AI and Data Product Management
Launch your career in AI and Data Product Management by developing in-demand skills—become job-ready in just 32 hours.
Mode of Training
Online – Virtual (Live, Instructor Led, Real-Time Learning with Q&A and Discussions)
Certification
After the completion of the course and the exam, you will be awarded the course completion certificate.
Duration
32 hours (16 hours of Instructor-led training plus 16 hours of student practice)
This course is ideal for:
- Product Managers:
Perfect for current or aspiring product managers who want to learn how to integrate AI and data into product strategy, user-centric design, and lifecycle management. - Project Managers / Program Managers:
Helps project leaders understand how to oversee AI-related initiatives, manage timelines, and collaborate with technical teams effectively—even without deep technical expertise. - Agile or Scrum Managers / Scrum Masters:
Useful for Agile professionals looking to support cross-functional AI and data teams, manage sprints involving ML features, and align product goals with agile execution. - Business Analysts & Data Analysts:
Ideal for those looking to move into product roles or gain a broader strategic view of how data insights shape product decisions. - Technology Leaders / Innovation Managers:
For those leading digital transformation initiatives, this course provides the frameworks to make informed decisions about AI integration and product development.
Highlights
Upgrade your career with top notch training
- Enhance Your Skills: Gain invaluable training that prepares you for success.
- Instructor-Led Training: Engage in interactive sessions that include hands-on exercises for practical experience.
- Flexible Online Format: Participate in the course from the comfort of your home or office.
- Accessible Learning Platform: Access course content on any device through our Learning Management System (LMS).
- Flexible Schedule: Enjoy a schedule that accommodates your personal and professional commitments.
- Job Assistance: Benefit from comprehensive support, including resume preparation and mock interviews to help you secure a position in the industry.
Outcomes
By the end of this course, participants will be equipped with:
- Understand of AI Essentials: Grasp the fundamental concepts of artificial intelligence, including machine learning, data analytics, natural language processing, and computer vision.
- AI Applications in Business: Learners will explore various applications of AI within different sectors such as finance, healthcare, retail, and manufacturing, understanding how AI can drive efficiency and enhance decision-making.
- Strategic Integration of AI: Learn how to assess and integrate AI technologies into existing business frameworks, enabling them to create data-driven strategies that align with organizational goals.
- Impacts on Business Models: Analyze how AI is transforming business models and practices, including automation of processes, customization of services, and innovative product development.
- Change Management and Adoption: Develop strategies for effective change management, focusing on culture, resistance, and training needed for successful AI adoption within an organization.
- Developing AI-Driven Strategies: Learn how to formulate and present AI-driven business strategies that leverage data analytics for enhanced competitive advantage.
- Case Studies and Real-World Applications: Examine case studies of successful AI implementation in various companies, providing practical examples of how AI impacts business performance.
Course Content
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About
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Key Learnings
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Pre-requisites
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Job roles and career paths
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Curriculum
The AI and Data Product Management course is designed for aspiring product managers, business professionals, and technology leaders who want to harness the power of artificial intelligence and data to build successful digital products. This course bridges the gap between AI technology and practical product management, empowering participants to design, develop, and deliver AI-powered solutions that solve real business problems.
Through a blend of theoretical foundations and hands-on applications, learners will explore how to manage the lifecycle of AI products, integrate data-driven insights into product strategy, and collaborate effectively with cross-functional teams. The course also covers essential topics such as machine learning, user-centric design, agile delivery, data ethics, and responsible AI implementation.
By the end of the course, participants will have the skills and knowledge to lead AI and data product initiatives, drive innovation, and create measurable business impact across industries like finance, healthcare, retail, and technology.
- Gain a comprehensive understanding of AI and data product management, including core concepts in artificial intelligence, data pipelines, product lifecycle, and machine learning applications.
- Explore real-world applications of AI across industries such as healthcare, finance, retail, and technology, and understand how AI-powered products deliver business value.
- Learn to design and manage AI-driven products, aligning user needs, data insights, and business objectives through agile product development methodologies.
- Understand the role of data in shaping product strategy, from customer behavior analytics to predictive modeling and personalization.
- Develop skills in cross-functional collaboration, enabling you to work effectively with data scientists, engineers, designers, and stakeholders.
- Master change management principles to support AI adoption across teams, including strategies for overcoming resistance and fostering an innovation mindset.
- Evaluate the ethical and regulatory considerations of AI product development, including bias mitigation, explainability, and responsible data use.
- Analyze case studies of successful AI products, extracting actionable insights and best practices for your own product initiatives.
- Learn to craft and present AI-driven business strategies that support competitive advantage, innovation, and long-term scalability in your organization.
- Stay ahead of emerging trends in AI technologies and data product practices, positioning yourself as a forward-thinking product leader.
- Basic Computer Skills: Participants should be comfortable using computers and common software tools such as spreadsheets, presentation software, and web applications.
- Understanding of Business Fundamentals: A foundational knowledge of business operations, product development, or strategic planning will help contextualize AI applications in real-world scenarios.
