Masters Program in Computer Science

Best 180 Master Programs in Computer Science 2017

Computer Science

A Masters degree is an academic degree awarded to individuals who successfully denote a higher level of expertise. There are two main types of Masters - taught and research.

There are several fields that make up the broader field of computer science. One of these fields is the computational complexity theory, which can be very abstract. Other fields, such as computer graphics, deal more with concrete and hands-on visuals.  

 

Master's in Computer Science

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MRes Computer Science

Xi'an Jiaotong-Liverpool University
Campus Full time 18  September 2017 China Suzhou

The MRes (Master of Research) in Computer Science programme is designed to develop students’ understanding of the research process and their ability to carry out research. [+]

Masters in Computer Science. Overview The MRes Computer Science programme is designed to develop your understanding of the research process. It is for graduates from a computer-related discipline who wish to investigate research as a possible career, or who wish to extend their knowledge of one particular facet of computing. This programme provides you with an MRes that allows you to focus on your desired specialism, whilst our international staff provide all necessary support. Graduates of this programme, as with all XJTLU masters degrees, earn a University of Liverpool degree that is recognised by the Chinese Ministry of Education. Knowledge and skills The MRes Computer Science programme will equip you with comprehensive knowledge and understanding of: • advanced theoretical fundamentals of current trends in computer science • state-of-the-art key research issues in specialised areas of computer science • techniques for project management and the design, implementation and evaluation of IT solutions. Modules You will complete four taught modules in the first semester, followed by a research project for a total duration of 18 months. The precise content of your research project will be discussed and decided with your project supervisor and is subject to approval. Core modules: • Research methods • Project management • Dissertation. Elective modules: • Cloud computing • Data mining and Big Data analytics • Interactive systems • Object-oriented programming. Additional learning activity modules Careers Graduates from this programme will find employment as research and development engineers, systems developers and project leaders in IT companies, or will go on to further studies as a PhD candidate. Fees RMB 90,000 for the entire 18 month full-time programme. University tuition fees cover the cost of your study with us. Entry requirements: academic background An undergraduate degree (UK 2:1 or equivalent) in a computer science-related discipline with suitable programming and programme design experience. English language requirements • IELTS: 6.0 (minimum of 5.0 in all sections) • TOEFL iBT: 80 [-]

M.S. in Computer Science

University of San Francisco - College of Arts & Sciences
Campus Full time August 2017 USA San Francisco

The ever-changing world of software and computer science has always demanded more advanced training and education. [+]

Master in Computer ScienceThe ever-changing world of software and computer science has always demanded more advanced training and education.With the University of San Francisco's prime location in the heart of the San Francisco Bay Area and its proximity to Silicon Valley, USF graduate students enjoy an environment rich with the many innovations and opportunities of this world-renown region of technology. For these reasons and others, the number of students in the graduate program in Computer Science at the University of San Francisco has grown by 65% since 1999. USF also offers a three-year MSCS Bridge Program that provides a unique opportunity for students who are from non-Computer Science backgrounds to pursue an MS in Computer Science. In the first year, students take preparatory classes. The Master of Science in Computer Science (MSCS) provides students with a broad background in software development and other core disciplines of computer science. This core background serves as a sound foundation for CS graduate students as they develop a substantial software project - either as a research-driven or commercially sponsored project.Small classes and close interaction with full-time faculty are a hallmark of graduate education at USF. Along with the full-time teaching and research faculty, outside experts bring real-word computing experience to the classroom. In the Harney Science Center on the USF campus, a state-of-the-art computer and multimedia studio was constructed and endowed with a $2.5 million gift from a Computer Science alumnus. Students and faculty also maintain the W.M. Keck Computer Cluster (a Myrinet-connected network of 128 processors which provides students with on-site access to one of the most powerful computers at a liberal arts university).... [-]


Master Sensor System Engineering (SSE)

Hanze University of Applied Sciences - Groningen, the Netherlands
Campus Full time September 2017 Netherlands Groningen

This master prepares you for a bright future in the fascinating world of advanced sensor applications. A domain that is rapidly growing, providing all kinds of interesting prospects for you, ambitious engineers. Within the globally important domain of health, sensor applications will provide totally new ways to monitor, heal, treat and care for people. [+]

Masters in Computer Science. Sensor System Engineering: www.hanzegroningen.eu/msse Passionate about technology and engineering? ​​ Are you open minded, do you like to stretch boundaries to find out what is out there? Can you apply yourself, developing new ways to move the technology ahead, specifically in the health domain? Then take a moment to consider the opportunity to join us for one year to complete the Sensor System Engineering (SSE) honours master's programme.​​​ Programme overview General knowledge about sensor applications needed for any type of specialisation Specialised knowledge involving sensors in the health domain Honours content Master's thesis project (30 ECTS) General knowledge about sensor applications needed for any type of specialisation Linear algebra (4 ECTS): mathematics required for the next modules. Advanced data analysis (4 ECTS): integrating data coming from multiple complex sensors and to interpret this data correctly Modelling & simulation (4 ECTS): theory and tools required to model complex systems and to analyse and represent simulated data. Data centric architectures (4 ECTS): the architectural design of sensor systems at the level of of system architectures for big data applications and at the level of digital signal processing (DSP). Specialised knowledge involving sensors in the health domain Products and services in Health (4 ECTS): using real cases to learn the full design process of a health related sensor system. Sensor applications in Health (3 ECTS): exploration of sensor applications in biology, technology, diagnostics and application in health environments like hospital and home care. Honours content Professional skills (3 ECTS): learning to excel in the professional fi eld by developing essential professional, non-technical skills. Research & ethics (5 ECTS): learning necessary research skills as well as the ability to reflect on ethical issues. Community contribution (1 ECTS): forming a network for the students to help them solve particular problems in a multidisciplinary setting. Master's thesis project (30 ECTS) A six month research project in the domain of sensor technology and health in industry, a research institute or university department, resulting in a master's thesis. [-]

