Online Master's Degree in Big Data in Europe

Search Online Masters Programs in Big Data in Europe 2017

Big Data

A masters refers to the completion of a graduate study program that prepares students to further their knowledge of a specific subject or advance their careers. The majority of masters are granted by state or public universities.

A student who does well in advanced mathematics and computer science may choose to study big data. This field deals with large data sets that must be analyzed as a unit instead of as individual points. There are applications for both the public and private sectors.

There are more than four thousand higher education organizations in Europe, from leading research institutions to small, teaching-focused universities. Europe itself is not as much different than other continents, reaching from the Arctic Circle to the coast of Africa.

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Master in Data Science

Bologna Business School
Campus Full time 12 months December 2016 Italy Bologna

The Master in Data Science is designed for recent graduates interested in management and data analysis and whom would like to take on a role which is central to any business and its value creation: the Data Scientist, having already become one of the most sought-after experts in the professional world. The data business is becoming a key sector for the European economy, the development of products and... [+]

Top Online Masters in Big Data in Europe. The Master in Data Science is designed for recent graduates interested in management and data analysis and whom would like to take on a role which is central to any business and its value creation: the Data Scientist, having already become one of the most sought-after experts 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. In one word: Big Data, but not exclusively. Companies, in fact, have both a need and an urgency to manage the acquisition, presentation, sharing, analysis and visualization of data. The 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, am understanding of the technological aspects and knowledge of business dynamics. This Master creates professionals with across-the-board skills whom are able to relate with the company’s management. The program concludes with a Field Laboratory Work and a company internship. 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 three terms: First cycle: December 2016 – April 2017 Second cycle: April 2017 – July 2017 Internship: August 2017 – December 2017 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. Fees The tuition fees for the 2016/2017 academic year are 14,800 euros to be paid in several instalments, the first one upon enrollment. The fees cover all academic materials via the online learning platform, all the facilities of the Alma Bologna Business School including use of the computers and secure personal Wi-Fi accounts, access to the study areas and gym, as well as student discount in the School’s cafeteria. Free parking is also available within the grounds of the School. In addition, with your University of Bologna Student Card you will have access to all university facilities with more than 100 libraries (including online subscriptions and databases), the 3 city centre canteens and all university student related discount offers. Scholarship/Financial Aid At Bologna Business School we understand the importance of financial aid in supporting our students in achieving their educational goals. We are aware that an advanced, high quality training path can be a significant commitment but we also truly believe that investing in one’s future always pays back. Bologna Business School is pleased to offer partial scholarships to the most meriting students: there are scholarships of 6,000 euros each and scholarships of 4,000 euros each. All applicants will be considered for a scholarship – no specific application is required. Thanks to the agreement between Bologna Business School and Intesa Sanpaolo, participants are eligible to apply for “PerTe Prestito Con Lode”, a long-term and low-interest honor loan. Main characteristics: Loan amount equal to the enrollment fee Reduced interest rate No collateral required Repayable in 10 years Without early closing fees [-]

Master's Programme in Molecular Techniques in Life Science

Karolinska Institutet
Campus Full time 2 years August 2017 Sweden Stockholm

The programme is a unique collaboration between Karolinska Institutet, KTH Royal Institute of Technology and Stockholm University, in the environment of Science for Life Laboratory, Stockholm. [+]

The programme is a unique collaboration between Karolinska Institutet, KTH Royal Institute of Technology and Stockholm University, in the environment of Science for Life Laboratory, Stockholm. The students will receive a comprehensive education in life science emphasising cutting-edge methods in bioinformatic analysis of big data, combined with state-of-the-art techniques used in modern "high throughput" molecular biology and how to translate biological findings into diagnostic tools and novel treatments. Programme presentation This two-year Master’s programme is delivered by a team of teachers who are internationally recognised researchers in their respective disciplines to ensure a relevant curriculum at the research forefront. The programme consists of courses aiming to give a solid education in a combination of molecular biology, biotechnology and medicine with a focus on high-throughput biology and analysis of big data for translation of biological findings from lab bench to patient bedside. The education also aims to develop skills and abilities essential to the professional career –including oral and written presentation, team working skills, and how to make ethical and societal considerations about life science related issues, all of which important for the ability to lead projects in academy and industry. Courses - Master’s programme in Molecular Techniques in Life Science *might be subject to changes Year 1 The first year contains advanced level courses in genetics, biophysical chemistry, and translational medicine, as well as the foundations of bioinformatics and comparative genomics. There is also a project course. All three universities offer courses during the first year, with an emphasis on Karolinska Institute (fall semester) and Stockholm University (spring semester). Mandatory courses fall semester Frontiers in life science 1 Frontiers in translational medicine Applied communication Genetics Mandatory courses spring semester Frontiers in life science 2 Bioinformatics Project in molecular life science Comparative genomics Biophysical chemistry Year 2 The second year offers courses in applied gene technology, proteomics, drug design, and bioinformatics analysis of large-scale data. There is also a project course. Most courses during the fall semester are offered by KTH Royal Institute of Technology. During the spring semester, the individual degree project is performed. Mandatory courses fall semester Frontiers in life science 3 Project in molecular life science Proteomics Drug development Applied gene technology Analysis of data from high-throughput molecular biology experiments Mandatory courses spring semester Degree project The application process for the programme will be handled by the Royal Insititute of technology (KTH) in collaboration with Stockholms universitet (SU) and Karolinska Institutet (KI). Career opportunities The combination of molecular biology, biotechnology and medicine provides an excellent profile for a professional research career in an academic setting or in the biotechnological and pharmaceutical industry. The life science industries and academic institutions working in these areas are active and the life science sector is expanding worldwide, which gives students an excellent job market and wide range of possible employments. Application and tuition fees If you have citizenship within the EU/EEA, or Switzerland, you are not required to pay application or tuition fees. Application fee 900 SEK Tuition fee Total amount: 400 000 SEK First instalment: 100 000 SEK [-]

