Data Scientists work towards estimating the unknown, building statistical models, and conducting casual experiments to figure out the root cause of an observed phenomenon and/or predict the future incidents. In
contrast, data analysts (or business analysts) are looking at the known, i.e. historical data, from new perspectives. They will write custom queries to answer complex business questions, incremental new data acquisition and addressing
data quality issues, such as data gaps or biases in data acquisition.
Data science programs target fields such as:
- Business Analytics
- Artificial Intelligence
- Artificial Intelligence
- Information Systems
- Applied Statistics
- Programming languages like R/Python
Data scientists work closely with databases and coding, high-performance computing and parallel processing, and machine learning. They can also use a variety of tools for data visualization. The ability to present hard data and analysis
in the form of charts and tables what is especially important in the business world. People who choose this track typically have backgrounds with excellent knowledge of statistics and coding skills. These data scientists build
complicated models and simulations in a big data environment.
Upon the completion of this course, the student will be able to:
- be competent in using appropriate algorithms.
- define, formulate and analyze a complex data structure involving human, material, machinery, money, information, time energy elements and various others and design it under realistic constraints and conditions by using making algorithms.
- design and conduct experiments, gather data, analyze and interpret results for investigating complex data structure by using algorithms.
- be proficient in statistical analysis of data and data management and apply algorithm concepts and methods to solve problems in various field.
- use information technologies effectively with the knowledge of state-of-the art hardware, and software capabilities related to algorithm designs.
- communicate effectively, using information technology and oral and written skills to enhance decision making process through better communication.
- make ethical and legal decisions by considering cultural differences.
- work efficiently in interdisciplinary and multidisciplinary teams by collaborating effectively, in addition to an individual effective working ability.
- enhance critical thinking skill by integrating relevant information, decision-making techniques, and concepts through the interdisciplinary machine learning science area.
- recognize the importance of algorithm design for entrepreneurship, innovation sustainable development and various other fields.
- have knowledge of the global and social effects of algorithm design. science and proper modelling of the data in various field.
The Master of Data Science one-year program prepares students from a variety of backgrounds for data science careers with a world-class analytics education. The technical curriculum includes courses in topics such
as analysis of algorithms, data management, statistics, machine learning and computation. Courses are organized into modules covering information systems, applied data science, deep and machine learning, industrial applications, ethics
During the course of their one-year study, students acquire real-world skills in applied mathematics, statistics, computer science and business disciplines with advanced IT and data analysis. The program is available online, making it a good fit for students who need to keep working while they earn the degree.
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The program features interdisciplinary curriculum that helps build the in demand technical, analytical and communications skills needed to manage large scale data sets along with the experience to meet their career and personal goals.
Master of Science in Data Science program is a year-round and online master’s degree program.
Students have to succeed 11 required course work and a capstone project in order to be graduated from the non-thesis program. Students, who want to have a thesis master degree diploma, have to succeed aforementioned course work and a
The non-thesis program and thesis programs have 36 and 39 credit hours, respectively. The program length is minimum 3 study semester and every semester have 14-week courses and 2-week examination, except summer semester.
The program length can differ if the student is a transfer student.