Master in Data Science

Bologna Business School
Campus Full time 12  December 2017 Italy Bologna

The Master in Data Science is designed for recent graduates interested in management and data analysis and who would like to take on a role which is central to any business and its value creation. A Data Scientist has already become one of the most sought-after specialists in the professional world. [+]

The Master in Data Science is designed for recent graduates interested in management and data analysis and who would like to take on a role which is central to any business and its value creation. A Data Scientist has already become one of the most sought-after specialists in the professional world. The data business is becoming a key sector for the European economy, the development of products and services based on data and the analysis of data collected in companies, public entities or that are available on social networks. The aim being to obtain operational indications and to identify new business opportunities. Big Data is a big challenge of today’s world, but we are training professionals to understand and create value from this complex information. Companies, in fact, have both a need and an urgency to manage the acquisition, presentation, sharing, analysis and visualization of data. Data Scientist is defined by the Economist as “the most interesting job of the twenty-first century, combining the skills of an IT technician, statistician and storyteller to extract the golden nuggets hidden under the mountains of data.” The Master in Data Science offers 3 different types of skills: solid computer training, an understanding of the technological aspects and knowledge of business dynamics. This Master creates professionals with across-the-board skills who are able to integrate with the company’s management. The program concludes with a Field Laboratory Work and a company internship. THE MASTER IS AN INVESTMENT. THE HONOR LOAN IS THE WAY TO FUND IT. “PerTe Prestito Con Lode”, a long-term and low-interest honor loan, with no collateral required to cover the full amount of the tuition fee. STRUCTURE The Master in Data Science is a full-time program structured in 1,500 hours of learning activities over 12 months of study, divided into: 360 hours of lecturing, an estimated 540 hours of independent study, and 600 hours of internship. The structure of the Master is divided into two terms: First term: December 2017 – April 2018 Second term: April 2018 – July 2018 Internship: September 2018 – December 2018 The Master offers a series of pre-courses at the start of the academic schedule: Software programming (Python), the foundations of data and SQL, basics in descriptive and inferential statistics, explorative data analysis and the fundamentals of economics. Classroom participation is about 30 hours per week structured in order to allow time to work in groups, while not neglecting individual students focus and management of interpersonal relationships. LEARNING METHOD The educational sessions provide different learning methods, including lectures, simulations, discussions of case studies and presentations by companies, testimonials, and group work. The curriculum is completed with master lectures held by professionals from the worlds of business, academia and politics, with opportunities for discussion and interaction with the business world through case histories. CAREER DEVELOPMENT Building synergies with businesses is a priority and a distinguishing characteristic of all programs of Bologna Business School, including the Master in Data Science. The School is fully dedicated to preparing students for the job market and it accomplishes this through systematic career development, with an ongoing commitment to combine the best professional projects by students with the demands of businesses. The internship is an excellent springboard to the professional world, evidenced by the fact that six months after completing the full-time master at Bologna Business School, an average of 85% of alumni are working in a company. [-]

Master in Computing Science

Umeå University, Faculty of Science and Technology
Campus Full time August 2017 Sweden Umeå

Our Master Programme in Computing Science is directed towards students how want to develop a deep understanding of the field, ... [+]

Our Master Programme in Computing Science is directed towards students how want to develop a deep understanding of the field, together with a scientific attitude characterized by logical reasoning and critical analysis. We want to make sure that you cannot only repeat and apply the facts you have learned, but also extend that knowledge by drawing your own conclusions. In the best of cases, this will enable you to continue your education on a PhD programme at Umeå University or somewhere else. At the very least, you should have acquired the knowledge and skills making it possible for you to work with challenging scientific problems in industrial research and development. Our teachers, who at the same time are successful scientists in the areas they teach, will help you to reach this goal.... [-]


Professional Master's Degree in Data Analytics

Sabanci University
Campus Full time October 2017 Turkey İstanbul

Big data is paving the way to empower businesses to make better decisions: With the amount of digital data increasing at an enormous rate, rigorous research is carried out in an effort to extract value from the massive data sets, to turn them into smarter decisions for improving business results. The emerging field of Data Analytics holds the key to unleashing that potential. [+]

