering advanced topics for those who want to go even deeper! Learning Objectives: By the end of this course, you will be able to: - Describe the input and output of a classification model. - Tackle both binary and multiclass classification problems. - Implement a logistic regression model for large-scale classification. - Create a non-linear model using decision trees. - Improve the performance of any model using boosting. - Scale your methods with stochastic gradient ascent. - Describe the underlying decision boundaries. - Build a classification model to predict sentiment in a product review dataset. - Analyze financial data to predict loan defaults. - Use techniques for handling missing data. - Evaluate your models using precision-recall metrics. - Implement these techniques in Python (or in the language of your choice, though Python is highly recommended). Machine Learning: Clustering & Retrieval Case Studies: Finding Similar Documents A reader is interested in a specific news article and you want to find similar articles to recommend. What is the right notion of similarity? Moreover, what if there are millions of other documents? Each time you want to a retrieve a new document, do you need to search through all other documents? How do you group similar documents together? How do you discover new, emerging topics that the documents cover? In this third case study, finding similar documents, you will examine similarity-based algorithms for retrieval. In this course, you will also examine structured representations for describing the documents in the corpus, including clustering and mixed membership models, such as latent Dirichlet allocation (LDA). You will implement expectation maximization (EM) to learn the document clusterings, and see how to scale the methods using MapReduce. Learning Outcomes: By the end of this course, you will be able to: - Create a document retrieval system using k-nearest neighbors. - Identify various similarity metrics for text data. - Reduce computations in k-nearest neighbor search by using KD-trees. - Produce approximate nearest neighbors using locality sensitive hashing. - Compare and contrast supervised and unsupervised learning tasks. - Cluster documents by topic using k-means. - Describe how to parallelize k-means using MapReduce. - Examine probabilistic clustering approaches using mixtures models. - Fit a mixture of Gaussian model using expectation maximization (EM). - Perform mixed membership modeling using latent Dirichlet allocation (LDA). - Describe the steps of a Gibbs sampler and how to use its output to draw inferences. - Compare and contrast initialization techniques for non-convex optimization objectives. - Implement these techniques in Python. Machine Learning: Recommender Systems & Dimensionality Reduction Case Study: Recommending Products How does Amazon recommend products you might be interested in purchasing? How does Netflix decide which movies or TV shows you might want to watch? What if you are a new user, should Netflix just recommend the most popular movies? Who might you form a new link with on Facebook or LinkedIn? These questions are endemic to most service-based industries, and underlie the notion of collaborative filtering and the recommender systems deployed to solve these problems. In this fourth case study, you will explore these ideas in the context of recommending products based on customer reviews. In this course, you will explore dimensionality reduction techniques for modeling high-dimensional data. In the case of recommender systems, your data is represented as user-product relationships, with potentially millions of users and hundred of thousands of products. You will implement matrix factorization and latent factor models for the task of predicting new user-product relationships. You will also use side information about products and users to improve predictions. Learning Outcomes: By the end of this course, you will be able to: - Create a collaborative filtering system. - Reduce dimensionality of data using SVD, PCA, and random projections. - Perform matrix factorization using coordinate descent. - Deploy latent factor models as a recommender system. - Handle the cold start problem using side information. - Examine a product recommendation application. - Implement these techniques in Python. Machine Learning Capstone: An Intelligent Application with Deep Learning Have you ever wondered how a product recommender is built? How you can infer the underlying sentiment from reviews? How you can extract information from images to find visually-similar products to recommend? How you construct an application that does all of these things in real time, and provides a front-end user experience? That’s what you will build in this course! Using what you’ve learned about machine learning thus far, you will build a general product recommender system that does much more than just find similar products You will combine images of products with product descriptions and their reviews to create a truly innovative intelligent application. You’ve probably heard that Deep Learning is making news across the world as one of the most promising techniques in machine learning, especially for analyzing image data. With every industry dedicating resources to unlock the deep learning potential, to be competitive, you will want to use these models in tasks such as image tagging, object recognition, speech recognition, and text analysis. In this capstone, you will build deep learning models using neural networks, explore what they are, what they do, and how. To remove the barrier introduced by designing, training, and tuning networks, and to be able to achieve high performance with less labeled data, you will also build deep learning classifiers tailored to your specific task using pre-trained models, which we call deep features. As a core piece of this capstone project, you will implement a deep learning model for image-based product recommendation. You will then combine this visual model with text descriptions of products and information from reviews to build an exciting, end-to-end intelligent application that provides a novel product discovery experience. You will then deploy it as a service, which you can share with your friends and potential employers. Learning Outcomes: By the end of this capstone, you will be able to: - Explore a dataset of products, reviews and images. - Build a product recommender. - Describe how a neural network model is represented and how it encodes non-linear features. - Combine different types of layers and activation functions to obtain better performance. - Use pretrained models, such as deep features, for new classification tasks. - Describe how these models can be applied in computer vision, text analytics and speech recognition. - Use visual features to find the products your users want. - Incorporate review sentiment into the recommendation. - Build an end-to-end application. - Deploy it as a service. - Implement these techniques in Python. [-]

