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Learn key skills such as data analysis, data mining, data visualization, programming, machine learning, and more.
Learn from instructors who have years of experience and are up to date on in-demand topics such as data ethics, machine learning, and artificial intelligence.
Showcase knowledge of key data science skills such as statistical modeling, programming, and data visualization.
The curriculum combines traditional data analysis with computer programming to ensure that graduates are equipped with the skills they will need to thrive in an evolving industry. Topics include AI/machine learning, big data analytics, high-performance computing, and cloud computing. The skills students acquire during the program can help open doors to diverse and lucrative employment opportunities in finance, technology, and sciences.
The curriculum consists of 10 courses, and a capstone designed to strengthen your data science portfolio.
Review foundational skills in statistics, programming, computing, and linear algebra. These prerequisites are highly recommended.
Distinguish learning problems, select machine learning and deep learning models, and implement a training algorithm.
Apply a framework to evaluate ethical issues in artificial intelligence and data science.
Hawai‘i Pacific University offers a variety of academic and career support resources for students as they jumpstart or pivot their careers. In addition, Hawai‘i Pacific University’s passionate graduates and their alumni network can help current students and graduates alike connect and engage with professionals across nearly every industry. Hawai‘i Pacific University supports members of the military and their families throughout their academic and professional journey through a variety of financial and career resources.
The faculty at Hawai‘i Pacific University are also committed to supporting students from undergraduate programs who are eager to apply data science skills in their field. For example, students with a background in marine science can use new insights from climate data, bioinformatics, epidemiology, and more to expand their impact in the field.
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