Patterned after the structure of the human mind, do ANNs allow machines to think like humans? What exactly are ANNs, how do they work, how do they differ from other machine learning algorithms, and what are their use scenarios in data science?

Artificial Intelligence has potentially changed everything: both blurring the lines between human and mechanical processes and shifting the managerial focus from studying best practices to influencing consumer behavior. As a manager in 2019, what will you really need to know about Artificial Intelligence? 

What sets these market leaders apart from the competition isn’t the volume of data or the sophistication of their analytics, but their capability to use data to enhance consumer trust. When companies in Europe and abroad evaluate GDPR in light of their digital strategies; they are missing a critical point – data will never be worth more than the confidence their stakeholders have in their data practices.

What is the probability that you are truly exceptional? Why would Bayes’ theorem be useful here, how is it applied to machine learning, what are its assumptions, and what precautions we should take when relying on this methodology?

Nothing quite racks havoc on an idealistic summer swim off the Florida Keys quite like a shark attack. Images of an imposing dorsal fin, large “white” teeth and generalized panic aside, how much have shark attacks over the last thirty years influenced the influx of residents on the Florida shoreline? Where would you look for the data? More importantly, which algorithm would a Data Scientist choose to predict the results and why?

With all the buzz concerning artificial intelligence, machine learning, and deep learning what exactly is the vision and value of each? More importantly, what can you learn about AI from the BAI in general, and our Summer School in particular?