You will focus on:
- Understanding the business and managerial implications of AI
- Becoming better at using AI technologies
- Learning to successfully integrate AI into your organization.
We will start by demystifying AI with an introduction to the technology, including an overview of machine learning (ML), deep learning (DL), neuro-linguistic programming (NLP), and autonomous systems. We will review definitions and buzzwords; the hype vs. reality; and the evolution of key AI technologies.
A survey of how enterprises are using AI will help you identify opportunities in your own companies. You will gain exposure to AI applications across functional areas, including:
- The workflow of an AI project—from proof of concept to production
- The importance of data
- The skills needed for AI
- A map of AI tools, infrastructure, and frameworks
Topics also include the economics of AI technologies and business models, as well as risks and regulatory compliance. You will explore an AI transformation playbook and learn how AI can be integrated into business functions through rich case studies and an AI-first strategy. Ethical, legal, and economic implications will be covered for business strategy and society as well as AI’s impact on work and trends in the labor market.
Finally, the future of work will be discussed, its changing nature, the balance between people and machines and the training, reskilling, and retention of needed talent.
By the end of this course, you will be able to create a business roadmap for implementation of AI in your specific domain areas.
Learning OutcomesAt the conclusion of the course, you should be able to
- Distinguish AI hype from reality in industry and diverse markets
- Leverage AI in business strategy to unlock new opportunities, differentiate and innovate
- Identify opportunities to apply AI in your own business or a use-case to deliver tangible business value and outcomes
- Navigate ethical and societal implications of AI and enterprise AI governance
- Describe successful AI delivery organizations with business stakeholders
- Summarize the AI project implementation lifecycle
- Create an enterprise AI program end-to-end implementation to gain an operational view of an AI project
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