Masters in Data Science & Analytics,Data Science & Analytics in ${country}

You will develop the analytical and technical skills to use data science to guide strategic decision making. Explore data mining, machine learning and data visualisation, and develop the skills to communicate data insights to key stakeholders effectively.

Our Master of Data Science is tailored for professionals with a strong mathematical or quantitative background who are passionate about drawing meaningful knowledge from data to drive business decision-making or research output.

The Master of Data Science prepares you for a career in data science giving you the skills needed to deal effectively within the areas of data analysis, data management or big data processing. The course includes topics in statistical and exploratory analysis, data formats and languages, processing of massive data sets, management of data and its role and impact in an organisation and society.

You will be able to apply your learning, knowledge and skills as part of the assessment process and have the opportunity to complete either a research project or an industry experience studio project.

This Master's course aims to accelerate your career in engineering or data science, enabling you to choose a path that’s right for you. This could be as a data scientist, a machine learning engineer, or a computational statistician.

This is an online and part-time course. This gives you the chance to participate even if you can't study in London or full-time.

With hands-on projects, you’ll build a portfolio to showcase your new skills. Everything from probabilistic modelling and deep learning to unstructured data processing and anomaly detection.

Through foundations in mathematics and statistics, you will be able to boost your confidence in analytical skills.

You will have the chance to gain expertise in implementing scalable solutions using industry-standard tools, including PySpark. This gives you the tools to tackle big and complex data.

Curriculum covering the ethics and limitations of machine learning will enable you to ethically apply these techniques to your work.

When you graduate, will have the ability to:

• Turn data into actionable insights
• Contribute to strategic decision making
• Become a responsible member of this growing profession

The Applied Statistical Modelling and Health Informatics course has been created to deliver a skill set and knowledge base in "multimodal" and "big data" analysis techniques, which are a recognised scarcity within UK Life sciences. You will receive world-class training in core applied statistical methodology, machine learning and computational methodology, and you will have the opportunity to apply your skills to real-life settings facilitated by the world-leading Institute of Psychiatry, Psychology & Neuroscience. The course will apply to a broad spectrum of graduates preparing for a career in medical statistics and health informatics, or professional methodologists and clinical researchers working in the private or public health sector who are interested in state-of-the-art technologies training from world-class experts. This course is also suitable if you are a graduate in/work in the fields of computer science, maths, physics, engineering and natural science, including psychology and medicine. The course will prepare participants for the ever-growing need for a sound scientific approach to processing information and generating knowledge in modern health services. Practical skills will be taught through applications to real-life settings in a world-leading research institution in mental health

Join Warwick's Big Data and Digital Futures MSc/PGDip and learn to critically engage with big data. The Centre for Interdisciplinary Methodologies works across disciplines, drawing from the Arts, Humanities, Social Sciences and Sciences, to answer employers' demands for a new generation of researchers.

The Master of Data Science (Social Analytics) shares a common core with the other Master of Data Science programmes. Social analytics will create a new cohort of social scientists with the necessary skills to apply new computational methods to inform policy, examine social phenomena and gain insight about the interactions between people and their social environment. It will also equip social scientists to work with social media and other new sources of data. While generic data science skills are useful for social scientists, interpreting social data comes with particular challenges. This programme includes modules about specialised methods and also the theoretical foundations to understand how to use them effectively.

Shared core modules with the suite of Data Science Master courses will ensure that you get equipped with the wider quantitative and computational skills required for your career. You will be carrying out team building activities, presenting case studies and carrying out both formative and summative assessments with students from all four faculties of Durham University, ensuring that you learn how to represent not just your own discipline but to also listen and integrate views and skills from other disciplines. An additional contribution to the academic environment will be provided by the Durham Research Methods Centre which will also help with the allocation of project topics through partnerships with local authorities, neighbouring NHS Trusts or other collaborators in the health and social care sectors.

All around us, massive amounts of increasingly complex data are being generated and collected, for instance, from mobile devices, cameras, cars, houses, offices, cities, and satellites. Business, research, government, communities, and families can use that data to make informed and rational decisions that lead to better outcomes. It is impossible for any one individual or group of individuals to keep on top of all the relevant data: there is simply far too much. Data science enables us to analyse large amounts of data effectively and efficiently and as a result has become one of the fastest growing career areas.

Previously, data science was the province of experts in maths and computer science, but the advent of new techniques and increases in computing power mean that it is now viable for non-experts to learn how to access, clean, analyse, and visualize complex data. There is thus a growing opportunity for those already in possession of knowledge about a particular subject or discipline, and who are therefore able to grasp the full meaning and significance of data in their area, to be able to undertake data analysis intelligently themselves. The combination of primary domain knowledge with an expertise in extracting relevant information from data will give those with this ‘double-threat’ a significant employment advantage.

