Masters in Data Science & Analytics,Data Science & Analytics in USA

The Department of Mechanical and Industrial Engineering offers the Master of Science in Data Analytics Engineering in order to meet the current and projected demand for a workforce trained in analytics. While the core courses for this program are offered by the College of Engineering, elective courses can be chosen from diverse disciplines spread across various colleges at Northeastern. The program is designed to enable graduating students to address the growing need for professionals who are trained in advanced data analytics and can transform large streams of data into understandable and actionable information for the purpose of making decisions. The key sectors that require analytics professionals include healthcare, smart manufacturing, supply chain and logistics, national security, defense, banking, finance, marketing, and human resources.

The Master of Science in Social Data Analytics and Research degree program builds on faculty expertise in criminology, economics, geospatial information sciences, political science, public and nonprofit management, public policy, political economy and sociology to equip students with advanced training that is widely applicable in a variety of fields.

As demand for social data production, collection and analysis increases—driven by government, nonprofit and private sector organizations, as well as doctoral programs and advanced research institutions—students with advanced training and expertise in both quantitative and qualitative methodologies will have the skills and experienced needed to thrive in many different industries.

The Social Data Analytics and Research master’s program ensures that students gain a broad understanding of their discipline, apply their knowledge and analytical skills to create effective and novel solutions to practical problems and communicate and work effectively in collaborative environments.

Are you a social​ ​scientist​ ​with​ ​intellectual​ ​drive​ ​and curiosity,​ ​who​ ​wants​ ​to​ ​think​ ​more​ ​critically​ ​about​ ​the​ ​importance​ ​of​ ​data​ ​in your​ ​field? ​This​ ​program​ ​lets​ ​students​ ​apply​ ​a​ ​variety​ ​of​ ​methodologies​ ​to​ ​a discipline​ ​of​ ​their​ ​choice. If you are an interdisciplinary​ ​student​ ​who wants​ ​to​ ​add​ ​even more​ ​value​ ​to​ ​your​ social​ ​sciences training in the digital age, this program is for you.

Conduct original research across a vast field with expert faculty and industry professionals. Gain the skills needed to use analytical programming languages, data science tools, and applications. Learn how to create knowledge from data.

Saint Louis University's Master of Science program in health data science is designed to prepare students for a career in today's data-driven health care industry. Successful data scientists possess an artful ability to blend, synthesize and communicate data for use in clinical decisions by patients and providers, as well as advancing quality improvement efforts across health systems.

SLU's health data science curriculum and academic training complement other existing programs and course offerings at Saint Louis University, including health informatics (Doisy College of Health Sciences), biostatistics (College for Public Health and Social Justice), and biomedical informatics and computational biology (College of Arts and Sciences). Students will have the opportunity to take courses from each of these programs.

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.

Big data, machine learning and cloud computing have fundamentally changed how we live and work. Data science is the application of these technologies to solve difficult problems in several domains. Probability and statistics provide the underlying mathematical foundation. The core knowledge and skills of data science are applicable to a broad range of application domains.

The discipline of Computing and Data Science utilizes state-of-the-art software, software development methodologies, project management techniques, and hardware. In graduate study in this discipline, an emphasis is placed on preparing students for an environment where change is the norm. This program is available to students who have completed undergraduate Computing Science majors or minors and to those who have baccalaureate degrees in related fields with the equivalent of a Computing Science minor in formal coursework or professional experience. As part of this degree, a total of 36 hours are required for completion.

In the past decade big data and data analytics has emerged as the new-frontier for data driven decisions across the public and private sector. Through the Behavioral Data Analytics graduate certificate program you'll learn to select, compute and interpret advanced statistical techniques to address cutting edge research questions.

Add to your arsenal of knowledge while tackling real-world issues in highly interactive classes. After completing our graduate certificate program you'll be well prepared to analyze and address problems of the future.

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.

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

The purpose of the M.S. degree program in Data Science and Analytics is to provide students with the knowledge and skills to use state-of-the-art programming tools and software packages to develop statistical models. Students will learn to use data for identifying trends and patterns, solving problems, communicating results, and recommending optimal solutions. Students will acquire knowledge, skills, and abilities about the discipline-specific scientific and theoretical concepts critical to data science and analytics.

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.

The Master of Science in Data Science is an interdisciplinary graduate program that combines the teaching of domain-specific and technical skills for analyzing large data sets.  Built upon a core of foundational data science courses in Computer Science, Engineering, and Mathematics, and a selection of courses from data science application domains, the program is interdisciplinary in nature.  Students interested in data science tools will be able to focus on tool principles and tool development, and students interested in data science application domains will be able to focus on the application of data science tools with a selection of courses that develop skills in one of three application areas.  The program also provides its students the option of doing an industrial internship, to acquire professional experience.  The program allows the various academic units involved to add courses in their specific application domains, thus keeping the program updated and relevant to current practice and industrial needs.  the program is both academic and professional in nature, providing course that are true to a Master's level degree and courses that reflect the needs of the profession.  

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.

The M.S. in data science trains the next generation of data scientists who have the analytical and technical skills to explore, formulate, and solve complex data-driven problems in science, industry, business, and government.​ ​The program focuses on the theory, methodology, application, and ethics for working with and learning from data.​ ​With an emphasis on statistical thinking and foundations, the​ ​program rigorously prepares its graduates with the abilities to develop and implement new or special purpose analysis and visualization tools. It promotes​ a fundamental understanding of how to quantify uncertainty in data-driven decision-making.​ ​