Certificate in Faith Based Data Scientist AI Mining Track

Total program length

18 semester credit hours

Normal completion time

Six to nine months

General education

Not required

Professional application courses

3 credit hours

Academic unit

HBIU College of Earth Science and Industrial Technology

Total credits

18

Duration

1 years

• Analyze complex datasets using advanced machine learning algorithms to uncover patterns relevant to organizational goals.
• Evaluate the ethical implications of AI-driven mining techniques to prevent bias and ensure equitable resource distribution.
• Design predictive models that optimize organizational efficiency while adhering to principles of biblical stewardship.
• Demonstrate proficiency in integrating AI tools with traditional data management systems to improve operational transparency.
• Communicate technical insights effectively to non-technical stakeholders in ways that honor institutional values and community missions.
• Develop a comprehensive data-governance strategy that reflects commitment to servant leadership and social responsibility.
• Course Outline
• Semester 1 — Year 1
• Code
• Title
• Credits
• Prerequisites
• DSCI 201
• Introduction to Ethical Data Mining
• 3
• College Algebra
• BUS 310
• Stewardship and Organizational Management
• 2
• None
• MAT 350
• Applied Statistical Methods for AI
• 2
• DSCI 201
• THE 305
• Foundations of Ethical Decision Making
• 2
• None
• DSCI 201 — Introduction to Ethical Data Mining: This course explores the fundamental principles of data mining, covering data cleaning, exploration, and descriptive analysis. It emphasizes the ethical responsibilities of data managers in maintaining privacy and organizational integrity. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• BUS 310 — Stewardship and Organizational Management: This course investigates management theories centered on servant leadership and the responsible use of organizational resources. Students examine how administrative decisions affect the sustainability of community institutions. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• MAT 350 — Applied Statistical Methods for AI: Students engage with advanced statistical techniques necessary for high-level data analysis and predictive modeling. The curriculum focuses on valid inference and the mitigation of statistical bias in modeling processes. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• THE 305 — Foundations of Ethical Decision Making: This course examines ethical frameworks as they relate to modern technology and professional leadership. It promotes critical thinking regarding the influence of personal convictions on organizational decision-making. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• Semester 2 — Year 1
• Code
• Title
• Credits
• Prerequisites
• DSCI 402
• Machine Learning and Artificial Intelligence Integration
• 2
• DSCI 201
• DSCI 420
• Data Governance and Security Ethics
• 2
• DSCI 201
• COM 410
• Data Communication and Stakeholder Engagement
• 2
• None
• CAP 490
• Data Science Capstone Project
• 3
• All prior program courses
• DSCI 402 — Machine Learning and Artificial Intelligence Integration: This course provides practical experience in implementing AI-integrated mining tools to solve complex, real-world analytical problems. Emphasis is placed on the technical deployment of algorithms within resource-conscious environments. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• DSCI 420 — Data Governance and Security Ethics: This course reviews the legal and ethical landscape of data governance, focusing on protection of sensitive information and stakeholder transparency. It prepares students to implement frameworks that respect organizational and donor privacy requirements. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• COM 410 — Data Communication and Stakeholder Engagement: Students learn to synthesize complex technical findings into clear, impactful narratives for non-technical leadership. The curriculum prioritizes transparency, clarity, and the importance of communicating mission-aligned results. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.
• CAP 490 — Data Science Capstone Project: The capstone provides the culmination of the program where students execute an AI-driven project for a specific community or nonprofit partner. Students must document their technical implementation alongside a formal reflection on ethical integration and organizational stewardship. This course prepares students in supporting faith-based, nonprofit, community organizations' missions.

Applicants must hold a conferred associate degree or higher from an accredited institution. A foundational background in college-level mathematics, specifically statistics or linear algebra, is required. Candidates are expected to submit an essay detailing their professional objectives, an explanation of how they seek to integrate ethical reasoning into technical work, and a record of academic performance that demonstrates readiness for rigorous quantitative study. Culminating Project The Capstone Project serves as the final synthesis of the student's learning, requiring the development of an original data-mining solution to a real-world problem faced by a nonprofit or community organization. This project mandates that students identify an authentic organizational challenge, curate relevant data, and implement an AI-integrated mining strategy that improves decision-making processes. Beyond technical implementation, the project requires a written analysis of the ethical considerations and stewardship practices embedded in the methodology, demonstrating how the student has applied faith-informed integrity to technical practice. This six-credit culminating experience necessitates a formal presentation and a final report that evaluates the project's impact on institutional sustainability and servant leadership. By completing this requirement, students demonstrate both the technical competence required for data mining and the character development necessary for ethically leading organizational transformation. The project serves as a capstone of the student's integration of professional rigor with faith-based values.

