MSDS Degree
Become a leader in this emerging field by unifying statistics, data analysis and machine learning. This program provides a foundation for new computational methods that capture, manage and analyze massive datasets to solve real-world problems.
Learn from faculty who are pioneering these new methods. Take advantage of internships in one of America’s leading tech hubs.
Free Master of Data science Practice Test Online
Master of Science in Data Science
Every second, more than 1.5 megabytes of data is created for every person on the planet. This massive amount of data requires powerful and innovative technology to make sense of, store, process, and analyze it. Fordham’s MS-DS program equips you with the theoretical and technical skills to extract meaningful insights from big data, as well as the critical thinking to apply those insights in real world settings.
The MS-DS curriculum covers a wide range of topics, including predictive and prescriptive analytics, natural language processing, machine learning, business processes, text analytics, and more. In addition, students will complete a capstone project to bring their knowledge to the workplace and prepare for a future in industry.
The MS-DS curriculum is flexible, allowing you to customize your course of study through the choice of an industry concentration or track. The track you choose will give you the opportunity to connect with faculty who will advise and help you plan your curriculum. You can find more information about tracks and courses in the MS Student Handbook.
Master of Data Science Online
The Master of Data Science (MS-DS) is an intensive program that prepares students to work with the most complex and voluminous data sets in the workplace. This online degree bridges statistical methodology with computational science, and teaches the skills needed to handle massive data sets, analyze and interpret data, develop predictive models, and make decisions based on those models. Students will learn how to apply statistical methods, machine learning, and optimization to solve real-world problems.
Designed for working professionals, this program can be completed in as little as nine months. Begin your journey by enrolling in a pathway course to gain the foundation you need to succeed in this rigorous program.
Earning this degree can boost your resume and help you become a leader in the field of data analytics. Through a combination of interactive coursework, collaborative group projects and virtual face-to-face classes, you will acquire the technical, analytical, and communication skills required to make meaningful data-driven decisions in various industries. The curriculum will provide you with essential data analytics topics like natural language processing, machine learning, text analytics and deep learning.
Master of Science in Data Analytics
A master’s degree in data science can help you advance your career by increasing your analytical skills, leadership training and access to a variety of internship and networking opportunities. Depending on your area of expertise, you can also choose to focus your coursework in a specific track and select one of the many elective courses available.
The program draws on the strengths of both the College of Engineering’s Department of Computer Science and the Lee Business School’s department of Management, Entrepreneurship & Technology to provide comprehensive and practical education in machine learning, large-scale data management, computational statistics and data analytics. The curriculum includes a final hands-on, collaborative capstone project and graduate co-op is available for on-campus, full-time students.
Our expert faculty are both traditional academics and practitioners with extensive industry experience. The program is taught in a cohort format and you will progress through the core curriculum with your fellow classmates. Throughout the program, you will be given the opportunity to gain real world experience by tackling data science and analytics challenges for nine months in Orange County’s high tech, bio-medical and aerospace industry clusters.
Master of Data Science Salary
Data science is a complex field that requires high-level programming skills and math and statistics expertise. This is why it’s not surprising that data scientists earn an average salary of more than $100,000.
While there are plenty of opportunities to get a job with a master of data science degree, it’s important to consider your professional and academic background before pursuing this advanced degree. The salary you can expect to receive depends on many factors, including your area of specialization, industry, and the type of company you work for.
A data scientist can help businesses understand and analyze large volumes of information, leading to unique discoveries and increased revenue. They can also identify hidden patterns in big data, which could be valuable for a wide range of industries. Whether you’re interested in data analytics, business intelligence, or machine learning, there is a degree program that can meet your needs.
UC Berkeley Master of Information and Data Science
The online UC Berkeley Master of Information and Data Science program prepares students to become leaders in the field. Its curriculum is based on the three critical pillars of quantitative science: meticulous collection, rigorous analysis and synthesis of that data, and effective communication of its results. It requires 27 course units and can be completed in 20 months. Those who wish to work at a slower pace can do so by following an accelerated path or taking up to 32 months to complete the degree.
The program features a dynamic learning experience, incorporating project-based learning and peer collaboration, along with expert faculty guidance. It also offers in-person immersion experiences, which give learners the opportunity to network with peers and industry leaders. Upon graduation, graduates are prepared to apply their skills in an array of industries.
The UC Berkeley Master of Information and Data Science is offered by the UC Berkeley School of Information, or I School, in Berkeley, CA. It is an accredited graduate school that provides its students with a world-class education while offering flexibility for those working professionals in the field.
