Part time Course in Computer Science

Compare Part time Course Studies in Computer Science 2017

Computer Science

You can usually take higher education courses if you’re 18 or older. They’re regularly taught in universities, colleges and professional institutions such as art schools or agricultural colleges - nearly all of which have their own websites. You can get a wide range of skills, for example, diplomas, bachelor degrees, foundation degrees and post-graduate degrees.

The Master Degree in Computer Science program prepares students to work with computing problems and solutions. Graduates are highly sought after by employers and can work in a vast array of fields including technology, business and much more.

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Course Cgi (computer Generated Imaginery)

GrisArt Escuela Superior de Fotografía
Campus Part time 7 months October 2017 Spain Barcelona

Thanks to new technologies, creating photographic practice and live an exciting time, with constant innovations and new horizons, forcing photographers to continuous learning. [+]

Thanks to new technologies, creating photographic practice and live an exciting time, with constant innovations and new horizons, forcing photographers to continuous learning. In some fields, such as in automotive advertising, architecture and interior design, the change is already in place and the ultra-realistic images that come to us are in most cases computer-generated drawings from designers, engineers and architects . Are familiar CGI images, both stills and motion, applied in film and television. This revolution, which the authors define only limit, currently shaping the advertising world. Their use, though not applicable in all fields, continues to be increasingly necessary, as a generator of new images or as an integrator of these photographic CGI in real environments. The course offered by CGI GrisArt taps into the vast possibility of creating 3D images, but does so in a selective manner, with the needs and skills of photographers. They discover the most direct link between this technology and conventional photography, and compatibility and possibilities. To this end, those strictly useful aspects develop, for example, the camera layout and perspective, lighting, texturing or rendering the output image. The application will be used MAXON Cinema 4D program, unlike other equivalent applications is characterized by friendliness and ease of use of its interface. The high degree of quality offering the latest versions of the Advanced Render (C4D render engine itself) program makes it a very attractive tool for professional willing to venture into this field. Furthermore, knowing the market needs, the course incorporates learning process of working with V-RAY, one of the best existing render engines. The focus of the course is very practical, so that students become familiar with solving exercises to deepen their understanding and management while they are trained to develop their own intuition.... [-]


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. [+]

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. [-]

Summer Economics Courses in California

University of California, Irvine - Summer Session
Campus 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 Part time Course Studies in Computer Science 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. [-]

Electronic Engineering Technician - Computers

Confederation College
Campus 2 - 3 years September 2017 Canada Thunder Bay

In response to the continued growth in the computer industry, Confederation College offers the two-year, OACETT/CTAB accredited Electronics Engineering Technician program. [+]

Electronic Engineering Technician - Computers In response to the continued growth in the computer industry, Confederation College offers the two-year, OACETT/CTAB accredited Electronics Engineering Technician program. Year one provides a solid foundation in electronics and computer fundamentals. You now have the option of a specialization in Year Two - Computers. As a computer specialist, your job will be to provide technical solutions and support to local and wide area networks. Following graduation from this program, you will be able to install, interconnect, configure, implement, and troubleshoot network systems, create and maintain documentation, be proficient with hardware wiring centres, routers, voice network hardware, and apply networking solutions in a client-server environment. Upon successful completion of the two-year Electronics Engineering Technician – Computers program, you can transfer into the third-year of the Electrical Engineering Technology program. [-]

Programming in Java

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

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

Best Part time Course Studies in Computer Science 2017. 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. [-]

Advanced Study Program in Web Design

IED – Istituto Europeo di Design Rome
Campus Part time 7 months March 2017 Italy Rome

Media Designers use blogging, podcasting (webcasting) and NetTV, as well as new media content generators, and have the ability of organising communities and social networks to enable their users to share their opinions through text, images, music, ideas and suggestions. The course aims at creating a professional profile within the Web Media Designer able to produce a new generation of services with the web 2.0 advertising and marketing techniques in which on-line ideas are produced and shared through on-line communities and companies. [+]

THIS PROGRAM IS TAUGHT IN ITALIAN Aimed at: The course is addressed to Newly-graduates and professionals (designers, developers, tool planners, journalists and columnists, Marketing managers, etc.) who want to specialize in the field of digital media in the communication scope. The knowledge of web 1.0 and marketing, advertising and design web principles is required. Objective and structure: The course in Web Design is conceived as a creative and productive lab and makes use of professionals working in the Digital Media field: Art Directors, Web Designers, Managers, Internet Technicians and Web Agencies. The didactic activity is integrated by projects ordered by real customers that allow applying the website design as well as realizing and publishing the conceived websites. DESIGN AREA The content elements representing the communication structure of the website with reference to design are the important step of the design on the Internet. COMMUNICATION AND MEDIA AREA During the training, the future Web Media Designer will learn the contents and the market techniques linked to the Internet. TECHNOLOGIES AREA The use of the state-of-the-art software technologies to realize highly interactive websites in which the users can change and update the contents. Hardware technologies and the software for the network to configure the servers and the network. RIGHTS AND COPYRIGHT AREA The Web Media Designer field uses the new models conceived to protect rights and the copyright with flexible and modifiable licences. [-]