Programming in Java

TU Berlin Summer & Winter University
Campus Full time 4 weeks January 2017 Germany Berlin

This course is designed for students who want to look into the field of computer science. [+]

Winter University block 1: January 3rd to 27th, 2017 Course price: 1.850 Euros 18 hours of class sessions per week, 5 ECTS credit points Target group This course is designed for students who want to look into the field of computer science. Learning Goal/Output After this course you will be able to understand basic concepts of writing a computer program with the programming language Java. Take a look at the syllabus below. Course Components Topics like variables, loops, objects, input and output, user interfaces, collections, sorting, concurrent programming and event-driven programming will be covered. Topic list: Variables and Types of Data Loops and Conditions Arrays Methods Classes and Objects Object inheritance Collections Creating and Designing Data Types Sorting and Searching Graphics Input and Output Short Description In this course you learn first the basic knowledge of computer programming and then how to write computer programs using the programming language Java. You will be working at the computer. There will be some assignments which will give you more understanding of the programming concepts. Prerequisites The general prerequisites of the TU Berlin Summer & Winter University are that candidates have B2 level English and at least one year of university experience. In addition, the following requirements are necessary for this course: Basic computer skills and knowledge of school mathematics. In mathematics is recommend to know: - How to calculate with complex numbers - How to calculate with matrices - Handle planes and lines It is recommend to know some basic Linux commands (but they will be also introduced in the course). Lecturer(s) Prof. Dr. Rand Kouatly Dr. Rand Kouatly is a visiting professor at Technische Universität Berlin Faculty of Audio Communication; he has experience of more than 20 years in teaching nationally and internationally with lots of courses in the fields of Information Technology and Communication Engineering, including Java. [-]

Summer Economics Courses in California

University of California, Irvine - Summer Session
Campus Full time 6 - 12 weeks June 2017 USA Irvine

UC Irvine combines the strengths of a large, dynamic research university with the friendly feel of a small college, and incredible bounty of an incomparable Southern California location. [+]

Best Course Studies in Computing 2017. Summer Economics Courses in California S1 ECON 13 Global Economy S1 ECON 15A Probability and Statistics in Economics I S1 ECON 15B Probability and Statistics in Economics II S1 ECON 25 The Economics of Accounting Decisions S1 ECON 100A Intermediate Economics I S1 ECON 100B Intermediate Economics II S1 ECON 100C Intermediate Economics III S1 ECON 122A Applied Econometrics I S1 ECON 122A Applied Econometrics II S1 ECON 132A Introduction to Financial Investments S1 ECON 134A Corporate Finance S1 ECON 149W Cultural Economics S1 ECON 161A Money and Banking S2 ECON 13 Global Economy S2 ECON 15A Probability and Statistics in Economics I S2 ECON 15B Probability and Statistics in Economics II S2 ECON 20A Basic Economics I S2 ECON 25 The Economics of Accounting Decisions S2 ECON 100A Intermediate Economics I S2 ECON 100B Intermediate Economics II S2 ECON 100C Intermediate Economics III S2 ECON 116A Game Theory I S2 ECON 122A Applied Econometrics I S2 ECON 122B Applied Econometrics II S2 ECON 135 Mathematics of Finance S2 ECON 140 Managerial Economics S2 ECON 157 Economic Development S2 ECON 167 International Trade and Commercial Policy UC Irvine combines the strengths of a large, dynamic research university with the friendly feel of a small college, and incredible bounty of an incomparable Southern California location. Why Study at UCI? Summer Session offers over 800 courses in 70 academic disciplines. Students will take courses led by world renowned faculty amongst domestic UCI undergraduates. As a visiting student, you have the option to choose courses that will help you fulfill degree requirements at your home university or courses just for interest. This is your summer to grow academically. Students are encouraged to meet with professors and strike up a conversation – some students have been offered opportunities to assist in research on campus. Furthermore, there are plenty of academic resources available on campus to help you with your learning needs such as peer tutors, 5 expansive research libraries, and 6 computer labs with over 400 PCs and Macs. Step-by-Step Application Process Apply to UCI Summer Session online or by downloading the paper application summer.uci.edu/international Our team reviews and processes your application UCI Summer Session sends your acceptance letter and I-20 Complete Housing Contract Use your I-20 to apply for a visa Interview for an F-1 student visa UCI Summer Session sends you Pre-Departure Materials Purchase your flights Depart for California! Estimated Costs* Expenses vary with the length of your stay. This chart represents the estimated cost of taking two courses (4 units each) during one of the Summer Sessions (six weeks). *Prices are in U.S. dollars and are subject to change. REQUIRED FEES Enrolment Fee: $750 Campus Fee: $265 Course Fee ($339 per unit): $2736 Housing: $1225 Approximate Cost: $4976 Visa Support International (non-immigrant) students coming from abroad are required to have valid visas to enter the U.S. Most international students enrolling in Summer Session will obtain an F-1 student visa. UCI Summer Session, in collaboration with UCI Extension, will issue the documentation necessary to obtain an F-1 student visa. Once you have arrived, immigration advisors will be available to assist with travel, medical issues, or any questions regarding your legal status in the U.S. After completing your courses, you can obtain an official UCI transcript as proof of your academic participation. This transcript can be added to your Resume/CV or used for future applications to graduate schools in the U.S. or internationally. [-]