Big data is paving the way to empower businesses to make better decisions: With the amount of digital data increasing at an enormous rate, rigorous research is carried out in an effort to extract value from the massive data sets, to turn them into smarter decisions for improving business results. The emerging field of Data Analytics holds the key to unleashing that potential. Data Analytics is considered to be a relatively new field which integrates state-of-the-art computational and statistical techniques to extract business value from a rapidly expanding volume of data. Many consulting firms claim that Data Analytics will be one of the key skills of the 21st century. Most critical issue, however, is the shortage of analytical talent that could turn the high-volume data into useful information that will be used for better decision making. In a business world in which the gap between winners and losers is narrowing down, companies are increasingly turning to data analytics to gain a competitive advantage in productivity, profitability and sustainable manufacturing processes for better products and better services. To be able to do that, companies need trained workforce skilled in Data Analytics, who are equipped to manage, understand and model the data, interpret the outcome and communicate the results for business use. Professionals holding a degree in Data Analytics will be well positioned to help their organizations gain a competitive advantage in a data-driven world. This program is designed to help our participants develop the skill set needed for creating and maintaining the added competitive edge that innovative companies are trying to establish. Our curriculum will help you develop skills required for data-driven decision-making with a wide variety of courses such as: Programming, Data management and data processing, Data mining, Machine learning, Statistical models for data analysis, Optimization, Decision modeling, Exploratory data analysis and visualization, Social network analysis, Data privacy, security and forensic discovery, Information security law, Business communication, Project management, a capstone project and more. Admission Requirements Applications for non-thesis master’s programs are evaluated by the assigned Admission Jury. Suitable candidates are invited to a personal interview. Admissions are finalized by the approval of the related Graduate School Board upon the recommendation of the Jury and are announced to the applicants. Application periods can be found in the Academic Calendar of Sabanci University. Your registration will be completed upon the approval of Turkish Higher Education Council regarding the equivalence of the last graduated higher instution and the course of study. Program Structure Professional Master's Degree in Data Analytics is a 30-credit program that can be completed in one academic year. The courses are distributed across three consecutive semesters (Fall-Spring-Summer), each of which lasts 14 weeks. Students take 10 courses (excluding the Term Project) in total from various areas. The Term Project is a non-credit course. Who should apply Professional Master’s Degree in Data Analytics is designed for working professionals who are looking into developing their analytical skills with no interruption on participants’ careers. The expected participant profile: Graduates of disciplines with a solid quantitative background (e.g. computer science, engineering, mathematics, physics, statistics, economics and other fields with a quantitative focus), or All professionals who have ample work experience in a data-analytics-related area and are seeking in-depth training in Big Data Analysis. Skills Acquired Diagnose, understand, measure and evaluate data to enable better decision making within the organization. Define and apply appropriate methodologies for complex business problems. Interpret findings, present and communicate the results. Graduates can find work as data analysts, data managers, data modelers and data scientists in the financial institutions, healthcare industry, insurance industry, telecommunications industry, marketing and media firms, retail industry and government agencies. [-]

M.Sc. Computer Science – Data Analytics

National University of Ireland Galway College of Engineering & Informatics
Campus Full time September 2017 Ireland Galway

Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep [+]

Masters in Computer Science. Big Challenges being addressed by this programme – motivation Globally, there is a reported shortage of data analytics talent, particularly of individuals with the required deep technical and analytical skills. (1) Accenture, Gartner and McKinsey have all identified Data Analytics as one of the fastest growing employment areas in computing and one most likely to make an impact in the future. The Irish Government’s policy is for Ireland to become a leading country in Europe for big data and analytics, which would result in 21,000 potential new employment opportunities in Ireland alone. (1) CNN has listed jobs in this area in their Top 10 best new jobs in America. 1) “Assessing the Demand for Big Data and Analytics Skills”, 2013-2020. Forfás Expert Group on Future Skills Needs, 2014. Programme objectives & purpose This is an advanced programme that provides Computing graduates with advanced knowledge and skills in the emerging growth area of Data Analytics. It includes advanced topics such as large-scale data analytics, information retrieval, data mining, natural language processing, and web data analytics. It also includes foundational modules in topics such as statistics and programming for data analytics. Students on the programme further deepen their knowledge of Data Analytics by working on a project either in conjunction with a research group or with an industry partner. Graduates will be excellently qualified to go into academic research or to pursue careers in industry in a wide range of areas. Opportunities include: - PhD-level research in NUI Galway, elsewhere in Ireland, or abroad - Multinational enterprises, in Galway and elsewhere, that provide services and solutions for analytics and big data; - Multinational enterprises whose businesses depend on analytics and big data technologies; - Innovative indigenous companies and leading-edge start-ups whose provide analytics solutions and products. What’s special about CoEI/National University Ireland Galway in this area: The MSc in Computer Science (Data Analytics) is being delivered by the Information Technology Discipline, in collaboration with the Insight Research Centre and with input from the School of Mathematics, Statistics and Applied Mathematics in NUI Galway - The Information Technology Discipline is NUI Galway’s Computer Science academic discipline, with a 25-year track record of education, research, and industry collaboration - The Insight research centre in NUI Galway is Europe’s largest research centre for Data Analytics - This programme opens the door for graduates for opportunities in PhD level research, careers in industry, or starting new ventures. Programme Structure 90 ECTS programme One full year in duration, beginning September and finishing August Comprises: - Foundational taught modules (20 ECTS) - Advanced taught modules (40 ECTS) - Research/Industry Project (30 ECTS). Programme Content Sample Modules - Statistics - Probability - Advanced Biomaterials - Linear Algebra - Digital Signal Processing - Programming for Data Analytics - Research Project Fundamentals - Open & Linked Data - Information Retrieval - Machine Learning & Data Mining - Learning for Information Retrieval - Tools & Techniques for Large Scale Data Analytics - Data Mining on the Web - Systems Modelling and Simulation - Case Studies in Data Analytics - Embedded Signal Analysis and Processing - Natural Language Processing - Data Visualisation Opportunity for number of Industrial & Research internships: Students enrolled on this programme will have an opportunity to apply for a one-year post-graduation internship in either a related industry or research group in Ireland. Scholarships   A number of scholarships are being made available by the College of Engineering and Informatics to non-EU students registered on these MSc programmes. Each scholarship will be valued at €2,500 and will be awarded to successful candidates based on the submission of a personal statement and CV to the College.    A number of industry sponsored Scholarships will also be available, each to the value of €2,500. Entry Requirements The M.Sc. is suitable for high-performing graduates of Computer Science and closely related degree programmes. Entry to the programme is open to individuals who have at least Second class honours, grade one in a Level 8 degree such as a B.Sc. in Computer Science or a BE in Computer Engineering, or another degree programme that is similar in content to the relevant undergraduate degrees offered by NUI Galway and is from a recognised university or third level college. How to apply Applications are made online via the Postgraduate Applications Centre (PAC). The PAC code for this program is GYE06. [-]