Master of Data Science

Harbour.Space
Campus Full time 2 years Open Enrollment 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. [+]

Top Online Masters in Big Data in Europe. 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 2 in Econometrics and Empirical Economics (EEE)

Toulouse School Of Economics TSE
Campus Full time September 2017 France Toulouse

The EEE M2 program provides in the first semester a solid training in microeconometrics, time series, panel data models, non-parametric methods, large dimension statistical tools, computer programming, and database management system. [+]

Aims and Scope This master aims at providing econometric and empirical analysis tools combined with strong skills in using large data sets in order to perform deep studies in a broad area of economics. The EEE M2 program provides in the first semester a solid training in microeconometrics, time series, panel data models, non-parametric methods, large dimension statistical tools, computer programming, and database management system. In the second semester, students apply these training to do empirical studies in industrial organization, finance, public policy evaluation programs, health and insurance, data analytics and big data. Courses are taught in English by TSE faculty members with well-established international reputation in econometrics, empirical economics, industrial organization, and finance among others. This training is completed with an empirical project done during the whole year in a group of students. Admission Admission is based on academic excellence. An undergraduate degree of at least 4 years of college or a Master’s degree is required with a curriculum considered as consistent with the program and approved by the TSE selection committee. Working knowledge of English is also required. Application deadlines: Applications are considered from November to the end of February for international students and in April/May for French University graduates. Fees 5500 euros + 256 euros : Master registration fees + 215 euros: Social Security Scholarships: Some Master scholarships will be awarded to Master students according to academic and individual criteria [-]

Master's Programme in Information Technology

Åbo Akademi
Campus Full time 2 years August 2017 Finland Vaasa Turku + 1 more

The programme gives you a broad education covering several different fields within computer science and computer engineering. [+]

Top Online Masters in Big Data in Europe. Degree awarded: Master of Science (Technology) or Master of Science Annual intake: 30 Contact: mit@abo.fi Website: www.abo.fi/mit Facebook: www.facebook.com/groups/aamasterit/ The programme gives you a broad education covering several different fields within computer science and computer engineering. You will obtain the necessary knowledge and experience which is needed in different types of careers within the software industry (for example supercomputing, e-health, IT security, formal methods, embedded systems and software engineering), in the biotechnology industry (for example, bioinformatics, computer modeling), in the data analysis industry (for example, machine learning, customer segmentation, data-driven business). Admission to the master's programme in Information Technology gives you the right to take the Master of Science degree in Computer Science or the Master of Science (Technology) degree in Computer Engineering. In Computer Engineering you can either focus on Software Engineering or Embedded Computing. Students applying to the Master's Programme in Information Technology will be able to rank the three available tracks (Computer Science, Embedded Computing and Software Engineering) in order of preference in the application form.The second and the third preference can be optionally added. In the admission decision, the student will be notified if s/he can be admitted to the track of first preference, or to the tracks of second or third preference. We are located in the recently renovated Agora building, where research groups and academic programmes from both Åbo Akademi University and University of Turku, meet, interact, and collaborate. The study facilities are brand-new and equipped with the latest technology. The programme is affiliated with the Turku Center for Computer Science (​​ TUCS​) graduate school, which coordinates all research and education in IT in both universities in Turku (University of Turku and Åbo Akademi University). Through TUCS, the students can take advantage of advanced-level courses offered by both universities. Admission requirements A completed university level Bachelor’s degree in Computer Science or Computer Engineering or in a closely related field is required for admission. Eligible applicants are selected on the basis of how well the bachelor’s degree corresponds to the programme and on the study merits of the student. We expect the applicant to has passed courses in several of these areas: Mathematics Basic computer science courses ( e.g. algorithms and data structures, operating systems, computer networks and protocols, compiler construction) Basic courses on computer architecture, computer network or system design Programming courses (e.g. courses in C/C++ or Java programming) Applicants to the Master's degree programmes taught in English must always prove their knowledge of the English language. For more detailed information on admission requirements, please check admission requirements and application procedures. No entrance examination. Admission is granted on the basis of the application. How to apply? For more information on the application requirements and procedures, tuition fee and scholarships, please see http://www.abo.fi/ansok/master [-]

