First week: AI technology, what is AI and what is machine learning? What’s supervised learning, that is learning inputs, outputs, or A to B mappings. As well as what is data science, and how data feeds into all of these technologies? What AI can and cannot do?
Second week: What it feels like to build an AI project? What is the workflow of machine learning projects, of collecting data, building a system and deploying it, as well as the workflow of data science projects? How to carry out technical diligence to make sure a project is feasible, together with business diligence to make sure that the project is valuable before you commit to taking on a specific AI project?
Third week: How such AI projects could fit in the context of our company? Examples of complex AI products, such as a smart speaker, a self-driving car. What are the roles and responsibilities of large AI teams? The AI transmission playbook, what are the five-steps for helping a company become a great AI company?
Last week: AI and Society. What are the limitations of AI beyond just technical ones? How AI is affecting developing economies and jobs worldwide?”
“Ng’snew courseis available through Coursera, appropriately, and launches on November 14. And while it’s open to anyone, it’s principally geared toward business professionals who want to “better understand AI” and how it can impact their business — that is to say, executives interested in learning to select AI projects that’ll yield a return.
“Artificial intelligence will transform every industry, just as electricity did 100 years ago,” Ng wrote in a forthcoming blog post, pointing to a study by theMcKinsey Global Institute. AI will result in a 1.2 percent increase in gross domestic product growth (GDP) over the next 10 years, the researcher firm predicted this year, and help capture an additional 20-25 percent in net economic benefits — $13 trillion globally — in the next 12.”