MEng in Computer Science

Northern Arizona University
Campus Full time August 2017 USA Flagstaff

This program assists students who wish to upgrade their current engineering expertise by delving into the contemporary and future-forward area of computer science. The plan features real-world relevancy and flexibility in course format and distance delivery. [+]

The MEng CS degree is a non-thesis program that focuses on building advanced computer science expertise through a project-based experience. Graduates with this degree possess advanced expertise and are well-qualified to be a leader in a variety of software development organizations. Students who are planning on further graduate study in a Ph.D. program may be interested in the thesis-based MSE CS program. This program assists students who wish to upgrade their current engineering expertise by delving into the contemporary and future-forward area of computer science. The plan features real-world relevancy and flexibility in course format and distance delivery. What Can I Do with a Master of Engineering in Computer Science? Computer scientists use algorithms and data structures to harness the incredible processing power of modern computers towards constructive ends. They write programs, the basic building blocks that form the computer world. They also create the databases, the "office" software, and the networking protocols at the core of today computing demands in business, science, and engineering. If this sounds like the career for you, we can help. Our program is intended to meet your educational needs as a practicing engineer. You will have the opportunity to enhance and/or develop the skills, knowledge, and understanding that are critical to today practicing engineers. Courses are offered through a variety of forms, including distance-delivery methods and flexible formats. Note: If you are interested in this advanced degree, you must apply and be accepted to the Master of Engineering program in addition to being admitted to the university. With further education, one of these paths is possible: Researcher Database analyst Engineering consultant Computer programmer University Requirements To receive a master’s degree at Northern Arizona University, you must complete a planned group of courses from one or more subject areas, consisting of at least 30 units of graduate-level courses. (Many master’s degree programs require more than 30 units.) You must additionally complete: All requirements for your specific academic plan(s). This may include a thesis. All graduate work with a cumulative grade point average of at least 3.0. All work toward the master’s degree must be completed within six consecutive years. The six years begins with the semester and year of admission to the program. In addition to University Requirements: Complete individual plan requirements. ADDITIONAL ADMISSION REQUIREMENTS Admission requirements over and above admission to NAU are required. NAU Graduate Online application is required for all programs. Details on admission requirements are included in the online application. Undergraduate degree from a regionally accredited institution Grade Point Average (GPA) of 3.00 (scale is 4.00 = "A"), or the equivalent. Admission to many graduate programs is on a competitive basis, and programs may have higher standards than those established by the Graduate College. Transcripts For details on graduate admission policies, please visit the Graduate Admissions Policy International applicants have additional admission requirements. Please see the International Graduate Admissions Policy Individual program admission requirements include: B.S. degree in Engineering or completion of prerequisite courses (see department website for details) GRE® revised General Test 3 letters of recommendation Personal statement or essay MASTER'S REQUIREMENTS Take the following 30 units: Applied Mathematics, in a topic relevant to your specific interests, such as Fourier transforms or statistical analysis (3 units) Engineering or Computer Science Management course offered through such colleges as Engineering or Business (3 units) Computer Science Electives, selected with your advisory committee’s approval to match your interests (18 units) This can include up to 3 units in a cross-disciplinary or otherwise related course. Practice-Oriented Project, facilitated and developed under your advisory committee’s guidance and focused on a real-world problem or theoretical issue with immediate relevance to current computer science practice (6 units) Accelerated Bachelor's/Master's Plan Option This program is available as an Accelerated Undergraduate/Graduate Plan. Accelerated Programs provide the opportunity for outstanding undergraduates working on their bachelor’s degree to simultaneously begin work on a master’s degree, which may allow them to complete both degrees in an accelerated manner by applying 6 units toward both degrees. Students must apply to the accelerated program and the master’s program by the application deadline, and meet all requirements as listed on the Accelerated Bachelor's/Master's Programs to be considered for admission. Admission to programs is competitive and qualified applicants may be denied because of limits on the number of students admitted each year. Be sure to speak with your advisor regarding your interest in Accelerated Programs. Be aware that some courses may have prerequisites that you must also take. For prerequisite information click on the course or see your advisor. Student Learning Outcomes The Master of Engineering is a non-thesis professional degree, based primarily on course work and/or on an engineering project designed with the guidance of a faculty advisor to address a need or problem specific to their engineering field of study (Civil, Environmental, Electrical, or Mechanical Engineering). This degree program is designed to provide a broad, practice-based education. Demonstrate the ability to apply graduate level critical thinking skills to formulate and solve advanced civil (electrical/environmental/mechanical) engineering problems. Acquires knowledge on advanced contemporary engineering topics and computational tools specific to civil (electrical/environmental/mechanical) engineering. Develops the ability to identify, formulate, and solve relevant advanced civil (electrical/environmental/mechanical) engineering problems. Develops the ability to synthesize, explain, verify, and justify solutions to complex civil (electrical/environmental/mechanical) engineering problems. Demonstrate the ability to, independently and creatively, design, plan, and conduct complex civil (electrical/environmental/mechanical) engineering projects; Assesses the state of the art in the field of study. Applies, independently and creatively, appropriate engineering theories and tools towards developing a viable solution for the project. Designs and conducts activities specific to the project. Demonstrate the ability to communicate effectively the results of a comprehensive research project through oral presentations and publications. Creates a report reflecting the integration of knowledge acquired through the project. Delivers an oral presentation to peers summarizing the work performed on the project and its outcomes. Synthesizes and presents the relevance of the engineering project in both technical and non-technical terms. [-]