International Master in Project Management & Data Science

HTW Berlin University Of Applied Sciences
Campus Full time 4 semesters October 2017 Germany Berlin

In the world's corporate environment it is highly important to be familiar with the international context and have a better understanding of it. The Master’s degree programme in Project Management and Data Science at HTW Berlin will help you to successfully manage and supervise projects in the international environment as well as facilitate, process and interpret extensive datasets and carry out analyses across different disciplines. [+]

Innovation and Diversity HTW Berlin, the largest University of Applied Sciences in Berlin, is defined by its future-oriented range of programmes and courses, consistently covering areas of current interest as well as those with longer term appeal. Increasing quantities of data are being generated across numerous industries and service provision areas and the international Project Management & Data Science Master’s Programme was developed in order to tackle the shortage of qualified staff in this area. Data related to customers, markets and competitors is extremely important in today’s commercial landscape. Sensitive and responsible handling of data is an important success factor for all manner of companies. “Big Data” – the intelligent management of large and simultaneously heterogeneous data – is one of the biggest commercial challenges of our times. The processing and analysis of this volume of data also generates extremely far-reaching findings. In the fight against cancer, for instance, Molecular Medicine uses vast quantities of data to develop individual treatments and therapies. Many firms have identified the lack in project handling and business analytics skills. They invest billions of dollars in training for employees in the areas of Project Management and Data Analytics. With quintillion bytes of data being generated every day, qualified managers are required who can appropriately assess this data and use it for managing projects in an industry and company-specific way. The combination of Project Management and Data Science studies therefore represents a comprehensive and in-demand academic qualification. It opens up a diverse range of commercial, creative and organizational opportunities and career paths. Graduates of the Master’s Programme Project Management and Data Science will possess a broad range of techniques and methodologies which are of huge interest to businesses today. Their extensive knowledge will equip them with the skills to increase efficiency and reduce costs in complex business processes. The Master of Science qualification offers graduates a wide range of potential areas of application as well as opportunities for career advancement. International context In the world's corporate environment it is highly important to be familiar with the international context and have a better understanding of it. The Master’s degree programme in Project Management and Data Science at HTW Berlin will help you to successfully manage and supervise projects in the international environment as well as facilitate, process and interpret extensive datasets and carry out analyses across different disciplines. Ideally prepared for a successful career This specialisation is based on our survey of major German industrial companies, which revealed a strong demand for internationally oriented project management specialists and data scientists. During this program you will acquire international skills by working together with students of different nationalities and background. Since the programme is taught entirely in English, you will also be ideally prepared for the international labour market. Language skills in German are not necessary. International and practice-oriented During your studies you will acquire knowledge of business administration with an international basis. The curriculum focuses on different areas of project and Information Management, various Data Analysis techniques as well as HR and Marketing. Deep knowledge of statistics is not required. Excellent Career Prospects Project Management & Data Science M.Sc. The rapid increase in data generation is resulting in a huge demand for Big Data specialists – specialists who possess the skills to efficiently and effectively organize the growing volume of information. In today’s workforce, there is already a lack of several hundred thousand managers qualified to tackle complex and interrelated managerial tasks. Standard period of study 4 semesters / incl. last semester thesis / 2 years: Master of Science (M.Sc.) First semester: International Project Management I, Foundations of Data Analytics and Statistical Programming, Contract and International Business Law, elective: Group Facilitation, Technology Management in Practice or Negotiation Techniques Second semester: International Project Management II, Advanced Computational Data Analytics, Change Management and Leadership, Financial Reporting and Management Information Systems Third semester: Project Management and Data Analytics Lab, Advanced Data Mining Techniques, Databases and Big Data, Practical Data Governance, Data Security and Regulatory Compliance, elective: Group Facilitation, Technology Management in Practice or Negotiation Techniques Fourth semester: Thesis and oral exam All modules are planned and structured in an extremely practice‐oriented manner. Cooperations with world leading companies are included. The modules involve working through specific questions during case‐studies and project simulations. Human resource, soft skills, intercultural topics and trainings, in particular, are covered. Other programmes at the HTW See also our international Industrial Engineering programme, Master of Business Administration & Engineering here. [-]

International Master in Business Analytics & Big Data (BABD)

MIP Politecnico di Milano School of Management
Campus Full time 12 months September 2017 Italy Milan

Business Analytics and Big Data is an innovative programme based on a holistic educational experience, where theory and practice are fully interlaced through the continuous support of companies and international partners. Furthermore, being in constant relationship with the Big Data Analytics & Business Intelligence Observatory of Politecnico di Milano, the course is at the forefront of research on ICTs for big data analysis and management. This truly unique programme is jointly offered by MIP and CEFRIEL - Politecnico di Milano and it is in partnership with IBM. [+]