ICT in Education - Advanced Professional Development [Level HE7] part-time

University of Bolton
Online & Campus Combined Part time 16 weeks August 2017 United Kingdom Bolton

This course allows you to integrate theoretical aspects of ICT with your own professional practice in education, as well as enabling you to assess your own achievement of the learning outcomes. In discussion with your tutor, you will identify a potential e-learning development portfolio that will be suitable for your professional practice... [+]

ICT in Education - Advanced Professional Development [Level HE7] part-time This course allows you to integrate theoretical aspects of ICT with your own professional practice in education, as well as enabling you to assess your own achievement of the learning outcomes. In discussion with your tutor, you will identify a potential e-learning development portfolio that will be suitable for your professional practice. Your portfolio needs to be significant in scale and scope. Routine development, such as that involved in normal course learning material development (normal power point presentations, traditional written handouts, etc.), is NOT what is envisaged. Some examples of the type of projects previous students have undertaken are given in the Further Course Information section below. This is a challenging course that involves both individual tutorial appointments for consultation and group teaching. You will use the WebCT discussion forum facility and actively participate in online discussions in order to get the most from tutorials and group work. You must complete required preliminary reading and tasks before attending any of the sessions (face-to-face or online discussion forums). For individual or group tutorials, you must bring your work and prepare questions to be addressed / clarified. On successful completion of this course you will be awarded a certificate of credit for 20 credits at Level HE7. In addition, you may use these credits towards one of the Masters in Education degrees offered by the University of Bolton. After an initial informal exploration, and an initial literature search (intensive use of electronic based resources available at the University of Bolton library and on the internet, is expected), you will formulate clear and specific project aims and objectives. You will agree these with your supervising tutor. The initial literature search including web based research is important. There must be up-to-date, published literature that is relevant to your proposed project. A key part of the assignment involves demonstrating that what you have done is informed. The results of the literature search are submitted with a written piece early on (see below). Having finalised and agreed your project aims and objectives, you will create an action plan showing key stages, criteria for completion, date for completion and keep this up to date. You will be expected to maintain contact with your supervisor at all stages, and WebCT provides the communication facilities necessary to achieve this. All work undertaken and submitted must be with guidance from your supervisor. When developing group-work you will need to keep a meeting log book to record the progress of your work, ideas and reading. Some examples of projects undertaken by previous students: a) Applying e-pedagogy to a multimedia online course: evaluating different pedagogy theories using technology and selecting the more effective one for a case study. b) The introduction of a VLE to support language learning in HE: a feasibility study using a VLE to support, by blended learning, a language course in HE. c) An e-learning portfolio for a HND in Photography: analysis, selection, justification and demonstration of multimedia resources to support a HND module. This module is part of a suite of professional development courses offered by the University of Bolton covering contemporary issues and developments in education. The modules are designed to equip you with advanced skills and knowledge as you progress in your career and take on additional levels of responsibility. To gain a Masters in Education award you need 180 credits; 120 credits from undertaking advanced professional development courses or other selected modules and 60 credits from completing a dissertation. There has to be a balance between what are called option and core modules but this is straightforward and the Programme Leader can advise. The courses can be taken over a number of years, to fit in with your career and work/life balance. Most part-time students gain their Masters qualification in 2 to 3 years, but you can take up to 5 years if you wish. You will have access to 24/7 IT facilities and campus-wide WiFi, as well as one-to-one support from professional and highly experienced tutors. Entry requirements This course is open to anyone with an interest in developing blended learning skills and e-learning. You will need a computer with internet access as this course involves on-line learning. [-]

