Past Courses

February 2019

PAC Framework 

How Non Tech Executives can Implement AI 

Date: Wednesday, February 6th, 2019 | 1.5 hours 

Presented By: Rob May, CEO, Talla 

Description: You want to implement AI at your company but aren’t sure where to start. This course is a great introduction to a new framework for evaluating opportunities to deploy AI at your company.  Rob will explain The Predict, Automate and Classify framework in detail. He will then guide you through an exercise to create your own PAC chart for your business.  This course is most valuable to senior executives who are figuring out their AI strategy, but is open to all. 

Strategic Thinking in AI 

How Artificial Intelligence changes the way you think about corporate strategy

Date: Wednesday, February 27th, 2019 | 1.5 hours 

Presented By: Rob May, CEO, Talla 

About: AI is changing some of the fundamental concepts of strategy. This class will cover value chains, competitive advantage, and other high level strategic concepts and discuss how artificial intelligence changes the way you think about corporate strategy.  

March 2019

The Road from Engineer to Executive 

Date: Wednesday,  March 6th, 2019 | 1.5 hours 

Presented By: Paula Long, SVP of Engineering, Talla 

About: Join us for a presentation led by our Senior VP of Engineering, Paula Long on the path from engineer to exec.

Selling and Marketing AI Products 

Date: Wednesday,  March 13th, 2019 | 1.5 hours 

Presented By: Rob Levy, Director of Sales, Talla 

About: Rob Levy, Director of Sales and Marketing at Talla, will lead this presentation covering how to sell and market AI Products.

AI Product Management 

Date: Wednesday,  March 20th, 2019 | 1.5 hours 

Presented By: Yemi Adepetu, Product Manager, Talla 

About: This course is led by Talla’s Product Manager, Yemi Adepetu, who will cover best practices of product management at an AI company.

April 2019

AI 101: Demystifying AI and Exploring Business Use Cases

Date: Wednesday, April 3rd, 2019 | 2 hours

Presented By: Dhairya Dalal, Data Scientist, Talla

About: It is an exciting time for AI research. There are breakthroughs being published and new technologies emerging almost every week. It can feel overwhelming to keep up and make sense of the broad scope of capabilities and technologies (GANs, deep learning, decision trees, and so much more). Part of the challenge is that this research is often technical, nuanced and scoped around specific academic problems. What does it mean to use neural networks for your organization. Does it even make sense to use these technologies? 

In this workshop, we aim provide an introduction to the research and state of AI technology today. Our goal is help you frame and map business challenges to appropriate AI solutions. We will provide you with a framework to communicate business goals and requirements to data science / AI research teams. You will learn what exactly AI research entails, where it can (and often can’t!) provide value for real world use cases, and how to take a information-centric world view in order understand how AI can benefit your organization.

Machine Learning for Non Technical Execs

Date: Wednesday, April 10th, 2019 | 1.5 hours – Being Rescheduled!

Presented By: Rob May, CEO, Talla 

About: In this talk, Rob will cover the basics of Machine Learning and the many ways it is used in everyday technology today. He will review why so many enterprises are utilizing ML and why you should care or implement into your own organization.

This is a great course for those leading teams in Sales, Marketing, Customer Success, Product, Support, etc and are not as familiar with ML concepts as other technically focused execs.

Imitation Learning – Reinforcement Learning for the Real World

Date: Wednesday, April 24th, 2019 @ 6PM ET

Presented by: Byron Galbraith, Co-founder & Chief Data Scientist, Talla

About:Reinforcement Learning has seen an explosion of work in the last few years with some high profile results from DeepMind with AlphaZero. Most of the success has been demonstrated on games – either two-player fully observable environments like Chess and Go, or classic Atari video games like Breakout and Pitfall that can be efficiently simulated at large scales. Yet, for all the hyped up results, there has been little translation to the real world yet.

Imitation Learning is a related approach to RL, but instead of having the AI agent learn from scratch through its own exploration, Imitation Learning is about learning decision policies from expert demonstrations. This talk will introduce the formal Imitation Learning problem, methods that are used to train agents under this paradigm, and examples of how this can be used to solve real world problems.


Best Practices for rolling out AI-Powered Tools

Date: May 1st, 2019 @ 6pm ET

Presented by: Lauren Mecca, Director of Customer Success, Talla

Lauren currently leads Customer Success at Talla. She comes from a background of working with customers in startups serving a wide range of industries, from the arts to agencies to real estate. She is obsessed with making progress and enthusiastic about people (and Radical Candor™). As a Customer Success leader she is always trying to answer tough questions that will improve the value Talla delivers to customers.

Talla provides AI-powered automation for knowledge management tasks and a lot of our customers are Customer Support teams. With customer-facing teams as our client base, it’s especially important that on-boarding, self-help, and support are well thought out. And each element of the customer experience may look a little different when you’re dealing with an AI-powered tool.

So whether you’re already working for an AI company or interested in working in AI someday, join us on May 1st for a presentation and discussion with colleagues in Customer Success.

Agent-Based Modeling – Understanding Complex Systems through Simulation

Date: May 15th, 2019 @ 6pm ET

Presented by: Jon Klein, Chief Architect, Talla

About: Agent-based modeling is a computational technique for exploring complex systems through the simulation of interactions between autonomous agents.  These techniques can be used to explore systems of complex behaviors in biology, social sciences and economics among other fields.  By altering environmental conditions and agent behaviors, we can explore how those changes affect the system as a whole and observe how “emergent behaviors” can arise in complex systems.

This talk will explore agent-based modeling and its applications.  We’ll look at some specific examples using the NetLogo modeling environment and attendees will learn how they build their own agent based models.


The Interpretation of Loss Functions

Date: Wednesday, July 17th, 2019

Presented by: Daniel Shank, Data Scientist, Talla

About: This course will be led by Daniel Shank, Data Scientist @ Talla, and is great for anyone looking to dive deeper into machine learning, who works as a data scientist or is interested in learning more about data science in general.

Machine learning and statistics both solve problems by finding minds with the best fit to data. But how ‘best fit’ is defined can vary wildly, and it can be difficult to figure out what is happening when we choose a model to minimize a loss function. In this course I’m going to talk about common loss functions, how they are used, and how we can use statistics to interpret what they mean.