Top Online Masters in Big Data in Europe. In partnership with CEFRIEL Start date: September Format: Full Time Duration: 12 months Tuition fee: € 14,000 Language: English Location: Milan Admission Requirements: 3 or 4 year Bachelor's degree (minimum 180 ECTS) Business Analytics and Big Data is an innovative programme based on a holistic educational experience, where theory and practice are fully interlaced through the continuous support of companies and international partners. Furthermore, being in constant relationship with the Big Data Analytics & Business Intelligence Observatory of Politecnico di Milano, the course is at the forefront of research on ICTs for big data analysis and management. This truly unique programme is jointly offered by MIP and CEFRIEL - Politecnico di Milano and it is in partnership with IBM. With the Big Data revolution an ever-growing number of leading organizations and governments are launching big data initiatives to gain actionable insights, drive key decisions and improve performance across all business functions. Welcome to the International Master in Business Analytics and Big Data designed to train a new generation of data-savvy professionals able to manage complex business analytics problems across a variety of different industries and environments. This truly unique programme is jointly offered by MIP and CEFRIEL- Politecnico di Milano. Be prepared for the jobs of the future as Business Analyst and Big Data Manager. The Partners MIP Politecnico di Milano: a global business school accredited by EQUIS, AMBA, EFMD and ranked by the Financial Times amongst the best European business schools, further complemented by it's deeply rooted knowledge and reputation in the luxury value chain management. The quality of the competencies expressed are also supported by the strong links developed with the Faculty of Engineeirng and Design of Politecnico di Milano, which is the largest one in Europe. CEFRIEL – Politecnico di Milano is a not-for-profit center of excellence in the field of Digital Innovation, established by Politecnico di Milano in 1988. CEFRIEL shareholders include Universities, Public Administration, and leading multinational companies in ICT and Media sectors. Since its inception, CEFRIEL mission has been to strengthen existing ties between the academic and business worlds through a multidisciplinary approach that innovates products and services with ICT and Design. CEFRIEL competences span all areas of ICT expertise, from microelectronics to the most advanced user experience models, addressing both technological and project management issues. CEFRIEL is actually able to merge technical and design skills with business and process expertise, thus working side by side with companies to create innovative and one-of-a-kind solutions, and offering advanced educational programs to graduate students and innovation executive professionals. Moreover, the center actively participates in European research projects and contributes to the dissemination of their results. CEFRIEL offices are located in Italy and USA, Cincinnati (Ohio), so to address the growing innovation demands both of its national and international clients. IBM is a globally integrated technology and consulting company headquartered in Armonk, New York. With operations in more than 170 countries, IBM attracts and retains some of the world's most talented people to help solve problems and provide an edge for businesses, governments and non-profits. Innovation is at the core of IBM's strategy. The company develops and sells software and systems hardware and a broad range of infrastructure, cloud and consulting services. Today, IBM is focused on five growth initiatives - Cloud, Big Data and Analytics, Mobile, Social Business and Security. IBMers are working with customers around the world to apply the company's business consulting, technology and R&D expertise to enable systems of engagement that deliver dynamic insights for businesses and governments worldwide. WHO IS IT DESIGNED FOR? The programme is specifically conceived for graduates who wish to acquire and develop advanced quantitative skills to analyze data describing transactions, interactions or people's behavior, in order to extract relevant insights, optimize actions and drive innovation. Students backgrounds reflect the dual focus of the master, coming from computer science, economics, engineering, management, mathematics, science or statistics. While having different academic backgrounds, students all share a deep interest in analytics and big data technologies for creating business value. Relevant career positions revolve around the roles of data scientist, business analyst and big data manager, and might include among others: Data Users: Business folks in the end user corporate community able to exploit insights from data to make better decisions. Data Producers: Data analysts able to use the appropriate tools to convert analytical problems into analytical solutions. Data Interpreters: Professionals able to understand both users and producers establishing a successful communication among them. Modules The course is entirely taught in English and has a duration of 12 months starting in September. The programme is divided into seven major modules: General Management, Data management and Warehousing, Foundamentals of Statistics and Data Visualization, Predictive Analytics and Business Applications, Analytics for Management and Electives. The master will end with the Project Work to present. Admissions IDEAL CANDIDATES FOR THE PROGRAMME The International Master in Business Analytics and Big Data is specifically designed for young graduated talents that want to be prepared for the jobs of the future as Business Analyst and Big Data Manager. Students with 3 or 4-year Bachelor's degree (minimum 180 ECTS) in the areas of Computer Science, Economics, Engineering, Management, Mathematics, Science or Statistics from Accredited Institutions are eligible for the programme. APPLICATIONS FOR THE 2016 PROGRAMME Applications for the September 2016 intake are now closed. Applications for the September 2017 intake will open in September 2016. Non-EU students are encouraged to apply at least three months before the start of the programme in order to allow enough time for the Declaration of Value (DOV) procedure for Italy and establishment of the student visa. If you would like more information about the International Master in Business Analytics and Big Data, please download our programme brochure by clicking the link, or write to infomasters@mip.polimi.it and we will respond to your requests in a timely fashion. Visit the BABD Frequently Asked Questions page to find out more! [-]