Master in Artificial Intelligence and Distributed Computing

Universitatea De Vest Din Timisoara
Campus Full time September 2017 Romania Timisoara

The Faculty of Mathematics and Computer Science offers study programmes in mathematics and informatics for around 1200 students. The Department of Computer Science offers BSc study programmes in Informatics (in Romanian and in English) and Applied Informatics (in Romanian), MSc study programmes in Artificial Intelligence and Distributed Computing (in Romanian and in English), Software Engineering (in Romanian) and Applied Informatics in Science, Technology and Economics (in Romanian), PhD programmes in Cloud Computing, High Performance Computing, Artificial Intelligence, Automated Reasoning and Theoretical Computer Science which are also the main research directions of the department members. [+]

Masters in Computer Science. The Faculty of Mathematics and Computer Science offers study programmes in mathematics and informatics for around 1200 students. The Department of Computer Science offers BSc study programmes in Informatics (in Romanian and in English) and Applied Informatics (in Romanian), MSc study programmes in Artificial Intelligence and Distributed Computing (in Romanian and in English), Software Engineering (in Romanian) and Applied Informatics in Science, Technology and Economics (in Romanian), PhD programmes in Cloud Computing, High Performance Computing, Artificial Intelligence, Automated Reasoning and Theoretical Computer Science which are also the main research directions of the department members (for details see http://research.info.uvt.ro). The Artificial Intelligence and Distributed Computing Masters Programme taught in English aims to offer competences in designing intelligent systems with application in various scientific and technical fields and in using the most recent technologies in high performance computing and distributed computing. It is a two years programme organized in three semesters devoted to teaching and a fourth one focused on research activities and the MSc thesis preparation. The students have the opportunity to use the infrastructure of the High Performance Computing Lab (http://hpc.uvt.ro), participate to international research projects and to industrial projects conducted in collaboration with IT companies. Main course titles Distributed Systems Parallel Computing Systolic Algorithms Workflow Technologies Multi-agent systems Operational Research and Optimization Data Mining Term rewriting Metaheuristic Algorithms Advanced Logical and Functional Programming Distributed Methods and Technologies based on XML Automated Theorem Proving Data Structures and Algorithms in Parallel Computing Potential labour market positions following graduation The graduates can target positions in IT industry as distributed systems engineer, high performance computing software engineer, cloud platform developer, data scientist/engineer, machine learning engineer, analytics engineer. They can also choose a PhD path oriented toward cloud computing and/or machine learning, fields which are currently in high demand of specialists. The students interested in research can be involved in the projects conducted at the e-Austria Research Institute (http://www.ieat.ro) The HPC lab from the West University of Timisoara includes one of the most performant computing infrastructure in Romania. [-]

Master's Programme in Embedded Sensor Systems

Mid Sweden University
Campus Full time September 2017 Sweden Sundsvall

Embedded Sensors can be found in all application domains: home/consumer electronics, medical electronics, vehicles, industrial, military and aviation and space. This Master Programme is design to provide the students with knowledge and understanding of technologies, method and tools for analysis and design of embedded sensors systems - both conceptually and in-depth. [+]

The courses in this master programme are designed to cover major aspect relating to design of embedded sensors systems such as sensing, processing, communication and energy supply with consideration for underlying technologies, design method and optimization, energy/power efficiency and measurement system. Programme students will participate with other international students in group- and individual-projects to acquire a deepened knowledge in a specific area through individual projects. Entry requirements Degree of Bachelor, Degree of Bachelor of Science in Engineering (at least 180 Credits), or equivalent, in Electrical Engineering/Electronics, Computer Engineering, Physics or Mathematics, with at least 22.5 Credits (22.5 ECTS) in Mathematics/Applied Mathematics and at least 15 Credits (15 ECTS) in Electronics Engineering. English course 6/English course B from Swedish Upper Secondary School (Gymnasium) or the equivalent. Title of qualification Degree of Master of Arts/Science (120 credits) Masterexamen med huvudområdet elektronik, translated into Degree of Master of Science (120 credits) with a major in Electronics or Teknologie masterexamen med huvudområdet elektronik, also translated into Degree of Master of Science (120 credits) with a major in Electronics, if the student has former studies of at least 30 credits in the subject of Mathematics. After the program After having completed the programme you will be able to work with research and development at high-tech companies specialising on for example telecommunication, multimedia and industrial electronics systems. Work experience contact We consider it important for business development and education to be closely linked. The programme is developed together with the industry based on their needs; this is why your project assignments have their starting point in problems identified by the companies or research institutes we are collaborating with. [-]

MicroMasters Programme in Artificial Intelligence (Columbia University)

edX MicroMasters Programs
Online Full time Part time 48  January 2017 USA Cambridge + 1 more

