Learn to analyze blocks of data, and effectively communicate results. The field of data science is becoming more and more relevant every day. The information weve collected helps point the way to a brighter future, and correctly analyzing and understanding this abundance of information is a highly specialized, sought-after skill. National University's Bachelor of Science in Data Science (BSDS) degree program balances a strong academic foundation, realistic design, and implementation projects to prepare you for an exciting career in this fast-paced industry.
Upon graduation from the program you will emerge well-rounded in the data science industry, with the skills to analyze batches of data, and to communicate the results to those outside the field. The data science program culminates in a three-month capstone where publicly available data are used in a project to demonstrate mastery of the data science life cycle in the chosen concentration area.
National University supports your journey with our whole human education approach. Our relevant, practitioner faculty will be with you every step of the way, showing you how to present data that tells a story, complete with demonstrations and visualizations, using the assertion evidence method, and more. You are able to customize their program by selecting from three specializations: AI and machine learning, cybersecurity analytics, and bioinformatics. With the Assertion Evidence Method, you are taught to solve real-world data science issues in their capstone course, where you will partner with existing small businesses to network and develop a portfolio of real-world problem solving.
The concentration in bioinformatics will provide students with the biological literacy necessary to evaluate techniques essential to bioinformatics, including practical knowledge of databases, relevant libraries, verifying and evaluating analyses, developing a research project, and communicating results to biologists.
1. Describe key biological concepts such as cellular, molecular, organismal, and evolutionary processes, and how they frame bioinformatics questions.
2. Implement and evaluate programs and libraries in relation to the contexts of molecular and cellular biology and genomics research.
3. Analyze and evaluate bioinformatics data to discover patterns, critically evaluate conclusions, and generate predictions for subsequent experiments.
4. Effectively communicate scientific information in written and oral form to audiences within and outside the discipline of bioinformatics.