Computer-Supported Collaborative Learning and E-Tutoring - Advanced Professional Development [Level HE7] part-time

University of Bolton
Campus Part time 14 weeks August 2017 United Kingdom Bolton

Computer-Supported Collaborative Learning (CSCL) is helping to change the experience of contemporary teaching and learning. This course gives you the opportunity to research, analyse and understand CSCL. You will critically analyse, design and evaluate possible developments of CSCL theories and practices. As you complete the course you will be expected to reflect on your achievement in the form of an assignment or project, leading to a reflective... [+]

Best Course Studies in Computing 2017. Computer-Supported Collaborative Learning and E-Tutoring - Advanced Professional Development [Level HE7] part-time Computer-Supported Collaborative Learning (CSCL) is helping to change the experience of contemporary teaching and learning. This course gives you the opportunity to research, analyse and understand CSCL. You will critically analyse, design and evaluate possible developments of CSCL theories and practices. As you complete the course you will be expected to reflect on your achievement in the form of an assignment or project, leading to a reflective journal and a collaborative group project. On successful completion of this course you will be awarded a certificate of credit for 20 credits at Level HE7. In addition, you may use these credits towards one of the Masters in Education degrees offered by the University of Bolton. You will be introduced to the ideas and concepts of CSCL through keynote lectures, and a series of workshops and tutorials will expand certain topics. These sessions will help you to identify a particular direction that you might wish to research in more detail. You will be encouraged to relate your research to your interest or a particular application in your own field of work. For the collaborative group project, you will be expected to work with others in your group. Project: You will be expected to produce a project based upon your particular chosen area of study. You will have opportunities to discuss this with your tutor and to identify a topic or direction you wish to study. You are then asked to proceed with a literature search and to prepare an outline of your proposed assignment before undertaking further research and writing your report. Collaborative Group Project: You will be expected to produce a collaborative group project based upon your group’s particular chosen area of study. Again you will have opportunities to discuss this with the tutor and to identify a topic or direction the group wishes to study. You will then complete a literature search and prepare an outline of the group’s proposed project before undertaking further research and preparing the report. You will be taught and supported by professional educationalists throughout your course. This module is part of a suite of professional development courses offered by the University of Bolton covering contemporary issues and developments in education. The modules are designed to equip you with advanced skills and knowledge as you progress in your career and take on additional levels of responsibility. To gain a Masters in Education award you need 180 credits; 120 credits from undertaking advanced professional development courses or other selected modules and 60 credits from completing a dissertation. There has to be a balance between what are called option and core modules but this is straightforward and the Programme Leader can advise. The courses can be taken over a number of years, to fit in with your career and work/life balance. Most part-time students gain their Masters qualification in 2 to 3 years, but you can take up to 5 years if you wish. You will have access to 24/7 IT facilities and campus-wide WiFi, as well as one-to-one support from professional and highly experienced tutors. Entry requirements This course is open to anyone interested in creating a blended learning teaching environment. You will need a computer with internet access as this course involves on-line learning. [-]

GDip Computing (Pre-Masters)

University of Kent, School of Computing
Campus Full time 9 months August 2017 United Kingdom Canterbury

The GDip in Computing is suitable for graduates of other disciplines seeking to progress to the MSc in Computer Science (conversion) or one of our IT and Business Masters programmes. [+]

This pre-Masters course tops up the equivalent of a UK ordinary BSc degree to UK honours level. It is aimed at international students with undergraduate degrees from institutions that do not award the equivalent of UK honours degrees. A Graduate Diploma (GDip) can be used to gain admission to a relevant MSc programme at Kent or elsewhere in the UK (subject to satisfactory performance). Performance on the GDip equivalent to a good 2.2 honours level guarantees entry to appropriate MSc programmes at Kent. The GDip in Computing is suitable for graduates of other disciplines seeking to progress to the MSc in Computer Science (conversion) or one of our IT and Business Masters programmes. If you have studied computing before the GDip in Computer Science may be more suitable. Entry requirements - A good ordinary Bachelors degree in any subject [-]

