Meet your instructors and fellow leaders and innovators while engaging in your AI-enabled next-gen learning platform. Preview the course content and capstone project, designing a road map for integrating AI into an organization.
Understand the foundations of data and its critical relationship to business processes:
- Learn the core components of data governance.
- Differentiate between data owners and stewards.
- Track the evolution of Big Data and artificial intelligence.
- Examine machine learning, neural networks and natural language processing.
Explore the critical link between data strategy and AI strategy:
- Define the critical components of AI strategy.
- Assess leadership qualities and roles.
- Identify gaps and improvement areas.
- Analyze the implementation of AI-powered projects.
Examine the developmental steps in designing a successful data strategy:
- Identify core components of data quality.
- Understand how data analytics support decision-making.
- Learn the value and limitations of prediction data and judgements.
- Assess the processes for restructuring an organization around technology.
Consider the costs of Big Data and AI deployment:
- Identify cost implications related to building with AI.
- Analyze the return on investment for AI initiatives.
- Determine when a data practice becomes outdated.
- Investigate strategies for Big Data analytics.
Consider the importance of AI transparency to avoid missteps and build trust:
- Understand the ethics of AI and its impact on businesses.
- Explain best practices for the responsible use of AI.
- Identify and manage the risks associated with AI.
Navigate data and AI policies, regulations and governance activities in the US and abroad:
- Differentiate among privacy, security, compliance and auditing.
- Explain federated AI and its application across various industries.
- Identify privacy and security vulnerabilities in data collection.
- Describe data protection laws in their region, the EU and Asia.