Masters Degree in Data Science

Sapienza University of Rome
Campus Full time 2 years October 2017 Italy Rome

The remarkable increase in the volume and complexity of available data and new technologies that have been developed to process them requires a combined multi-disciplinary approach to design an overall strategy aimed at transforming data into useful information. [+]

The remarkable increase in the volume and complexity of available data and new technologies that have been developed to process them requires a combined multi-disciplinary approach to design an overall strategy aimed at transforming data into useful information. Key ingredients to develop a successful strategy are data manipulation and visualization, large scale computing, statistical modelling, learning techniques, algorithmic thinking. Laurea Magistrale in Data Science is a new Master's degree taught in English. It is a joint initiative within the i3S Faculty combining the expertise of four Departments Informatics (DI) Department of Computer, Control and Management Engineering (DIAG) Information Engineering, Electronics and Telecommunications (DIET) Statistics (DSS) This Master's program provides a solid and modern preparation to understand and manage the multi-facet aspects of carrying out a complete data analysis, including acquisition, management, and statistical analysis. Admission To guarantee that students have the required background, there are some requirements that candidates should satisfy. For Italian students, these are: They must hold a 3-year bachelor's degree (laurea trienale) The must have acquired at least 90 credits in the following scientific sectors: Mathematical sciences: MAT/* Informatics: INF/01 Physics: FIS/* Economical and statistical sciences: SECS-P/*, SECS-S/* Industrial engineering: ING-IND/* Computer engineering: ING-INF/* They must possess basic knowledge from some of the following areas: Matematics: Differential calculus and integration in one or multiple real variables, basic notions of linear algebra and analytical geometry in the Euclidean space Probability: Random variables, distributions and mean values, basic distributions, convergence of sequences of random variables Informatics: Programming principles, knowledge of at least one of the following programming languages: C, C++, C#, Java, Python They must know the english language at a level of at B2 Course Plan First year Semester I ALGORITHMIC METHODS OF DATA MINING AND LABORATORY 9 ECTS FUNDAMENTALS OF DATA SCIENCE AND LABORATORY 9 ECTS STATISTICAL METHODS IN DATA SCIENCE AND LABORATORY I 6 ECTS INTELLECTUAL PROPERTY COMPETITION AND DATA PROTECTION LAW 6 ECTS ECONOMICS OF NETWORK INDUSTRIES 6 ECTS Semester II NETWORKING FOR BIG DATA AND LABORATORY 9 ECTS STATISTICAL METHODS IN DATA SCIENCE AND LABORATORY II 6 ECTS DATA MANAGEMENT FOR DATA SCIENCE 6 ECTS CLOUD COMPUTING 6 ECTS DATA MINING TECHNOLOGY FOR BUSINESS AND SOCIETY 6 ECTS DATA MONITORING ANALYSIS AND COMMUNICATION 6 ECTS STATISTICAL LEARNING 6 ECTS QUANTITATIVE MODELS FOR ECONOMIC ANALYSIS AND MANAGEMENT 6 ECTS Second year Semester I DATA PRIVACY AND SECURITY 6 ECTS SOCIAL AND BEHAVIORAL NETWORKS 6 ECTS SIGNAL PROCESSING FOR BIG DATA 6 ECTS NETWORK INFRASTRUCTURES 6 ECTS OPTIMIZATION METHODS FOR MACHINE LEARNING 6 ECTS STATISTICAL METHODS FOR OFFICIAL STATISTICS 6 ECTS EFFICIENCY AND PRODUCTIVITY ANALYSIS 6 ECTS PROBABILITY AND STOCHASTIC PROCESSES FOR DATA SCIENCE 6 ECTS DIGITAL EPIDEMIOLOGY 6 ECTS Semester II EARTH OBSERVATION DATA ANALYSIS 6 ECTS ECONOMICS OF INFORMATION 6 ECTS BIOINFORMATICS 6 ECTS [-]

Master Web Analytics And Big Data

Spain Business School
Online Part time 10 months February 2017 Spain Madrid

The digital analyst and scientific data are two of the most demanded today and the next few years profiles. This master is aimed at both management level profiles, as middle managers, technical profiles, independent professionals, businessmen, entrepreneurs, etc. In short, any professional who wants to be a leader in the digital business ... [+]