HNC & HND Computing & System Development

Chichester College
Campus Full time 2 years September 2017 United Kingdom Chichester

The HND in Computing and Systems Development develops a wide range of skills related to modern computing and technology. [+]

Best Course Studies in Computing 2017. The HND in Computing and Systems Development develops a wide range of skills related to modern computing and technology. The emphasis is on implementing computing solutions for the modern computing environment. This means focusing on the internet and intranet applications, mobile app development, web design and database management techniques and technologies which underpin e-commerce and cloud computing. ENTRY REQUIREMENTS 16 (+) years old, 5 A*-C GCSE in English, Maths and relevant subjects, or equivalent. Successful interview with course leader or Chichester College designated officer IELTS 5 from an approved SELT test centre, no element below 5(Government changes might be applicable) Compulsory supplements and other entry requirements may be applicable as per study area. Note: It is highly advised to check the entry requirements of your university of choice to ensure progression. Five highlights Good value Higher Education experience with generous contact hours. An enthusiastic focus on employability led teaching and learning. Current techniques and technologies, constantly under review. Access to the latest industry standard software. Experienced teaching staff dedicated to developing each individual [-]

Transformation Deisgn

exMedia
Campus Full time October 2017 Germany Cologne

found both in the cultural studies in research and in the design sciences, the "Knowledge in / Knowledge in the making" increasingly interested. The exteriority of thought is observed in their dynamic development and the remuneration of thinking and doing as well as the role of artifacts involved to be reassessed. [+]

found both in the cultural studies in research and in the design sciences, the "Knowledge in / Knowledge in the making" increasingly interested. The exteriority of thought is observed in their dynamic development and the remuneration of thinking and doing as well as the role of artifacts involved to be reassessed. This development meets the tasks of structuring knowledge work in organizations that is increasingly seen as a design object. Design Thinking Here, a charting thought, currently called "Design Thinking" has proven economy. Thus there are two good reasons to re-consider the knowledge-forming functions of the design: On the one hand it is necessary to determine the knowledge in design clearer so that self-understanding of the discipline to improve and to connect with technical cultivation research. On the other hand, the functions of the design for the knowledge processes are working out of third parties to meet the demanding tasks of future knowledge design requirements. Both areas of responsibility are increasingly recognizing a diversity of thinking and working styles, design and modes of knowledge, knowledge and representation types (cognitive diversity). The design can use this base to reposition itself in the design of action and imaginative spaces of knowledge work (enabling spaces). It is the integrated design of knowledge, media and space as cognitive design, profound innovation (radical innovation) allows. The under the impact of emerging digital media early formulated concept of "knowledge designs" (Bolz 1993) learns as an update and clarification. The cognitive dwelling - Design, Computers and Cognition Among the methods of knowledge designs include the design specific model thinking that connects to cybernetics, systems theory and cognitive sciences. The subject of a so-understood design is cognitive habitation which includes social processes, media representations, technical systems and physical spaces. Thus (Winograd, Mitchell, Gero) is connected to the international discussion on design, Computers and Cognition. However, the German version of the knowledge Designs wins a particular strength through their connection with the local media studies, especially in its manifestation as a cultural technique (Siegert). Matters of concern Another research topic is the "question of the thing" (Heidegger), particularly in the expression as actor-network theory (Latour). This is based on chains of action hybrid actants which questions a "Dingpolitik". Designer as specialists for things and interactions have participated little in these discussions, but can make a substantial contribution to the future shape of "matters of concern" (Latour). [-]

Experimental Computer Science

exMedia
Campus Full time October 2017 Germany Cologne

The Experimental computer science at the KHM asks for the basic requirements and possibilities of today's design and manufacturing. In particular, the role of information processes and their interaction will be investigated with material processes. [+]

