How Data Science is Used in Full Sail's Technology Programs
Discovering how technology-focused degree programs at Full Sail integrate the applications of data science.
Data has become one of the world’s most valuable technological assets and the science driven by data has led to a better understanding of factors surrounding food, agriculture, climate change, and the transportation sector. Other applications for data science include game development, manufacturing, marketing, image recognition, fraud detection, and much more. With this broad scope of opportunity, it’s no wonder that in the United States the demand for data scientists increased by 344 percent between 2013 and 2019.
Technology-oriented degree programs at Full Sail like the Computer Science master’s program integrate the importance of data science and teach students to explore concepts including data preparation, the statistical evaluation of data, and the representation of data, all while preparing them for careers in technology-focused roles.
On account of the rapid growth in this branch of computer science, Full Sail Emerging Technologies Education Director Haifa Maamar, Ph.D. believes Full Sail's degree programs are the perfect place to expand one’s knowledge, saying, “This [Computer Science] program can evolve with the technology trends and industry needs. I am looking forward to seeing graduates of this program lead the technology of tomorrow.”
While massive amounts of data currently exist – in fact, more data has been compiled just in the last two years than in the whole of human history – analyzing, interpreting, and applying that data takes massive amounts of brainpower. Through intelligent software solutions powered by artificial intelligence, data science seeks to utilize components like machine learning to ask the right questions in order to find the right solutions. In Full Sail’s Computer Science degree program, students will create their own solutions to turn large amounts of data into usable information.
Some of the most exciting opportunities in data science relate to healthcare, something Dr. Maamar is looking forward to exploring with students.
“I am really excited to have the students work on projects related to healthcare [such as] artificial intelligence in pneumonia detection, detection of Parkinson's Disease, sentiment analysis, speech emotion recognition, diabetic retinopathy, driver drowsiness detection, and more,” she says. “For example, with [a type of AI called] computer vision, we are working on things like ‘How can computers recognize images?’ This recognition could be used to automatically categorize pictures to assist in things like determining a broken bone on an x-ray.”
At the core of data science is the development of software solutions that address a specific need or solve a specific problem through large datasets. Having the skills and knowledge to create algorithms and software solutions integrating data science is the first step in unlocking a career in the future of emerging technology.
According to Haifa, this solution-centric focus will only continue to evolve over time, saying, “Machine learning and AI are going to change the way we do things. Right now I go, ‘Hey, Google, turn on the lights.’ That whole concept is no longer going to be ‘Hey, Google,’ somebody's going to come up with a system where you can create your own personal identity.”
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