Earn a MicroMasters in Artificial Intelligence from Columbia University to launch your career in computer science and design the future. [+]

Masters in Computer Science. Average Length: 12 weeks per course Effort: 8-10 hours per week, per course Number Of Courses: 4 Courses in Program Subject: Engineering, Computer Science, Physics Institution: Columbia University Institution Offering Credit: Columbia University Language: English Video Transcripts: English Price (USD): $300 per course Earn a MicroMasters in Artificial Intelligence from Columbia University to launch your career in computer science and design the future. Gain expertise in one of the most fascinating and fastest growing areas of computer science through an innovative online program that covers fascinating and compelling topics in the field of Artificial Intelligence and its applications. This MicroMasters Program from Columbia University will give you a rigorous, advanced, professional, graduate-level foundation in Artificial Intelligence. The program represents 25% of the coursework toward a Masters degree in Computer Science at Columbia. Job Outlook Though Artificial Intelligence is one of the fastest-growing areas for high-tech professionals, there are too few qualified engineers, according to a recent Kiplinger report. Robotics and artificial intelligence will impact wide segments of daily life by 2025, with huge implications for a range of industries such as health care, transport and logistics, customer service, and home maintenance. (Pew Internet) The need for AI specialists exists in just about every field as companies seek to give computers the ability to think, learn, and adapt. (IEEE) Exciting and rewarding career opportunities as a Machine Learning Software Engineer, Deep Learning Specialist, Data Scientist, Automation Engineer, 3D Artist, Computer Vision Engineer, and many more! What You'll Learn: Solid understanding of the guiding principles of AI. Apply concepts of machine learning to real life problems and applications. Design and harness the power of Neural Networks. Broad applications of AI in fields of robotics, vision and physical simulation. MicroMasters Program Details How To Earn The MicroMasters Credential Complete, pass and earn a Verified Certificate in all four courses to receive your MicroMasters Credential. Learners who successfully earn the MicroMasters Credential are eligible to apply to the Master of Computer Science program at Columbia University. Take your Credential to the Next Level If a student applies to the Master of Computer Science program at Columbia and is accepted, the MicroMasters Credential will count toward 25% of the coursework required for graduation in the on campus program. Courses Artificial Intelligence (AI) Learn the fundamentals of Artificial Intelligence (AI), and apply them. Machine Learning Master the essentials of machine learning and algorithms to help improve learning from data without human intervention. Animation and CGI Motion Learn the science behind movie animation from the Director of Columbia’s Computer Graphics Group. Robotics Learn the core techniques for representing robots that perform physical tasks in the real world. What is a MicroMasters Program? Developed to advance a career and born from Master's programs of leading universities, MicroMasters programs are a series of higher-level courses recognized by companies for real job relevancy, and may accelerate a Master's degree. [-]

Master in Computer Science

Marconi University
Campus Full time 12  October 2017 Italy Rome

The Master in Computer Science responds to this need and represents an important opportunity of vocational training on: development/implementation of information systems architecture; development, management and maintenance of business databases; implementation of guidelines for software development; knowledge and implementation of policies for the security and reliability of systems and the web. [+]

With the spread of information technologies into contemporary lifestyles and into many different professional contexts, it is evident how important is to meet the growing demand for high-qualified learning programs for the development and project of effective and innovative IT solutions. The Master in Computer Science responds to this need and represents an important opportunity of vocational training on: development/implementation of information systems architecture; development, management and maintenance of business databases; implementation of guidelines for software development; knowledge and implementation of policies for the security and reliability of systems and the web. A student is granted a Master’s degree after successfully defending his or her final thesis in front of a panel of judges. Grading is based on a scale of 0-110; 66 is the passing grade and students who obtain full marks of 110 may also be awarded ‘summa cum laude’ (110 e lode). The final thesis of the Master’s program, intended to assess the technical, scientific and professional preparation and competences of the student, requires the completion, discussion and presentation of a written project work during the dissertation. The MCS degree program consists of four modules: Computer networks (12CFU/ 9 quarter credits), Database (12CFU/ 9 quarter credits), Software engineering (18CFU/ 13.5 quarter credits) and Security (12CFU/ 9 quarter credits). Module 1 – Computer networks – MCS_E_M1 CFU/ECTS 12 – US QC 9 The module allows you to have in depth knowledge of computer and telecommunication networks. A description of the layers will be given: physical, data links and the network and transport of the OSI model. Furthermore, the features of the main systems used in geographical areas will be described such as telephone networks and cell phone systems, as well as metropolitan areas such as WiMax where protocols and structures will be explained. Lastly, the functioning of IPv6 will be considered. Module 2 – Database – MCS_E_M2 CFU/ECTS 12 – US QC 9 The module aims to present the system characteristics, their architecture and the principles that they aspire to, based on database technology and in particular on the relational ones. They deal with the application design point of view and, in addition, the systems for data management, interrogation languages and design methodologies will be studied on the databases themselves. They will deal with automatic information retrieval systems from heterogeneous and distributed sources by giving the skills needed to understand the processes and techniques of information processing which characterize today’s search engines and their applications. Particular emphasis will be given to automatic learning technologies which allow for the rapid development of systems based on the reutilization of data and available knowledge in electronic format within open sources. Module 3 – Software Engineering – MCS_E_M3 CFU/ECTS 18 – US QC 13,5 The module’s objective is to understand the more advanced aspects of object oriented programming by using Java as the language of reference. The software industrial production process will be defined, by highlighting the lifecycle of the software product from the requirements stage to the implementation and integration stage according to the most modern object oriented methodologies. The knowledge for the analysis, design and quality software systems implementation will be given, by focusing on the description of the software development stages. Furthermore, the methodologies developed for complex problem analysis will be described in order to evaluate the complexity of each approach and to identify the structures and strategies to resolve them. Module 4 – Security – MCS_E_M4 CFU/ECTS 18 – US QC 13,5 The module intends to give the know how in order to understand the different aspects in which we articulate the theme of security in computing systems. The technical aspects relating to cryptography, system and network security will be dealt with, as well as the managerial and normative point of view. The capacity of dealing with the digital signals which must be transmitted remotely or stored on a device will be considered, whose purpose is to reduce redundancy and increase the probability of correct information retrieval after the transmission or storage. Learning Objectives The Master enables students to project, develop, create, manage and maintain business information systems and is specifically focused on the physical structure of the information network. Moreover, the Master provides students with the basics in the field of the development of software and the management of business databases, web applications and mobile technology. Outcomes and Professional Profile The Master in Computer Science intends to form high-skilled professionals able to work in public and private organizations worldwide as business information systems managers. [-]