Best Course Studies in Computing 2017. The Experimental computer science at the KHM asks for the basic requirements and possibilities of today's design and manufacturing. In particular, the role of information processes and their interaction will be investigated with material processes. Where do they occur at all information and algorithms, as they are produced, communicated, processed and integrated into planning and manufacturing processes? How does human reason and perception with physical materials and how they are mediated by semiotic processes? In short, the way in which they are mutually dependent reason and artifact and what role do the characters? The fact that so far no general science of artifacts exist, the so the "know-how" that go beyond mere questions of making, is regarded as one of the main reasons that our company has never really mastered the art intellectually. Not the technical "know-how" is therefore at the center of our thinking and experimental approach, but reflect on the conditions of the possibility producing action and the question under what stipulations we want to develop our resulting technologies at all and operate? Access to this complex issue is basically experimentally. With the help of artifacts, small structures and process-oriented installations field Poietischer actions is artistic and practically investigated and critically. [-]

Training in Programming and Web Development

Digital Film Academy and Code Immersives
Campus Full time 1 year May 2017 USA Hell's Kitchen

Code immersive is designed specifically to maximize your employability and potential. Our curriculum is deeper, more inclusive and goes on for a longer period of time than any of the competitor’s program. Our curriculum also out performs any “boot camp” program. This curriculum is designed directly with input from hiring personal from Google and Amazon. Only full on immersive programs can qualify for financial aid and veteran benefits - and this is that program. [+]

WELCOME TO NEW YORK CITY AND THE BEST WEB DEVELOPMENT TRAINING ANYWHERE! CODE IMMERSIVES CURRICULUM All inclusive, employable curriculum. Code immersive is designed specifically to maximize your employability and potential. Our curriculum is deeper, more inclusive and goes on for a longer period of time than any of the competitor’s program. Our curriculum also out performs any “boot camp” program. This curriculum is designed directly with input from hiring personal from Google and Amazon. Only full on immersive programs can qualify for financial aid and veteran benefits - and this is that program. Tuition $13,000 Materials fee $1,895 (includes Mac Laptop) Technology Fee $110 Registration Fee $100 Program Total $15,105 HTML Hypertext Markup Language or HTML, is the markup language that is used to create web pages. It constitutes the building blocks of all websites and is considered a cornerstone technology together with CSS and Javascript, that is widely used to create user interfaces for web and mobile applications and visually appealing pages of websites. CSS CSS or Cascading Style Sheets is a style sheet language used to describe the presentation of a document written in a markup language. Together with HTML and JavaScript, CSS makes up the three essential languages that are used to create the visually engaging pages of most websites. JavaScript JavaScript (JS) is a high level programming language used to create web and mobile application interfaces and visually appealing websites. It is a prototype-based, multi paradigm language with first class functions that supports object oriented and functional programming styles. jQuery jQuery is a JavaScript library. It has been designed to make the client side scripting of HTML simpler. It is a cross-platform, free and open-source software. Ruby Ruby is a general purpose language that was designed in the mid 1990’s by Yukihiro Matsumoto. It is a dynamic, reflective and object-oriented programming language.Ruby draws inspiration from Perl, Smalltalk, Eiffel and a few others. It is a language that’s been designed with an enhanced focus on human rather than computer needs. Rails Ruby on Rails or ‘Rails’ as it is more commonly known is a framework for web applications that’s been written in Ruby. It facilitates the use of web standards such as JSON or XML for data transfer and HTML, CSS and JavaScript for display and user interfaces. [-]

Front-End Web Development

Ironhack Barcelona
Campus Part time 10 weeks June 2017 Spain Barcelona

Become a front-end developer in 10 weeks. Learn the fundamentals of HTML, CSS and JavaScript. [+]

Best Course Studies in Computing 2017. Who is it for Coding Newbies New to programming? This course is the perfect starting point for those who have tried learning online without any success. Designers Take your UX/UI skills to the next level. Bring your prototypes to life by turning them into fully functional websites. Professional Development Working with developers at your workspace? Learn to effectively communicate ideas in a technical environment Future Bootcamp Students Thinking of enrolling in full-time bootcamp but not sure if it's the right step? This course is the perfect place to make the leap easier Course Syllabus Intro to HTML & CSS You will learn how to create captivating user experiences using HTML, CSS and front-end frameworks such as Bootstrap & Foundation. Topics Include: Programming tools and workflow setup Introduction to Markup & HTML Deep dive into CSS Grid System & Responsive Design Rapid Prototyping with Bootstrap Intro to JavaScript You will learn how to add interactivity to the site using JavaScript & the most common JavaScript libraries including jQuery. Topics include: Basics of Programming using JavaScript (Control flow & Data structures) Introduction to jQuery Boostrap JS Components Third Party APIs using JavaScript Intro to WordPress You will learn to create templates using WordPress, one of the most in-demand CMS, followed by an introduction to the art of freelancing. Introduction to building with PHP & Wordpress, the world’s most popular CMS Optimizing Sites (Semantics, Meta Tags, Sprites) Introduction to Sass and compiling tools Intro to Freelancing Course Structure Class Every Monday will start with quick intro to a new topic followed by in-class pair-programming exercises. Online Content Students will get access to the Ironhack online platform for self-guided learning outside of class. Project Lab Each week will end with a culminating project individually or in pairs. TA’s will be available for in-class help as well. [-]

