Sat, 25 Jan

|

2 Savoy Pl

A Crash Course in AI: Everything You Wanted to Know About AI but Are Afraid to Ask!

Taught by Dr. Ronjon Nag, a seasoned entrepreneur and Stanford lecturer, who has founded and advised companies sold to Motorola, BlackBerry and Apple. This is a one day course which will demystify artificial intelligence techniques for executives, product managers, and software engineers.

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A Crash Course in AI: Everything You Wanted to Know About AI but Are Afraid to Ask!

Time & Location

25 Jan 2020, 09:00 – 17:00 GMT

2 Savoy Pl, 2 Savoy Pl, London WC2R 0BL, UK

About The Event

Taught by Dr. Ronjon Nag, a seasoned entrepreneur and Stanford lecturer, who has founded and advised companies sold to Motorola, BlackBerry and Apple.

Artificial Intelligence (AI) is a term that is widely used and abused everywhere and has given rise to powerful techniques known as neural networks and deep learning. However, what do these terms mean and what is hype and what is real. This is a one day course which will demystify artificial intelligence techniques for executives, product managers, and software engineers. The course is accessible to all levels of experience and will also give an opportunity to network with executives, investors and entrepreneurs. This highly curated one day event will be held at a beautiful venue of historical significance in central London. Capacity will be limited.

​Additionally, there will be an invite-only dinner in the evening for a small group of guests to discuss AI and Healthcare opportunities.

Course Outline: 9am - 5pm

Lecture 1

  • Class structure, Broad Overview of AI, Machine Learning, Deep Learning
  • How does a neural network work? Perceptrons, Neural networks with real numbers.
  • Playing with Tensorflow Playground

BREAK

Lecture 2

  • Advanced neural networks: Convolutional Neural Networks, LSTMs, End-To-End
  • Neural Networks, Playing with Google Collab Neural Network Applications
  • Applications: AI for Healthcare & Longevity

LUNCH BREAK

Lecture 3

  • Evaluating AI Systems, Over and Under Fitting,
  • Reinforcement Learning
  • Generative Adverserial Networks
  • Deep Fakes, Explainable AI, Ethics and Regulation

Lecture 4

  • Boundaries of Humanity
  • Brain-Machine Interfaces
  • AI Competitiveness
  • Investing in AI and Applications
  • Where is Strong AI Going to Come From

This Course is Suitable For:

  • General Public​
  • Non-AI Engineers​
  • People who Interact with AI engineers – Marketing, HR, Finance
  • Venture Capitalists​
  • People who Work for an AI Company but are not in an AI Implementation Function​
  • Policy Makers, Strategists, Entrepreneurs who want to build AI Products and Want to Understand Potential and Limitations
  • AI Engineers who Want to Learn how to Explain AI in Simple Terms to their Colleagues and be Exposed to Wider AI Concepts and Tools