Free Stock Footage | Royalty Free Videos for Download | Coverr. Master of Science in Data Science | Harvard John A. Paulson School of Engineering and Applied Sciences. M.S. in Applied Data Science | Program Requirements - St. John Fisher College. The 36 credit hour M.S. in applied data science program offers courses designed for the working professional. The program typically takes two calendar years to complete, although well-prepared students with minimal external obligations may be able to complete it in one calendar year.
Applicants who wish to be considered for exemptions from bridge and/or core courses will be individually reviewed as part of the application process. Unless otherwise noted, courses are three credits each. Requirements Bridge Courses – 6 credits GDAT 501 – Introduction to Statistics for Data ScienceGDAT 502 – Foundations of Working with Data Core Courses – 15 credits GDAT 511 – Data Mining & Machine LearningGDAT 512 – Predictive Modeling IGDAT 613 – Predictive Modeling IIGDAT 514 – DatabasesGDAT 515 – Communicating with Data: Visualization and Presentation Capstone Courses – 6 credits GDAT 640 – Capstone IGDAT 641 – Capstone II Electives – 9 credits Elective courses chosen from below to equal 9 credits.
Curriculum - NYU Center for Data Science. The curriculum for the MS in Data Science (MSDS) degree is 36 credits. One of the key features of the MS in Data Science curriculum is a capstone project that makes the theoretical knowledge you gain in the program operational in realistic settings. During the project, you will go through the entire process of solving a real-world problem: from collecting and processing real-world data, to designing the best method to solve the problem, and finally, to implementing a solution. The problems and datasets you’ll engage with will come from real-world settings identical to what you might encounter in industry, academia, or government.
The MSDS also offers two ways to structure the graduate program that give students the opportunity to pursue a specialization. Students in the Data Science track will follow the standard curriculum, which consists of 6 required courses and 6 electives.Students may also enroll in tracks where specializations are formalized. Data Science Track Year 2 – Spring. Data Science Computer Science | Lewis Online. Turn your Programming Skills into Effective Big Data Discovery Tools. The online Master of Science in Data Science in Computer Science concentration at Lewis University is designed to give you an edge when it comes to understanding and managing big data across a variety of computer platforms.
During the duration of the program, students will be responsible for designing and developing computing systems that enable processing, interpreting, and presenting large data sets in an organized fashion. The curriculum is designed and delivered by Lewis’s Department of Mathematics and Computer Science. The coursework will prepare you to: The skills you learn during the program will be applicable within the many fields that now focus heavily on data-driven decision making. Decoding the Mysteries of Data Science Should I Apply for a Computer Science Concentration? How Can I Learn More? MS in Applied Data Science Curriculum.
Course Descriptions. Data Science | Johns Hopkins University Engineering for Professionals. Master of Science in Data Science - NYU Center for Data Science. Educating the next generation of data scientists The Master of Science in Data Science is a highly-selective program for students with a strong background in mathematics, computer science, and applied statistics. The degree focuses on the development of new methods for data science. We live in the “Age of the Petabyte,” soon to become “The Age of the Exabyte.” Our networked world is generating a deluge of data that no human, or group of humans, can process fast enough. This data deluge has the potential to transform the way business, government, science, and healthcare are carried out. But too few possess the skills needed to use automated analytical tools and cut through the noise to create knowledge from big data. A new discipline has emerged to address the need for professionals and researchers to deal with the “data tidal wave.” 36 credits | 2 years The curriculum is 36 credits, half of which are required courses and half of which are electives.
Scholarships.