Advanced Diploma in Animation for Game, Film, & Visual Effects

Centre for Arts and Technology
Campus 24 months October 2017 Canada Kelowna

LIMITED NUMBER OF SCHOLARSHIPS AVAILABLE FOR UPTO $3000 ON A FIRST COME FIRST SERVE BASIS. APPLY TODAY. Do you ever wonder about the talent, dedication and hard work that goes into the magic of bringing a character or environment “alive” in an animation or special effect? Our 3D animation program in Kelowna, BC, trains you to succeed in this continually in demand and evolving field. [+]

LIMITED NUMBER OF SCHOLARSHIPS AVAILABLE FOR UPTO $3000 ON A FIRST COME FIRST SERVE BASIS. APPLY TODAY.

Do you ever wonder about the talent, dedication and hard work that goes into the magic of bringing a character or environment “alive” in an animation or special effect? Our 3D animation program in Kelowna, BC, trains you to succeed in this continually in demand and evolving field. Through concept development and storyboarding all the way to post production and special effects, our Animation for Game, Film, & Visual Effects diploma program allows you to build a strong foundation of 3D animation skills to start your career as an animator in gaming, film, and animation studios across the country.... [-]


Top Grade Training Cycle In Web Application Development

IED – Istituto Europeo di Design Madrid
Campus 2 years October 2017 Spain Madrid

The Higher Level Training Course in Web Application Development, specializing in Digital Design and User Experience, you way to become a programmer with advanced knowledge in digital design, one of the most demanded market profiles. [+]

THIS PROGRAM IS IN SPANISH Taught Like program and want to make it your profession? The Higher Level Training Course in Web Application Development, specialist in Digital Design and User Experience, You how to become a programmer with advanced knowledge in digital design, one of the most demanded market profiles. Develop your communication and creative skills and learn, through specific technologies and development environments, to develop and improve applications for all operating systems and mobile platforms. You will board concepts like usability and user experience while digging into the digital design and information systems, generating technological solutions for all platforms. Aimed at young people who want to guide their professional work in the field of programming and software development in the field of creative industries. IED Madrid, as Superior Design Center complements technical education with specific training in digital design, creating professionals with a double profile. Why study this course? We train programmers specialized in digital design, so that you are able to cope with autonomy the development of specific visual components for any software development. We have a laboratory equipped with the latest technologies for programming in multiplatform environments. We rely on a theoretical and practical training and the development of real projects with companies as a learning opportunity. Opt for a blended learning through our teaching, a balance between qualified and recognized professionals active hallmark of the specific methodology taught at the IED Madrid. Study IED Madrid means living with all branches of design in a privileged space, a creative experience and a unique opportunity to offer our students. Career Outlook: Software development in the field of creative industries. Implementation of specific visual components for software development. Developer of multimedia applications, games and applications adapted for mobile devices. Creator of graphics and multimedia components for integration into various applications content. Manager and database administrator. LANGUAGE COURSE: SPANISH [-]

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 Part time Course Studies in Computer Science 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. [-]

INTERNATIONAL WINTER SCHOOL : IOT

EPITECH
Campus 2 weeks February 2017 France Paris

From January 23 to February 3, 2017 Week 1: Embedded programming and prototyping Week 2: Project Ideation and Bootstrap [+]

International Winter school: IOT From January 23rd to February 3rd, 2017 WEEK 1: Embedded programming and prototyping January 23rd to 29th, 2017 2 days of embedded programming courses and 2 days of lab work on how to prototype basic projects. Students will interact with IOT prototyping devices, 3D printing and learn how to use different components for their projects (motion sensors, camera, wifi, Bluetooth, NFC, etc…). 1 day of Ideation / off campus activity WEEK 2: Project Ideation and Bootstrap January 30th to February 3rd, 2017 With the help of the Epitech Innovation Hub, IOT professionals and Epitech instructors, students will have to challenge themselves and make a working prototype of the connected object of their choice! Previous year projects include autonomous plant watering systems, an automatic barman, an automatic remote controlled car, and many more ! Several cultural activities and company visits will be included in the program. Below are some examples: - French language and culture - Visit of Eiffel Tower - Visit of Palace of Versailles - Visit to start-ups and accelerators - Disneyland This list is tentative. The final list of activities will be communicated to the students upon their arrival. ADMISSION REQUIREMENTS Two years of higher education in IT/computer science or 3 years of higher education in other technical fields. APPLICATION DEADLINE: December 30, 2016 PROGRAM FEE: 1 400€ Program fees include tuition fees, extra-curricular activities, accommodation, lunches and metro pass. [-]

Game Development Programme Oxford Gap Year (for ages 17-19)

Oxford Royale Academy
Campus August 2017 United Kingdom Oxford Yarnton

Game Development Programme Oxford Gap Year (ages 17-19) [+]