Master of Computer Science

Universiti Putra Malaysia
Campus Full time 1 - 3  January 2017 Malaysia Selangor

The Master of Computer Science is a 40 credits postgraduate programme by course work. It offers an opportunity for advanced studies and career development in the field of computer science. The objective of this programme is to produce graduates with new technology in the field of computer science. [+]

Masters in Computer Science. Master of Computer Science The Master of Science programme provides students with specialisation education in the various fields of computer science. This is achieved through a completion of academic course work in the major fields with an independent research project. A student pursuing a Master of Science programme may complete the programme after a minimum period of one year and a maximum period of three years. The Master of Computer Science is a 40 credits postgraduate programme by course work. It offers an opportunity for advanced studies and career development in the field of computer science. The objective of this programme is to produce graduates with new technology in the field of computer science. Specialisation Areas: Distributed Computing [-]

Master of Data Science

Harbour.Space
Campus Full time Open Enrolment Spain Barcelona

The MSc Data Science programme is designed for those who desire to deepen their comprehension of all aspects of the data sciences. Applicants could be graduates from other degrees with a strong mathematical core, or those continuing their academic pursuit after achieving a BSc in data science. [+]

This program is taught in ENGLISH. The Master Degree program in Data Science is designed for those who desire to deepen their comprehension of all aspects of data science. Applicants could be graduates from other degrees with a strong mathematical core, or those continuing their academic pursuit after achieving a bachelor degree in computer science. PROGRAM STRUCTURE Year 1 Students begin the programme with foundational knowledge of programming and mathematics, including data structures and algorithms, statistics and machine learning. During the first year their knowledge of mathematics, programming and data analysis will be significantly extended. The programme also offers the opportunity to obtain key soft skills for the professional world including technical project management, writing and presenting. Finally, students are expected to attend a substantial amount of talks and workshops offered by the university, as well as working on the Capstone project. Modules Combinatorics And Graphs Convex Optimization Information Theory Discrete Optimization Auctions Stochastic and Huge-Scale Optimization Computability And Complexity Probability and Statistics Statistical Data Analysis Machine Learning C++ JAVA Python Practical Unix Data Structures and Algorithms Parallel and Disrtibuted Computing R Databases Technical Writing and Presenting Technical Project Management Leadership and Group Dynamics Introduction to Interaction Design Web Graphs Capstone Project Seminars & Workshops Year 2 During the second year of the program students will primarily focus on learning the key applications of the data science as well as advanced methods in mathematics and data analysis. A significant part of the year will be allocated to the completion of the capstone project. Through completion of the programme, students will learn to conduct data analysis on any scale, develop the software necessary for analysis and present the results in a professional and efficient ways. Modules Nonlinear Optimization Robust Optimization Machine Learning Statistical Data Analysis Machine Learning on Big Data Stochastic and Huge-Scale Optimization Data Visualization Map Reduce Distributed Databases Technical Writing and Presenting Leadership and Group Dynamics Technical Project Management Big Data Analysis Cryptography Social Network Analysis Image And Video Analysis Text Mining Information Retrieval Machine Translation Algorithms in Bioinformatics Spectral Graph Analysis And Data Science App Capstone Project Seminars & Workshops MATH AS A SECOND LANGUAGE (MSL) A Harbour.Space major requirement for all students in tech is a very good level of math. Anyone who lacks the strong math foundation they need for a career in tech, but is eager to learn has a home in our foundation course (link). Students acquire all the basic tools they need to continue studies in Computer Science, data Science or Cyber Security. Graduating from MSL means opening the doors to apply for a place at Harbour.Space University and any other top-rate tech university in the world. Programme Leadership Andrei RaigorodskiiDr.Sci, PhD, Chair of the Department of Discrete Mathematics Konstantin MertsalovPhD, Director of Software Development Europe, Rational Retention Career Path Junior Data Scientist Data Scientist Senior Data Scientist Principle Data Scientist Chief Data Officer LIVING IN BARCELONA Studying in Barcelona has the following advantages: Barcelona is #1 in Europe for quality of life and clearness of environment (2012 Quality of Life City Rankings – Mercer Survey) Barcelona is #1 in the world for the level of infrastructure and urban development (2011, Ernst & Young). The region of Catalonia, where Barcelona is the capital, contributes significantly to the Spanish GDP. The growth of Catalonia’s GDP is currently 3.3%, much higher than in Europe on average. Catalonia’s exports are €42.2 billion, higher than in any other region of Spain. 7,000+ innovation and technological companies during the last 10 years. Barcelona is 6th in Europe for attractiveness and comfort for doing business (European Attractiveness Survey 2011, Ernst & Young), Barcelona is 2nd in Europe (after London) for being promoted as a business center (European Cities Monitor 2011); Barcelona is 2nd in the world for hosting different international conferences and congresses (City and Country World Report 2011, ICCA ). Barcelona is the host of the annual World Mobile Congress, which attracts thousands of international companies that work in the mobile industry. 7,000,000 + millions of tourists / year 20° C - average temperature during the day 2437 hours of sunshine/ year Cost of living 550 euro / month [-]

