Applied Data Analytics in Technology, Post-Baccalaureate Certificate

About the Certificate

The Post-Baccalaureate Certificate in Applied Data Analytics in Technology prepares professionals to leverage data for informed decision-making in technology-driven business and research environments. This 9-credit graduate certificate develops foundational data literacy, analytical reasoning, predictive modeling, and data visualization competencies necessary to transform raw data into actionable insights.

Students begin by developing conceptual and practical fluency in data literacy, including hypothesis generation, data capture and storage strategies, analytical thinking frameworks, and interpretation of results. Building on this foundation, students apply quantitative methods and predictive analytics techniques to evaluate trends, construct models, and support strategic business decisions while addressing ethical considerations in data collection and use. The certificate culminates in hands-on experience with modern visualization tools and design principles, enabling students to communicate complex quantitative and qualitative findings clearly and effectively.

Through applied coursework, students learn to collect, clean, organize, integrate, analyze, model, and visually present large datasets. Emphasis is placed on critical thinking, ethical reasoning, and professional communication of analytical outcomes.

This certificate is designed for professionals and graduate students seeking practical data analytics skills applicable across technology, engineering, manufacturing, supply chain, healthcare, and digital business contexts. The curriculum provides immediately applicable competencies for career advancement or continued graduate study in analytics-related fields.

Program Website

Certificate Requirements

9 Credits Required

Program Learning Outcomes

Students will:

• Apply foundational data analytics concepts, models, and methods to evaluate problems and opportunities in technical and technology-driven environments.
• Prepare, analyze, and interpret datasets to generate evidence-based insights that support improved decision-making.
• Develop and evaluate predictive and quantitative analyses to assess trends and inform strategic or operational recommendations.
• Design and produce effective data visualizations that clearly communicate analytical findings to technical and non-technical audiences.
• Demonstrate ethical and responsible use of data in collection, analysis, and presentation within professional contexts.

Graduate Programs Disclaimer

• The student is ultimately responsible for knowing and completing all degree requirements. Students should consult with their advisor/department for more information.
• Not all graduate programs may be actively recruiting students and course modality availability may vary. 
• Please refer to the Explore Graduate Programs website for a list of currently available graduate programs.
• Transfer credit policy: Credits earned for graduate study at other universities (both domestic and international) may be applied toward an advanced degree. Only credit hours associated with graduate courses for which grades of B- or better were obtained will be eligible for transfer. Any additional conditions under which credit transfers may be made are determined by the various departments.
• Comparative information about Purdue University and other U.S. educational institutions is also available through the College Navigator tool, provided by the National Center for Education Statistics, and through the U.S. Department of Education College Scorecard.