Top Online Masters in Big Data in Europe. Who should attend: The digital analyst and scientific data are two of the most demanded today and the next few years profiles. This master is aimed at both management level profiles, as middle managers, technical profiles, independent professionals, businessmen, entrepreneurs, etc. In short, any professional who wants to be a leader in the digital business. Objectives: Know, understand and apply the fundamentals of any company, but from the perspective of the new market, digital. Learn to interpret the behaviors that users are on the network and especially on our site in order to adapt your products, services and business to what users are demanding. Mastering the most important tools like Google Analytics. Also, make contact with the reality of Big Data is an unstoppable reality that affects both businesses and individuals. Being able to build your own project and get funding for it. In addition, a number of global targets to all programs consisting of: efficiently lead teams, learn to make strategic decisions, develop a global and inclusive vision, master change management and capture management skills. agenda: Module 1: Fundamentals Session 1: technological and legal environment. Session 2: Introduction to laanalítica. Session 3: Objectives and strategy of a website. Module 2: Analyst Session 1: Google Analytics I. Session 2: Google Analytics II. Session 3: Analytics Adobe / Omniture. Session 4: Comscore. Session 5: Excel for analysts. Module 3: Statistical and analytical method Session 1: Social Media Analytics. Session 2: Analytical in e-commerce. Session 3: Qualitative analysis. Session 4: Quantitative analysis. Module 4: Big Data Session 1: Big Data environment. Session 2: Architecture Big Data. Session 3: Analysis of information and knowledge. Session 4: Fundamentals R language and SQL. Module 5: Digital Management Skills Session 1: Public Speaking. Session 2: Emotional Intelligence. Session 3: Communication for leadership. Session 4: Effective presentations. MASTER THESIS PROJECT. Always accompanied by your expert, your project tutor and the head teacher. Additional Information: Those students who wish have the possibility of internships in major companies. This training can be funded by the Tripartite Foundation Reviews of students: Francisco Oviedo • What is the best course? Time flexibility when organizing the study, the implementation of practices to learn the knowledge and the ability to combine it with other activities. Teacher training, with great experience, proximity and speed in resolving doubts. • What can be improved? Some classes over face / webinars doing practical exercises. • Would you recommend the Master or Expert you're doing? Yes I recommend, for the contents, by professionals and flexibility (which is very important). Inma Bonilla • What is the best course? Professional Output • What can be improved? Communication with some teachers more agile • Would you recommend the Master or Expert you're doing? Although I just started, yes. Desiree Lopez • What is the best course? The content of the master and follow-up by the teachers • What can be improved? Creating notifications when a partner shares something in the forums • Would you recommend the Master or Expert you're doing? I think it is highly recommended, although have little time. David Bello • "My name is David and I would recommend the Master in Web Analytics and Big Data Business School of Spain. The master is very complete and has both specific and public speaking courses and leadership courses, which are absolutely necessary for any professional today. Also, I really like the methodology of case study because it allows deeper knowledge of a dynamic and entertaining way. But undoubtedly the most interesting part is the live classes you can see the screen of your teacher as he works with the analytical tool, because it is the best way to learn how to use it. Also, you can see her again after the virtual campus if you have any questions. Last but not least, I would highlight the close relationship of all school staff that will guide you throughout the learning process. Do not think twice, join Spain Business School! " Salido Ernesto Galan "The MAWBD, combining two fields of huge professional projection as Web Analytics and Big Data, presented in a unique training range, enabling you to solve, through the successful formation obtained after the same, various solutions Business Intelligence any possible professional challenge which you must meet. Of the many highlights of the Master, would highlight its innovative character, with a generation of academics and professionals in the sector, which will facilitate direct and immediate access to pointers work environments, balancing training both theoretical and practical, all linked a generalized own demand quality and brand teaches the school. Teacher quality, connected through management positions in digital training environments, helps you to cope from day to possible real situations in your professional field. " [-]

Master in Data Science (DSC)

EIT Digital Master School
Campus Full time 2 years September 2017 Spain Madrid Finland Espoo United Kingdom London France Paris Sweden Stockholm Italy Trento Germany Berlin Hungary Budapest Netherlands Eindhoven + 16 more

Data abounds: social media, manufacturing systems, medical devices, logistic services, and countless others generate petabytes of data on a daily basis. With a wealth of data available, we are at a point in history, where we can conduct analyses to detect, discover, and, ultimately, better understand the world around us. [+]