The Master of Data Science suite of programmes is a conversion course with a hard-core of data science, intended to provide Masters-level education rich in the substance of data science for students who hold a first degree that is not highly quantitative, including those in social sciences, the arts and humanities. Introductory modules are designed to bring students with non-technical degrees up to speed with the background necessary for data science. This is done on a need-to-know basis, focusing on understanding in practice rather than abstract theory. Core modules then introduce students to the full range of data science methods, building from elementary techniques to advanced modern methods such as neural networks and deep learning. Optional modules allow students to focus on an area of interest.

The programme provides training in relevant areas of contemporary data science in a supportive research-led interdisciplinary learning environment. The broad aims are:

• To develop advanced and systematic understanding of the complexity of data, including the sources of data relevant to science, alongside appropriate analysis techniques
• To enable students to critically review and apply relevant data science knowledge to practical situations
• To develop a critical awareness of current issues in data science which is informed by leading edge research and practice in the field
• To develop a conceptual understanding of existing research and scholarship to enable the identification of new or revised approaches to data science practice
• To develop creativity in the application of knowledge, together with a practical understanding of how established, advanced techniques of research and enquiry are used to develop and interpret knowledge in data science.
• To develop the ability to conduct research into data science issues that requires familiarity with a range of data, research sources and appropriate methodologies and ethical issues
• To develop advanced conceptual abilities and analytical skills in order to evaluate the rigour and validity of published research and assess its relevance to new situations
• To extend the ability to communicate effectively both orally and in writing, using a range of media.

The programme is designed around a pedagogical framework which reflects the core categories of the data science discipline.

A number of subjects can be identified and defined within each application domain. Whilst a Masters programme cannot incorporate all subjects, a selection of subjects representative of each domain ensures that the programme incorporates the necessary breadth and depth of material to ensure a skilled graduate.

The programme allows for progressive deepening in the students’ knowledge and understanding, culminating in the research project which is an in-depth investigation of a specific topic or issue.

The global dimension is reinforced through the use of international examples and case studies where appropriate.

The MSc Data Science and Artificial Intelligence is a conversion master’s designed for motivated students who have a good first degree in a subject other than Computer Science, who wish to develop the knowledge and skills to gain employment in the Data Science and Artificial Intelligence industry. 

Data Visualisation is an increasingly important part of data science. It aims to bridge the gap between the human and data. It supports human perception and cognition to make sense of data analytics outputs.

We created the PGDip, PGCert, MSc Data Science with Specialisation in Visualisation in collaboration with a number of high profile industry leaders. It aims to address the skills shortage in data analytics.

Our master's in data science brings together students and industry practitioners to develop and translate new technologies into industry practice.

You'll receive a comprehensive grounding in the theory and application of data science. You'll also gain the ability to apply these skills to real problems in a given application area.

Through project work, you'll experience the full lifecycle from design of interactive visualization to experimental evaluation of an advanced visualization approach.

Topics covered in the course include:

• cloud computing
• Bayesian statistics
• machine learning

Gain an in-depth understanding of the theory and practice of data science and its application in different organisational contexts. You'll be provided with a set of fundamental principles that support ethical extraction of information and knowledge from data. Case studies will help to show the practical application of these principles to real life problems.

The programme is centred on three key aspects of data science fundamental data-related principles, supporting infrastructures and organisational context.

You'll gain practical skills in handling structured and unstructured data, analysing and visualising data, data mining, as well as gaining hands-on experience of software tools used and their use in real-world settings. You'll gain the skills of a data manager who understands what the algorithms (e.g., for data mining or handling ‘big data’) can do and when to use them for the benefit of the organisation.

From business and finance to health and medicine, from infrastructure to societal studies, data science plays a vital role in all aspects of the modern world. The programme provides a foundation in statistical modelling and data analytical skills; the theories underpinning statistical modelling; programming; data mining and data science as process for gaining insight from data. You can study either full-time or part-time.

Upon successful completion of the modules you may wish to progress to a PGDip or an MSc in Data Science.

If you’re looking for a Master in Analytics, Data Science, or MBA in Business Analytics degree, enrolling in our MS in Analytics program makes you the change-agent you want to be as it turns group-think into a powerful platform for success.

The M.S. in Data Science prepares students for related careers that involve the application of computational and statistical techniques that are becoming more vital to industry and research. This is accomplished through coursework in topics such as database management systems, data mining and machine learning algorithms, data visualization, statistics, text analytics, and big data. Graduates of the Data Science program will obtain a variety of skills required to analyze large datasets and to develop modeling solutions to support decision making.  They will also develop a specialization in distributed Big Data, marketing analytics or healthcare analytics. This M.S. degree is a STEM designated program.

The MS ABA in the Department of Psychological Sciences and Counseling is a two-year program that meets the BACB Fifth Edition Task List for coursework and is a verified course sequence (VCS) by the Association for Behavior Analysis International (ABAI). This qualifies graduates to sit for the Board Certified Behavior Analyst (BCBA) exam to earn the BCBA credential as well as qualified to become Certified Ohio Behavior Analysts (COBA) in the state of Ohio.