Master of Applied Data Science
The Master of Applied Data Science is the perfect way to acquire the skills and experience necessary for a career in this exciting field. The program’s rigorous coursework and demanding, hands-on projects give you the tools to develop predictive and prescriptive models in a variety of settings. You will also gain real-world industry experience through a Capstone project and learn the critical importance of ethical and responsible data use in both public and private sectors.
Our unique MSDS curriculum combines approaches and techniques from statistics and computer science, giving you the breadth of knowledge needed to solve any data challenge. You’ll explore topics in statistics such as probability and regression analysis, while also studying computer science concepts like data structures and optimization.
The degree will prepare you for a wide range of technical and managerial positions in industry, including data scientist, analytics manager, information systems engineer, business intelligence analyst, knowledge engineering and informatics engineer, and more. You’ll also be able to select an industry concentration, which helps you connect with faculty who can advise and guide your academic and professional path.
NYU Master of Data Science
New York University’s Master of Science in Data Science program covers a wide range of topics, including data management and machine learning. This comprehensive curriculum allows students to gain a deep understanding of the field and apply their skills to solve real-world problems. The program also addresses the ethical and social implications of data science.
The program’s curriculum focuses on developing the necessary knowledge, skills and techniques to extract and analyze information from large data sets. This information can then be used to make better decisions and improve business processes. It draws from a broad range of disciplines, including engineering, statistics, information science, and computer science.
The program offers a number of tracks to help students tailor the degree to their career interests. Choosing the right track is a crucial step in completing a successful master’s program. You should always review the curriculum of each track before making a decision. It is also important to look at the track’s faculty and alumni. If possible, you should also talk to alumni who are currently working in the field of data science.
Master of Data Science Ranking
Students with a master’s degree in data science have more career opportunities than those without one. They can work as information research scientists, solutions architects, and systems engineers. These professionals can apply new technological approaches to large datasets and solve modern business problems. They also enjoy higher salaries than most other professions.
The master of data science degree focuses on the principles and practice of statistics, math, computer science, and information science. This program trains students to work with and manipulate massive amounts of data to make accurate predictions. It also helps them understand the social implications of their data centered decisions.
The online master’s in data science from SMU prepares graduates to be sought-after data scientists in a variety of industries. The program offers cross-disciplinary faculty and small student-to-professor ratios. The curriculum consists of 12 courses, including a capstone project. Students learn how to collect, clean, and process data to derive insights and present them in a clear and understandable manner. It also includes training in the latest statistical models and tools, and how to implement them in different applications.
Master of Data Science Questions and Answers
Data science bachelor’s degrees are available from many universities, although they typically need four years to complete.
Gaining a master’s degree in data science opens up a wide range of career opportunities, including increased pay, a quicker route to leadership roles, and greater understanding of the field’s theoretical and practical applications.
Data science master’s degree holders operate in a variety of industries. These include fields like designing computer systems, providing healthcare, and working in government. Data scientist, data manager, biostatistics scientist, machine learning engineer, and clinical data scientist are some examples of job titles.
• Establish a Solid Foundation in Math and Statistics
• Learn to Program Using Python and R
• Learning About Databases
• Study data analysis techniques
• Discover, Practice, and Repeat
• Develop Your Data Science Skills
• Work on projects involving data science
• Learn how to tell data stories
• Never Stop Learning
A bachelor’s degree from an approved institution is normally required to be eligible for a master’s in data science program. It’s not always necessary, but it can be beneficial to have a bachelor’s degree in data science or a closely related subject like computer science, cybersecurity, accounting, mathematics, or statistics.
The quick response is no. The different programming languages and tools you’ll come across along the way may cause you to get confused or overwhelmed, but a master’s in data science could help you grow in your data science profession more effectively.
Data science is a challenging subject.
Job opportunities:
• Machine learning engineer
• Big data engineer
• Data modeler
• Data scientist
• Software engineer
• Data engineer
• Artificial intelligence engineer
• Data analyst
A data science online master’s degree is not worthwhile because abilities and experience are more important than degrees.
• Business, finance, or economics
• Computer science
• Statistics
• Biostatistics
• Physics
• Computer information systems
• Data/analytics
• Information technology
• Applied mathematics
• Engineering (mechanical, electrical, or industrial)
• Harvard University
• Cornell University
• Princeton University
• Carnegie Mellon University
• Purdue University
• Georgia Institute of Technology
• University of Michigan
• Massachusetts Institute of Technology
• University of Illinois Urbana-Champaign
• University of California, Berkeley