Computer Science, A Level

Richard Huish College
Campus Full time 2 years August 2017 United Kingdom Taunton

Computing aims to give you an introduction to the fundamentals of computing and has a strong practical programming element. It is taught in a specialist computing room using Visual Studio 2008. [+]

Computer Science A Level Full-time Examining Board: AQA Computing aims to give you an introduction to the fundamentals of computing and has a strong practical programming element. It is taught in a specialist computing room using Visual Studio 2008. If you plan to become a computing professional you are advised to continue your studies to university level. This A Level course is only offered as a two year programme. You may have studied computing related IT courses at school but these are not a requirement for entry to this course. You should already have an interest in all things to do with computing and this course will extend your skills into programming and the extended skills including how a computer works. Here are some of the topic areas we cover: Programming skills using Visual Basic.NET Principles of computing Coding existing programmes Web-based programming Operating systems Networks I really like the way that the course is structured in terms of the practical and theory. In programming, I am able to practice my theory straight away by writing a program which helps me to understand it better. Former A Level Computing student To do this course you need the following: Standard college entry requirements: 5 GCSEs at grade C or above, including Maths and English Language [-]

French AMerican Exchange program (FAME)

ENSEA Graduate School
Campus Full time September 2017 France Cergy-Pontoise

The French AMerican Exchange program is a Spring Semester Study Abroad program for undergraduates taught in English by professors at ENSEA, one of the top French Engineering Schools in Electrical Engineering. [+]

Best Course Studies in Computing 2017. What is FAME famous for? The French AMerican Exchange program is a Spring Semester Study Abroad program for undergraduates taught in English by professors at ENSEA, one of the top French Engineering Schools in Electrical Engineering. Eligibility Students in their third year of an undergraduate ABET-accredited degree program with a major in Electrical or Computer Engineering or Computer Science. FAME program will perfectly match their junior year Spring Semester. FAME Partner Universities Since the beginning of the program, 9 US Universities have joined us : Illinois Institute of Technology at Chicago (IIT), University at Buffalo (UB), University of Pittsburgh : School of Engineering (UPitt), Colorado School of Mines (CSM), University of Colorado at Boulder (UCB), University of Illinois at Urbana-Champaign (UIUC), Georgia Tech (GaTech), University of Michigan at Ann Arbor (U-M), Mississippi State University (MSU). [-]

Computer Science

Lurleen B Wallace Community College
Campus Full time September 2017 USA Andalusia

Do you strive to meet challenges? Do you like to solve problems and develop new ways of making everyday tasks easier or more beneficial? If so, Computer Science is the field for you. [+]

Computer Science Do you strive to meet challenges? Do you like to solve problems and develop new ways of making everyday tasks easier or more beneficial? If so, Computer Science is the field for you. The Computer Science curriculum places emphasis on fundamental principles, procedures, flowcharting, coding, peripheral equipment, computer center operations and programming techniques. Technical Areas Include Spreadsheet Software Applications Microcomputer Operating Systems Advanced Microcomputer Applications Intro to Computer Logic and Programming Database Management Software Applications Software Support Hardware Support C++ Programming Network Communications Visual Basic Programming E-Commerce Network Security Intro to Web Development JAVA Programming General Education Requirements Orientation English Composition I Mathematical Applications Mathematics of Finance Microcomputer Applications History, Social Science, Behavioral Science Elective Fundamentals of Oral Communications Humanities and Fine Arts Elective Total Credit Hours: 64 Job Opportunities According to the U.S. Department of Labor, Computer Science occupations are expected to be the fastest growing occupations through 2014. Various Job Opportunities include: Computer Analyst Computer Programmer Data Analyst Network Administrator Applications Manager PC Repair Technician Technical Support Specialist Web Developer Software Specialist Data Entry Operator Database Administrator Program Features Class sizes are small, allowing for individual training and assistance. The program features hands-on training with modern, up-to-date equipment. Students are allowed to participate in upgrading and/or troubleshooting departmental equipment. Students who successfully complete the Computer Science program have a very versatile array of knowledge within the field and are prepared to compete for the best and most challenging jobs available. [-]