• Graduation from the certificate program requires the successful completion of all 18 credit hours with a minimum cumulative GPA of 2.0. Students must earn a passing grade in the Capstone Project, demonstrating an ability to synthesize technical analytical skills with the ethical mandates of institutional stewardship and servant leadership. In addition to academic requirements, candidates are expected to participate in scheduled spiritual formation and character development reflections, which reinforce the university's commitment to excellence, integrity, and faith-informed service. Graduates are recognized for their academic achievement as well as their commitment to applying their professional expertise in service to their communities and society at large, ensuring they are prepared for the moral demands of their field.
• Career Opportunities
• Data Analyst for Faith-Based Nonprofits
• Social Impact Data Researcher
• Nonprofit Operations Strategist
• Ethical AI Implementation Specialist
• Community Development Data Consultant
• Stewardship and Resource Optimization Coordinator
• Important Notices
• The program educates ethical professionals who demonstrate technical excellence, servant leadership, professional integrity, and a commitment to apply sound principles to advance faith-based organizations, strengthen communities, and contribute responsibly.
• HBIU is a lawfully operating nonpublic faith-based postsecondary institution that maintains its status under section 1005.06(1)(f), Florida Statutes. The University annually affirms its compliance with the requirements applicable to faith-based institutions in Florida through Commission for Independent Education.
• HBIU accreditation from QAHE (for quality assurance in pre-tertiary and higher education mechanisms). QAHE offers globally recognized accreditation and quality assurance for higher education, training providers, and professional institutions worldwide. Students should consider the nature and scope of this recognition in relation to their individual certification and professional goals.
• Transfer credit is evaluated individually based on course content, credit hours, grades, institutional documentation, program requirements, and applicable university policies. Although HBIU provides academically structured programs, no institution can guarantee that another college, university, employer, licensing board, or credential-evaluation service will accept its credits or credentials. Students are encouraged to obtain advance written confirmation from the intended receiving organization.
• The program develops academic knowledge and applied competencies for service in faith-based organizations, nonprofit institutions, community programs, and related professional environments. Some occupations associated with the subject area may be regulated by governmental or professional authorities. A degree from HBIU demonstrates completion of the University's academic requirements but does not, by itself, confer professional licensure or legal authority to perform regulated services.
• Where a program is related to an external certification, eligibility is determined exclusively by the applicable certifying organization. Certification bodies may establish additional requirements involving education, examinations, experience, background screening, continuing education, or membership. HBIU does not guarantee certification eligibility or examination approval unless a formal written agreement expressly provides otherwise.
• Career and occupational information is provided to help students make informed educational decisions. Employment outcomes depend on factors such as the graduate's experience, geographic location, professional qualifications, employer requirements, economic conditions, interviewing ability, and any applicable licensure or certification requirements. Completion of a program does not constitute a promise of employment, promotion, job placement, or a particular occupational title.
• This program is delivered through online instruction. Students must have access to the technology, equipment, internet service, software, and learning resources identified in the University's technology requirements.
• Internship or field-experience participation is subject to academic eligibility, site availability, supervisor approval, and the requirements of the participating organization. The University assists students with the placement process but cannot guarantee placement with a particular organization, supervisor, location, or schedule.
• Students are responsible for reviewing the catalog, understanding program requirements, providing accurate information, meeting academic and financial obligations, and verifying whether the program supports their intended educational or professional goals.
• Completion of a University program does not authorize a graduate to use a professional title that is protected or restricted by law. Graduates must use titles that accurately reflect their education, credentials, employment role, and current licensure or certification status.
• Credential abbreviation | Certificate in Faith Based Data Scientist (Mining) – AI Integrated - Stewardship, Ethical Mining Track
• Total program length | 18 semester credit hours
• Normal completion time | Six to nine months
• General education | Not required
• Foundational faith based data science courses | 12 credit hours
• Professional application courses | 3 credit hours
• Final applied project | 3 credit hours
• Code | Title | Credits | Prerequisites
• DSCI 201 | Introduction to Ethical Data Mining | 3 | College Algebra
• BUS 310 | Stewardship and Organizational Management | 2 | None
• MAT 350 | Applied Statistical Methods for AI | 2 | DSCI 201
• THE 305 | Foundations of Ethical Decision Making | 2 | None
• Code | Title | Credits | Prerequisites
• DSCI 402 | Machine Learning and Artificial Intelligence Integration | 2 | DSCI 201
• DSCI 420 | Data Governance and Security Ethics | 2 | DSCI 201
• COM 410 | Data Communication and Stakeholder Engagement | 2 | None
• CAP 490 | Data Science Capstone Project | 3 | All prior program courses