LinkedIn AI Academy AI-100: 1 Demystifying AI

Course details

Artificial intelligence has been in the public consciousness for decades, but is getting more and more attention every day as the technologies advance. There seems to be equal parts curiosity and anxiety when it comes to AI, and many people have questions about what exactly “artificial intelligence” means today—and all the pros and cons that come with it.

This course aims at demystifying AI—what AI is and how it works—by starting from simple, well-known concepts, and incrementally developing an understanding of complex AI methods and how they are used to build powerful applications at LinkedIn. Souvik Ghosh, Director of AI at LinkedIn, covers topics like the three pillars of AI, supervised and unsupervised learning, linear regression, classification, and gets into more complex topics like nonlinear models and neural networks. Join Souvik in this course to get a brief history of the field, the variety of ways in which AI touches our lives today, and the possibilities that lay ahead.

Concepts

0. Introduction

01 - The LinkedIn AI Academy - The imperative of understanding AI

1. Introduction to AI

02 - What is AI
03 - AI and machine learning
04 - Three pillars of AI - Objectives, data, algorithms
05 - Building real AI applications

2. Supervised Learning

06 - Supervised learning vs. unsupervised learning

3. Regression

07 - What is regression
08 - Linear regression
09 - Multiple linear regression
10 - Bias and variance
11 - Evaluating a linear regression model

4. Classification

12 - What is classification
13 - Logistic regression
14 - Evaluating models and choosing the best

5. Nonlinear Models

15 - Why are linear models not enough
16 - A primer to nonlinear models - Decision trees, neural networks

6. Do It Right

17 - Know your objective, know your data, and listen to the data

Conclusion

18 - Continuing with AI