Master of Applied Computer Science

Saint Xavier University
Campus Full time September 2017 USA Chicago

The Master of Applied Computer Science (MACS) program is designed to further students' understanding of the computing technologies shaping our world today. [+]

Masters in Computer Science. Master of Applied Computer Science The Master of Applied Computer Science (MACS) program is designed to further students' understanding of the computing technologies shaping our world today and to prepare students for sustaining a life-long contribution to a technology-related career. The MACS program provides students with a theoretical and practical understanding of important areas in the computing field. This program may be completed in two semesters by completing 16 credit hours each semester, or in three to four semesters by spreading the courses over a longer period. A Master of Business Administration (MBA) degree may be completed by taking an additional 24 graduate credit hours from the Graham School of Management, which can be completed in one additional year. Five-Year Option Get a bachelor's and master's degree in just five years! The Department of Computer Science is excited to announce this new option for all incoming freshmen. You can... Complete the requirements for the Bachelor of Science (Computer Science) or Bachelor of Arts (Computer Studies) and in the fourth year take two graduate level courses in computing that will count for eight hours towards the general electives in your bachelor’s degree and also eight hours towards your master’s degree. In the fifth year, you take 24 hours (six courses) of graduate courses to complete the master’s degree. You may also delay graduating with the bachelor’s degree until the end of the fifth year, and then graduate with both the master’s and bachelor’s degrees at the same time. This is an advantage because although you will be taking graduate courses, SXU will consider you to be an undergraduate and not only charge you undergraduate tuition but also allow you to use your financial aid package in the fifth year. However, since every student’s situation is different, you should check with the Financial Aid Office before making this decision. Entrance Requirements The MACS program is designed for students with a bachelor's degree in computer science or a related field. However, a student with a non-computer-related degree may substitute relevant work experience as a prerequisite for entry into the program. College graduates who have not worked or studied in a computing field may become eligible for the program by addressing their deficiencies, either by taking courses at Saint Xavier University prior to their enrollment in the program (a conditional acceptance will be considered) or by providing documentation that they have completed similar courses at another institution. Students wishing to pursue this option should consult with the program director. Students with no experience in programming will be required to gain proficiency in one programming language (for example, Visual Basic, C, Java or C++) prior to acceptance into the program. In some cases a student may be required to complete an introductory computing course. Please contact the program director for advice on fulfilling these requirements. Program Requirements The master of applied computer science degree requires 32 credit hours of graduate course work consisting of at least 20 credit hours at the 500-level and at most 12 credit hours at the 400-level. Required Courses (20 credit hours from the Following, including ACSG-599): ACSG 520: TCP/IP Architecture and Protocols (4) ACSG 540: Programming Languages for the Web (4) ACSG 561: Systems Analysis and Design (4) ACSG 570: Computer Systems Security (4) ACSG 591: Special Topics (4) ACSG 599: Graduate Capstone Course (1-4) Elective Courses (Select 12 credit hours from the following): ACSG 400: Current and Future Trends of the Internet (4) ACSG 405: Project Management for Information Technology (4) ACSG 425: Data Communications and Wireless Networking (4) ACSG 430: Mobile Applications (4) ACSG 435: Cloud Computing (4) ACSG 450: Digital Forensics (4) ACSG 452: Advanced Database Topics (4) ACSG 455: Open Source Software (4) ACSG 460: Special Topics (4) ACSG 465: Usability and Design (4) ACSG 545: Software Engineering (4) ACSG 575: Information Ethics (4) ACSG 592: Independent Study (1-4) ACSG 593: Directed Study (1-4) ACSG 594: Internship (varies) Application Requirements Below are the requirements for the master of applied computer science program: 1. A completed application form (PDF). 2. Official transcript(s) sent directly from the registrar of the accredited baccalaureate degree-granting college/university and all graduate level coursework. 3. A non-refundable $35 application fee, unless applying online. 4. Personal statement. In approximately 300 words, please address (1) your personal career goals, (2) how you developed an interest in computer technology and the Internet, (3) your computer background and proficiency, (4) how this program fits into your goals, (5) what skills and experience you bring to the program, and (6) what are your needs and expectations of the master of applied computer science program? 5. Two completed recommendation forms. Recommendation forms must be completed by individuals (supervisors, professors, coworkers, etc.) who can attest to your academic competence, professional skills and character. Graduates of Saint Xavier University need not submit recommendations, unless specifically asked to do so after submitting the application. 6. If admitted into the program, an advisor will review your resume and transcripts. Students who have not worked in the information systems field and/or do not have a computer based undergraduate degree may need additional coursework. Apply online for the master of computer science (MACS) program or request an information packet by mail. [-]