The data science certificate is intended for students interested in a variety of career fields, including statistics, business and network administration, or for those who intend to pursue graduate and professional schools. The strategic combination of computing and statistics will develop students' expertise in the design and analysis of data.
The data science certificate program combines the strengths of database skills with interdisciplinary computational statistics.
The program provides students with an understanding of the computational and statistical methods used to extract insights from complex datasets and provides hands-on experience with them. In particular, it includes courses that cover key techniques for the different stages of the data science process: data collection, data processing for small and big data, data cleaning, exploratory data analysis, data visualization, predictive modeling with machine learning techniques and statistical modeling.
At A Glance
Data Science (Certificate)
- Offered by: New College of Interdisciplinary Arts and Sciences
- Location: West
All students are required to meet general university admission requirements:
Find and apply for relevant scholarships.
ASU has many financial aid options. Almost everyone, regardless of income, can qualify for some form of financial aid. In fact, more than 70 percent of all ASU students receive some form of financial assistance every year.
Prerequisites for this certificate are:
ACO 201 Data Structures and Algorithms (3)
MAT 243 Discrete Mathematical Structures (3) or MAT 300 Mathematical Structures (3)
STP 226 Elements of Statistics (3)
A student pursuing an undergraduate certificate must be enrolled as a degree-seeking student at ASU. Undergraduate certificates are not awarded prior to the award of an undergraduate degree. A student already holding an undergraduate degree may pursue an undergraduate certificate as a nondegree-seeking graduate student.
A certificate in data science helps prepare students who have an interest in databases and statistics. Possible careers include data scientist, machine learning scientist or engineer, applications architect, data architect and data engineer.