EC-Council Certified Courses

Zeus Consulting
Campus Full time 5 days September 2017 United Arab Emirates Dubai

Zeus Consulting is Accredited Trainings Centre of EC-Council. All EC-Council programs are delivered by certified trainers. [+]

Best Course Studies in Computing 2017. Zeus Consulting is Accredited Trainings Centre of EC-Council. All EC-Council programs are delivered by certified trainers. EC-Council - Disaster Recovery Professional The EDRP course teaches you the methods in identifying vulnerabilities and takes appropriate countermeasures to prevent and mitigate failure risks for an organization. It also provides the networking professional with a foundation in disaster recovery principles, including preparation of a disaster recovery plan, assessment of risks in the enterprise, development of policies, and procedures, and understanding of the roles and relationships of various members of an organization, implementation of the plan, and recovering from a disaster. This EDRP course takes an enterprise-wide approach to developing a disaster recovery plan. Students will learn how to create a secure network by putting policies and procedures in place, and how to restore a network in the event of a disaster. Who Should Attend Network server administrators, Firewall Administrators, Security Testers, System Administrators and Risk Assessment professionals. EC-Council - Certified Encryption Specialist ECES course introduces students to modern symmetric key cryptography including the details of algorithms such as Feistel Networks, DES, and AES as well as an overview of many other algorithms such as Blowfish, Twofish, Skipjack, and others. Students will learn the basics of information theory as it applies to cryptography. Students will be introduced to hashing algorithms including MD5, MD6, SHA, Gost, RIPMD 256 and others. The course also covers asymmetric cryptography including thorough descriptions of RSA, Elgamal, Elliptic Curve, and DSA. Students will master significant concepts such as diffusion, confusion, and Kerkchoff’s principle. Target Audience Penetration Testers, Computer Forensics Specialists, Anyone involved in selecting, implementing VPN’s or digital certificates, Anyone involved in information security operations EC-Council - Certified Security Specialist EC-Council Certified Security Specialist (ECSS) allows students to enhance their skills in three different areas namely information security, network security, and computer forensics. Target Audience The EC-Council Certified Security Specialist (ECSS) program is designed primarily for students of academic institutions. It covers the fundamental basics of information security, computer forensics, and network security. The program will give a holistic overview of the key components of information security. Students, who complete the ECSS program, will be equipped with the adequate foundation knowledge and should be able to progress onto the next level. EC-Council - Certified Secure Computer User The purpose of the CSCU training program is to provide students with the necessary knowledge and skills to protect their information assets. This class will immerse students into an interactive environment where they will acquire fundamental understanding of various computer and network security threats such as identity theft, credit card fraud, online banking phishing scams, virus and backdoors, emails hoaxes, sex offenders lurking online, loss of confidential information, hacking attacks and social engineering. Target Audience This course is specifically designed for todays' computer users who use the internet and the www extensively to work, study and play. EC-Council - Network Security Administrator The ENSA program is designed to provide fundamental skills needed to analyze the internal and external security threats against a network, and to develop security policies that will protect an organization’s information. Students will learn how to evaluate network and Internet security issues and design, and how to implement successful security policies and firewall strategies. In addition, they will learn how to expose system and network vulnerabilities and defend against them. The ENSA Course is for experienced hands in the industry and is backed by a curriculum designed by the best in the field. Who Should Attend This course will significantly benefit System Administrators, System Engineers, Firewall Administrators, Network Managers, IT Managers, IT Professionals and anyone who is interested in network security technologies. EC-Council - Certified Security Analyst The EC–Council Security Analyst (ECSA) program is a comprehensive, standards-based, methodology intensive training program which teaches information security professionals to conduct real life penetration tests by utilizing EC-Council’s published penetration testing methodology. Target Audience Network server administrators, firewall administrators, information security analysts, system administrators, and risk assessment professionals all benefit from the ECSA program Certified Ethical Hacker   A comprehensive Ethical Hacking and Information Systems Security Auditing program focusing on latest security threats, advanced attack vectors, and practical real time demonstration of the latest Hacking Techniques, methodologies, tools, tricks, and security measures. Unlike other strictly theoretical training, you will be immersed in interactive sessions with hands-on labs after each topic 
Target Audience This course is designed for security officers, auditors, security professionals, site administrators, and anyone who is concerned about the integrity of their network infrastructure. [-]