BCBA Exam pass-rate data are not published for sequences with fewer than six first-time candidates in a single year or for sequences within their first four years of operation. To access current pass rates, current and potential students can view https://www.bacb.com/verified-course-sequences/

Program objectives include mastery of basic behavior-analytic skills (measurement, experimental design, behavior-change considerations, fundamental elements of behavior change, specific behavior-change procedures, and behavior-change systems), client-centered responsibilities (problem identification, measurement, assessment, intervention, and implementation, management, and supervision), and knowledge of the BACB Professional Disciplinary and Ethical Standards and Guidelines for Responsible Conduct for Behavior Analysts.

BCBAs typically supervise a team (Board certified associate behavior analysts, Registered Behavioral Technicians, & direct care staff) that provide individualized ABA services directly in homes, schools, businesses, and elsewhere. BCBAs are in high demand in Ohio, the United States and throughout the world. BCBAs have multiple employment opportunities with handsome benefit packages.

Students pursuing an MS in Data Analytics and Policy may obtain an additional credential by completing courses that lead to the Certificate in Intelligence. This combined credential prepares graduates for careers in the U.S. Intelligence Community, and in those parts of the government and private sector that use intelligence or work with the Intelligence Community, as well as other parts of the national security community.  Students can complete the program with 15 courses.

The UBC Master of Data Science (MDS) is a 10-month professional degree program. The MDS program was developed by the combined expertise of the UBC departments of Computer Science and Statistics to help meet a growing need for data scientists by producing skilled professionals who can turn data into knowledge. 

Everything we do generates data and every new technology used to capture this data brings with it even more opportunities to extract knowledge, to learn, to grow, and to create change.  

Data science is the process of extracting value from that data through reproducible and auditable processes. 

Utilizing descriptive and prescriptive techniques, students extract and analyze data from both unstructured and structured forms and then communicate the findings of those analyses in ways to enable organizations to make informed decisions based on data

Good news. The University is launching a new Data Science Master’s Degree in Fall 2021 in the College of Sciences and Liberal Arts.

The program is based on the growing trend in industry of the “democratization of data,” where organizations are pushing the competencies of Data Science and Analytics into various sub-disciplines within the corporation where decisions based on data are made.

The Data Science, M.S. is designed for students with a computer science or related background interested in pursuing data analytics, machine learning, visualization, and more. You'll learn how to employ data science concepts and methods to solve problems in business and scientific contexts and communicate these solutions effectively. You'll study computing theory, languages, and algorithms, and use mathematical and statistical models to formulate and implement data analyses and learn to apply them ethically.

Our practical curriculum incorporates case studies in advanced topics of computer architecture from classic and modern processors, including large-scale systems. You may also participate in sponsored research projects alongside faculty members from funding sources such as the Department of Defense.

With more and more data being collected every day, there is now an increase in demand for experts in Data Analytics. From the healthcare to the financial sector, solutions are needed to solve complex, big data problems. At Lawrence Tech, you can partner with faculty that train students with critical thinking skills required to effectively define, discuss, and solve complicated problems related to managing, analyzing, and disseminating vast amounts of information.

Business Analytics and Data Analytics related professions have strong demand at the local, regional, and national levels. The Bureau of Labor Statistics reports that the employment of database administrators is projected to grow 10 percent from 2019 to 2029, much faster than the average for all occupations.

The College of Business and Information Technology also offers:

• A personal faculty advisor who mentors you as you strive to meet your professional goals
• Dedicated student relationship advisors who guide you throughout your academic experience
• Insight theories and thoughtful reflection that enhance managerial learning and development
• A learning environment that encourages the cultivation of global thinking to advance a more humane and sustainable world community
• Your choice of online, on-ground or hybrid courses

CyberGIS – a new generation of geographic information science and systems (GIS) in the era of artificial intelligence and big data – represents the latest innovative development in the fast-growing field of geospatial data science. Combining advances in high-performance and data-intensive computing with developments in geospatial data analysis, management, processing, and visualization, cyberGIS has rapidly emerged as a major force in private and public organizations and in higher education for harnessing the rapid geospatial data revolution. The fully-online masters degree program in CyberGIS and Geospatial Data Science requires 32 credit hours (thesis not required). Students will work with their program advisor to individualize their program and the required capstone research project.

Upon completing the MDS degree, students will be able to:

1. Develop a graduate-level understanding of the computational and statistical foundations of Data Science.
2. Through in-depth study, obtain mastery of either one of the core methods of Data Science or one application area of Data Science.
3. Apply Data Science techniques to solve difficult, real world problems, beginning with raw and dirty data, and ending with actionable insights that are effectively communicated to a lay client.