- Familiarity with Data Concepts: A basic understanding of data analytics, key metrics, and data-driven decision-making will enhance comprehension of AI-driven product strategies.
- No Programming Required: While technical awareness is helpful, this course does not require coding or deep technical expertise—making it ideal for business-oriented professionals and aspiring product managers.
This training will equip you for the following job roles and career paths:
- AI Product Manager
- Data Product Manager
- Technical Product Manager – AI/Data
- AI Strategy Consultant
Business Intelligence Analyst - AI Project Manager
Data Analyst / Data Strategist - Product Owner – AI Initiatives
- Digital Transformation Lead
- Innovation Manager – AI & Data Products
Session 1: Introduction to AI & Data Product Management
1.1 Understanding AI & Data Products
- What is AI & Data Product Management?
- Differences between Traditional vs. AI-driven Product Management
- Types of AI-driven products (Predictive Analytics, NLP, Computer Vision, Recommendation Systems)
1.2 The Role of an AI & Data Product Manager
- Key responsibilities and skills required
- Collaboration with Data Scientists, Engineers, and Business Stakeholders
- Challenges in managing AI-powered products
Session 2: Data Strategy & AI Development Lifecycle
2.1 Data Strategy & Infrastructure
- Understanding Data as a Product
- Data Collection, Processing, and Governance
- Data Quality, Bias, and Ethical Considerations
2.2 AI Model Lifecycle & Deployment
- AI Model Development: Training, Testing, and Validation
- Model Deployment & Monitoring (MLOps)
- Handling Model Drift and Continuous Improvement
Exercise: Case Study Discussion – AI in Action (Real-world AI-driven product examples)
Session 3: Building & Managing AI-Driven Products
3.1 Problem-Solving with AI
- Identifying AI use cases
- Matching AI capabilities with business needs
- How to assess feasibility and risks
3.2 AI Product Design & Development Process
- Defining AI Product Requirements
- AI Development Lifecycle
- Testing AI Use Cases
Exercise: AI Product Ideation Workshop – Define an AI-powered product and outline its key features
Session 4: AI Governance, Compliance, and Ethical Considerations
4.1 AI Ethics & Responsible AI
- AI Bias & Fairness
- Privacy & Security Concerns
4.2 Compliance & Legal Aspects
- GDPR, CCPA, and AI Regulations
- Model Interpretability & Risk Mitigation
- Industry-Specific AI Compliance
Exercise: Ethical Dilemmas in AI – Participants discuss real-world AI ethics scenarios
Session 5: AI Product Metrics & Roadmap Planning
5.1 Measuring AI Product Success
- Key AI Performance Metrics (Precision, Recall, F1 Score, ROI, Confusion Matrix)
- User Adoption & Business Impact of AI Products
5.2 Creating an AI Product Roadmap
- Setting Milestones for AI Model Development
- Managing AI Experiments & Iterations
- Scaling AI Solutions & Continuous Improvement
Demand for AI and Data Product Management
The demand for AI and Data Product Management is rapidly growing as businesses seek professionals who can bridge the gap between technical AI capabilities and strategic product development. With AI transforming industries like healthcare, finance, and retail, companies need talent that can lead data-driven initiatives and manage AI-powered products. This course meets market demand by equipping learners with the skills to design, build, and scale AI solutions that deliver real business value. As organizations continue their digital transformation, the need for AI-savvy product managers and strategists is higher than ever.
FAQs
This course is ideal for product managers, project managers, Agile or Scrum professionals, business analysts, and technology leaders who want to understand how to manage and scale AI-powered products. It’s also suitable for professionals transitioning into AI or data-driven roles who need a practical, business-focused understanding of artificial intelligence and data strategy.
No prior experience in AI or data science is required—just a basic understanding of business and data concepts.
The course is designed to be completed in approximately 32 hours, which includes 16 hours of instructor-led training and 16 hours of student practice.
No, prior experience in AI or data science is not required. This course is designed for individuals interested in understanding how AI can impact business strategy, regardless of their background.
Participants will learn how to manage AI-powered products, align data and AI capabilities with business goals, define product strategies, and lead cross-functional teams. The course covers AI fundamentals, data strategy, product lifecycle, and real-world applications.
Yes, participants will receive a certificate of completion for the course.
The course includes real-world case studies, AI product templates, roadmap planning tools, and access to our online Learning Management System (LMS) with session recordings, readings, and assignments.
Yes, the course is offered in an online format, allowing you to participate from anywhere with a stable internet connection.
Participants will have access to instructor support throughout the course, along with resources to facilitate learning, including assignments, and exercises.
To enroll in this course, please email us at enroll@ohiocomputeracademy.com
Yes, discounts may be available for group registrations. Please contact us at enroll@ohiocomputeracademy.com for more details on group pricing options.
This course prepares you for roles such as AI Product Manager, Data Product Manager, Technical Product Manager, AI Project Manager, and AI Strategy Consultant—ideal for professionals leading AI-driven product development and digital transformation initiatives.
