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Data Governance With AI
Price
KSh45,000.00 KSh30,000.00
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Description
Course Description
The Data Governance with AI course is a comprehensive 16-week program designed to equip learners with the strategic, ethical, and technical skills required to manage data effectively in AI-driven environments. As organizations increasingly rely on artificial intelligence, the need for robust data governance frameworks becomes critical to ensure transparency, compliance, and trust.
This course explores foundational governance principles data quality, privacy, security, lifecycle management, and regulatory alignment while demonstrating how AI technologies can be leveraged to automate oversight, enforce policies, and enhance decision-making. Learners will gain hands-on experience with governance tools, AI auditing systems, and risk mitigation strategies across diverse data ecosystems.
Through case studies, interactive modules, and practical assignments, participants will learn to design governance architectures that support scalable, ethical, and resilient AI systems. The curriculum emphasizes responsible data stewardship, cross-functional collaboration, and the strategic role of governance in enabling innovation.
This course is ideal for data professionals, compliance officers, AI practitioners, and organizational leaders seeking to build trustworthy, AI-ready data governance capabilities.
Learning Objectives
By the end of this course, learners will be able to:
- Design and implement data governance frameworks tailored for AI environments
- Apply AI tools to automate data quality checks, policy enforcement, and compliance monitoring
- Evaluate and mitigate risks associated with data privacy, bias, and ethical use in AI systems
- Align governance practices with global regulatory standards (e.g., GDPR, HIPAA, ISO)
- Collaborate across technical and non-technical teams to ensure responsible data stewardship
- Audit AI models and data pipelines for transparency, accountability, and fairness
Course Features
- 16 weeks of structured instruction with weekly modules and assessments
- Hands-on labs using AI tools for governance automation and auditing
- Case studies from real-world AI governance challenges and solutions
- Expert-led instruction from industry practitioners and governance specialists
- Capstone project: design a governance strategy for an AI system
- Certificate of completion recognized by industry partners
- Fully online access with flexible scheduling and downloadable materials
Ideal Candidates
This course is designed for:
- Data professionals seeking to expand into AI governance roles
- Compliance officers and risk managers working with AI systems
- AI developers and engineers responsible for ethical data use
- IT leaders and strategists building governance frameworks for digital transformation
- Students and graduates in data science, computer science, or business analytics
Features
- 16-week structured curriculum with weekly modules and assessments
- Practical labs using AI tools for governance automation and auditing
- Case studies from real-world AI governance challenges and solutions
- Expert-led instruction from industry practitioners and governance specialists
- Capstone project: design a governance strategy for an AI system
- Certificate of completion recognized by industry partners
- Fully online access with flexible scheduling and downloadable materials
- Optional peer forums and review features for collaborative learning
- Progress reset and retake options available for continuous improvement
Target Audiences
- Data professionals seeking to specialize in governance and compliance
- AI developers and engineers responsible for ethical data use
- Compliance officers, risk managers, and legal professionals working with data systems
- IT leaders and strategists building governance frameworks for digital transformation
- Students and graduates in data science, computer science, law, or business analytics
- Policy makers and organizational leaders aiming to align AI systems with regulatory standards
- Entrepreneurs and innovators building data-driven products with responsible oversight
Requirements
- Basic understanding of data concepts and digital systems
- Familiarity with spreadsheet tools or basic data platforms
- Interest in AI applications and responsible data management
- Ability to commit approximately 6–8 hours per week for coursework
- Proficiency in English, as all instruction and materials are delivered in English
- Optional: Prior exposure to Python or data tools is helpful but not required
- Access to a computer with internet connectivity and basic productivity software
Curriculum
FAQs
No. The course is designed for all levels. Foundational concepts are introduced before progressing to advanced topics.
You’ll work with Python-based platforms, AI auditing tools, and governance frameworks aligned with industry standards.
The course is self-paced with structured weekly modules. Instructor guidance is provided through curated content and optional forums.
Yes. A certificate of completion is awarded to learners who successfully complete all modules and the capstone project.
Yes. Learners have the option to reset their progress and retake the course at any time.
Absolutely. While technical tools are introduced, the course emphasizes strategic thinking, ethical frameworks, and cross-functional collaboration.
Learners have access to downloadable materials, optional peer forums, and periodic announcements to guide progress.
Instructor
2649 Students13 Courses
Reviews
Students List
Price
KSh45,000.00 KSh30,000.00
Get unlimited access to all learning content and premium assets Membership Pro
Featured Review
"This course exceeded my expectations. The integration of AI into traditional data governance frameworks was both timely and practical. I appreciated the balance between technical depth and strategic insight, especially the hands-on labs and real-world case studies. By the end of the program, I felt confident designing governance models that support ethical and scalable AI systems. Highly recommended for professionals serious about responsible data management."
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