Best Part time Course Studies in Computer Science 2017. Accommodation details Students will be accommodated in single and twin rooms, both in the historic manor and in modern outbuildings. Bathrooms are shared between a few students. Male and female students will be separated by corridor and/or staircases. Safety and security on campus In the manor, students are overseen by the Programme Director, who implements the day-to-day running of the programme. The Director is assisted by a team of Counsellors who very often are current members of the University of Oxford. The Counsellors ensure that students are looked after pastorally, culturally and socially during their programme. Students are able to talk informally and frankly to the Counsellors in order to raise concerns or to discuss university applications. The manor has a few members of residential staff who live on-site throughout the programme and are able to assist students at any time of the day or night. [-]

Course in Web Development & Design

First Media Design School
Campus 30 hours August 2017 Singapore

This course is designed to teach learners without technical knowledge to design and build a friendly and functional website. Emphasis is rooted on design aesthetics, functionality and user friendliness using Adobe Dreamweaver. [+]

Course in Web Development & Design This course is designed to teach learners without technical knowledge to design and build a friendly and functional website. Emphasis is rooted on design aesthetics, functionality and user friendliness using Adobe Dreamweaver. Entry requirement 1. Basic computer operational knowledge and skills. 2. Able to speak, read and write in English. 3. Have an interest in arts and design. Methods of assessment All assessment is based on 100% coursework. Students are expected to demonstrate their design skills in the form of verbal and visual presentations and reports in preparation of portfolio work. Certification obtained upon completion of the programme WSQ Design Dynamic Websites to Meet Technical Requirements [-]

GDip Computing (Pre-Masters)

University of Kent, School of Computing
Campus 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. [+]

Best Part time Course Studies in Computer Science 2017. 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 [-]

Installing and Configuring Windows Server 2012

Kensington and Chelsea College
Campus 1 week August 2017 United Kingdom London

Get hands-on instruction and practice installing and configuring Windows Server 2012, including Windows Server 2012 R2, in this five-day Microsoft Official Course. [+]

Business and Management skills are essential for people working in all sectors. Whether you wish to find your first job, gain professional development in your current role, or take the next step in your career, we provide the know-how you need. Courses have a strong employability focus, giving you an opportunity to learn new skills and share ideas. Course Overview Get hands-on instruction and practice installing and configuring Windows Server 2012, including Windows Server 2012 R2, in this five-day Microsoft Official Course. This course is part one in a series of three courses that provides the skills and knowledge necessary to implement a core Windows Server 2012 infrastructure in an existing enterprise environment. This course maps directly to and is the preferred choice for hands-on preparation for the Microsoft Certified Solutions Associate (MCSA). Exam 410: Installing and Configuring Windows Server 2012, which is the first of three exams required for the MCSA: Windows Server 2012 credential. Campus: Chelsea Centre Times: Mon-Fri 09:00 - 17:30 [-]

Expert In Big Data

Universidad Pontificia De Salamanca
Campus 1 year October 2017 Spain Salamanca

In today's world data continuously, internet browsing, moving around the city, making card purchases using public services are generated, [+]

Best Part time Course Studies in Computer Science 2017. Program Description In today's world data continuously generated, surfing the internet, moving around the city, making card purchases using public services ... The amount of data continues to grow, and only those organizations able to convert these data into knowledge and value are going to be able to survive and grow in an increasingly competitive environment. In this postgraduate course in 'Big Data' they will be studied and applied to real cases of Telefónica R & D tools and more important for 'Big Data' technologies. GOALS Meet new methodologies for analyzing massive amounts of data generated by applications like twitter, social networking, biomedical technologies etc. Knowing the most widely used programming tools to develop applications within the field of 'Big Data' and to analyze complex data. Knowing the characteristics and working with real applications that generate massive amounts of data and require the development of advanced tools 'data mining'. priority to applications that work the center of Telefónica I + D will. Implemented using the prototypes studied languages ​​and tools that provide solutions to open problems in applications of 'big data'. priority to those issues forward for Telefónica I + D will. Professional profiles Data Analyst Data scientist Information Systems Engineer Curricula Module I: Techniques storage and data analysis Introduction and Motivation The data storage technologies Data Analysis with R Programming languages: Python Module II: Programming languages ​​and technologies for big data Python for data analysis Introduction to Hadoop Hadoop ecosystem components YARN: Hadoop 2.0 Apache Spark Open Data and Open Government Indexers documents: Elasticsearch The importance of data visualization Module III: Tools and visualization techniques Data visualization technologies D3.js Capstone Project Module IV: Project 'Big Data' Project on a real case of 'Big data' Methodology seminars (200h) with high practical content Projects on applications in which Telefónica R & D work for each topic Final project on a real problem Duration and price Start date: October 2016 Duration: From October to June Price: 1,500 Places available: 30 Location: Salamanca Contact: mmartinmac@upsa.es [-]