Why study Data Science? Data abounds: social media, manufacturing systems, medical devices, logistic services, and countless others generate petabytes of data on a daily basis. With a wealth of data available, we are at a point in history, where we can conduct analyses to detect, discover, and, ultimately, better understand the world around us. What are the carier opportunities for Data Science graduates? Become a professional for a career in a highly innovative area: data science. The profession in Data Science is hailed as the “… Sexiest Job of the 21st Century,” by Harvard Business Review in October 2012. The Data Scientist is a professional who simultaneously possesses breadth and depth in scalable data management, data analysis, and domain area expertise, and who is capable of solving real-world problems. This is an opportune time to pursue training in both a challenging and rewarding new field. Join us and embark on a journey of a lifetime! Why Data Science at EIT Digital? Getting value, meaning and answering big questions, are the ultimate goals of Learning Data Science at EIT Digital. Mazen Aly Data Science Master student Eindhoven University of Technology Study Data Science at EIT Digital, where education is provided by renowned universities and where entrepreneurial data scientists of the future are come to being! Farideh Heidari Data Science Coordinator What is Data Science Master at EIT Digital all about? The newly established Data Science Master’s offers a unique academic programme, whereby students can study data science, innovation, and entrepreneurship at leading European universities. In this programme, students will learn about scalable data collection techniques, data analysis methods, and a suite of tools and technologies that address data capture, processing, storage, transfer, analysis, and visualization, and related concepts (e.g., data access, pricing data, and data privacy). How is the programme structured? The first year will be similar at all three DSc entry point universities: Universidad Politecnica de Madrid (UPM), Eindhoven University of Technology (TU/e), and Universite Nice Sophia Antipolis (UNS) with foundations courses, such as data handling, data analysis, advanced data analysis and data management, visualization, and applications. The second year will enable students to concentrate one of six technical specialisation areas of their own choosing. See: specialisations below. An important part of the programme are the Innovation and Entrepreneurship (I&E) courses. The I&E basics course provides an introduction to business & management. Students participating in the DSc track are offered an internship with an industry partner or research centre of the EIT Digital to work on their thesis project. Directly linked to the master thesis is the I&E minor thesis that specifies the requirements, strategy and business plan for the selected thesis project. Students participating in the DSc track are offered an internship with an industry partner or research centre of the EIT-Digital to work on their thesis project. Directly linked to the master thesis is the I&E minor thesis that specifies the requirements, strategy and business plan for the selected thesis project. Where can I study if I choose Data Science? Entry - 1st year Eindhoven University of Technology (TU/e) Universidad Politecnica de Madrid (UPM) Universite Nice Sophia Antipolis (UNS) Exit - 2nd year, specialisation Internet of Things (IoT) at UPM Multimedia and Web Science for Big Data at UNS Process Mining at High Tech Systems, Healthcare, Visual Analytics or Big software at TU/e Distributed Systems and Data Mining for Really Big Data at KTH Design, Implementation, and Usage of Data Science Instruments at TUB Specific Admission Requirements A B.Sc. degree in electrical engineering/ electronics, computer engineering, computer science or information technology is required. The studies should include at least 60 ECTS courses in computer science, computer architecture, or programming, and mathematics including calculus, algebra and mathematical statistics. [-]

ICT Management Engineer

ESAIP Graduate School of Engineering
Campus Full time 3 years September 2017 France Angers

A 3 year programme in French [+]

Top Online Masters in Big Data in Europe. A 3 year programme in French - Security Intelligent Systems - Connected Devices - Big Data & Data science - Digital Management (+) Professional certifications in our in-house training center [-]

Master In Process Management (sap)

Grupo IOE
Online Part time September 2017 Colombia Bogotá Mexico Mexico City Peru Lima Spain Barcelona Brazil São Paulo Madrid Murcia Valencia + 10 more

The name comes from SAP Systems, Applications and Products in Data Processing. This system includes many fully integrated modules. The information is shared, both between modules and between all areas. [+]

The name of SAP comes from: Systems, Applications and Products in Data Processing. This system includes many fully integrated modules. The information is shared, both between modules and between all areas. SAP It establishes and integrates the production system of companies and has a number of modules that constitute a ideal tools to meet the needs of business management around: Finance. Management control. Human Resources. Sales and distribution. logistics Production planning OBJECTIVES: Mastering SAP FI focused on the needs of your company. General working knowledge of the application and the various tools it contains. Specific development of the various business matters that facilitates the use of the application. Programming in ABAP In order to guarantee the quality of this program, Places are limited to 20 students. Remember that your company can provide aid for job training to do so. Consult us without obligation. [-]

Master in Human-Computer Interaction

Umeå University, Faculty of Science and Technology
Campus Full time 2 years August 2017 Sweden Umeå

In addition to the continued development of increasingly powerful and portable personal computers, a range of new artefacts is appearing, including... [+]

Master's Programme in Human-Computer Interaction

 

In addition to the continued development of increasingly powerful and portable personal computers, a range of new artefacts is appearing, including car navigation devices and electronic books, adding to a large number of traditional artefacts, such as cameras, phones, washing machines, and fitness equipment, all of which are IT-artefacts which include advanced information processing components.

