By the end of the course, you will be able to:
Day 1
• Have a better understanding of AI
• Identify resource requirements for adopting AI
• Articulate expert systems (e.g., temporal reasoning, logic and inference)
• Distinguish machine learning models (e.g., decision trees, regression models, Bayesian)
Day 2
• Describe machine learning algorithms (e.g., supervised learning, unsupervised learning, deep learning)
• Describe enterprise usage of artificial intelligence (e.g., RPA, log analysis, image processing, NLP, fraud detection, cybersecurity,
healthcare)
• Identify consumer usage of artificial intelligence (e.g., autonomous vehicles, digital assistants, freelance mobile marketplace)
• Identify risks associated with artificial intelligence (e.g., cybersecurity, privacy, data loss)
• Articulate ethical dilemmas in artificial intelligence (e.g., privacy, bias, nefarious usage)