 

The trend towards the widespread use of IT-artefacts is one of the key aspects of the so-called "digital transformation", a revolutionary transformation of our culture and society that places a heavy emphasis on information and knowledge. This trend gives rise to new phenomena of human interaction with technology and world. Computational capabilities of the interactive things we use every day, combined with powerful new communication, input, and output capabilities, provide great possibilities for human action but also create numerous problems. Realising this potential effectively and efficiently requires that the interaction between people and IT-artefacts becomes an object of study dealing with both people and technology.... [-]


Master of Science in Computer, Communication and Information Sciences - Signal, Speech and Language Processing

Aalto University
Campus Full time 2 years August 2017 Finland Espoo

The purpose of the major is to provide the students with basics of either signal processing or speech and language processing and the ability to apply those in various fields of science and technology. [+]

Study programme The purpose of the major is to provide the students with basics of either signal processing or speech and language processing and the ability to apply those in various fields of science and technology. Students focusing in Signal Processing are given a strong theoretical background of modern signal processing. This means a toolbox of knowledge on signals and systems modelling, representation through transforms, systems optimization and implementation. Some emphasis is on the most recent research priorities in the field of signal processing in domains of data analysis, compression and storage, communications as well as in representation of signals. In addition, students can obtain even deeper understanding of signal processing and adjacent sciences, or apply signal processing in other fields. Interesting applications include radar systems and networks, data transmission, sensing and tracking of objects and spaces, as well as analysis of technical (machine based) and social (human based) networks. The cyber level of the smart power grid is increasingly important for efficient energy distribution and utilization, offering a platform for applying signal processing methodology for solving essential problems of great societal impact. Students focusing in Speech and Language Processing are provided basics of that field and the ability to apply those in various fields of science and technology. Speech and language processing utilizes signal processing, mathematical modeling and machine learning for statistical language modeling, information retrieval and speech analysis, synthesis, recognition and coding. Applications and research priorities have recently been, for example, speech recognition and synthesis, dictation, subtitling, machine translation, language learning, large-scale video data indexing and retrieval, speech coding and quality improvement in mobile phones and networks as well as in medical research of the human voice. Tuition fees and scholarships Non-EU/EEA students selected in the application round 2017 will be charged tuition fees. Admission requirements General admission requirements The general eligibility requirements are the same for all Master's programmes in the field of science and technology. Please see also the requirements concerning language skills. Eligible applications are then sent to the academic evaluation described in more detail below. Programme-specific admission requirements Applicants to the programme must first meet the general eligibility and language requirements that are common to all Master’s programmes in Science and Technology. Admission criteria to the CCIS programme is a high quality Bachelor’s degree in computer science, software engineering, communications engineering, or electrical engineering. Excellent candidates with degrees in other fields such as information systems, engineering, natural sciences, mathematics or physics will be considered if they have sufficient studies and proven skills and knowledge in the required areas. Required background: mathematics (linear algebra, calculus, probability theory, statistics) programming skills algorithms and data structures software engineering signal processing Knowledge of the following areas is considered an advantage: speech and language processing pattern recognition machine learning project and team work Application documents In addition to the compulsory application documents, the applicants are requested to provide the following, additional documents: at least one original recommendation letter (preferably academic) course descriptions of courses taken in relevant subject areas (see the subject list above) work certificates and certificates of other relevant achievements copies of any publications official transcript of records for other university studies which are not included in the mandatory part of the application GRE or GMAT test results, if available The application should explain full educational history of the applicant. Applicant’s motivation letter (compulsory part of the online application form) should be written in English. For purposes of study guidance, the applicants are asked to indicate already on the motivation letter which track they wish to follow. Also additional application documents described above (recommendations letter(s), course descriptions, work or other certificates, and publications) should preferably be submitted in English. If some other language than English, Finnish or Swedish is used in them, the applicant must provide precise, word-for-word translations of them. [-]

Master in High Performance Computing and Big Data Analytics

UNIVERSITATEA BABEȘ-BOLYAI
Campus Full time 2 years October 2017 Romania Cluj-Napoca

The master’s program aims at providing students with the appropriate tools for further doctoral studies and professional activity... [+]

Top Online Masters in Big Data in Europe. The master’s program aims at providing students with the appropriate tools for further doctoral studies and professional activity. Programme objectives Acquisition of theoretical, applicative and practical knowledge in: - complex systems modelling based on mathematical concepts and methods, and on programming concepts and techniques. - programming and usage on/of computation systems, especially those of high performance, which are necessary for solving real life problems and for simulating complex problem solutions. - exploitation (data-analysis, knowledge-discovering) and visualization of „big data” for computation problems, statistical interpretations, decision processes, or for scientific instruments. - applicative scientific domains where high performance systems are used. - analysis and improvement of software processes. - professional modelling for team work as well as interdisciplinary approaches to research and development. Core courses - Programming Paradigms - Parallel and Distributed Operating Systems - Formal Modelling of Concurrency - Advanced Methods in Data Analysis - Functional parallel programming for big data analytics - Models in parallel programming - General Purpose GPU Programming - Workflow Systems - Resource-aware computing - Data Mining - Grid, Cluster and Cloud Computing - Knowledge Discovery in Wide Area Networks Admission requirements Bachelor degree in Computer Science, Computer Engineering, Computer Science in Economics Tuition fees Students coming from: - EU/EEA – 3000 RON / year - Non-EU countries – 3000 EURO / academic year [-]