AI Foundations for Robotics Course - Python

AI, AI for beginers, AI basics, probability

Course Summary

In this course, through robot simulations, we will guide you in your first steps into the AI world. Understanding the topics explained in this course is crucial for being able to develop your own models. Let's learn AI Foundations together!

What you will learn

Univariate probability, multivariate probability, statistics, decision theory, information theory, logistic regression.

Course Overview

Unit 1: Introduction

In this unit you will see an overview of the "AI Foundations for Robotics" course.

Unit 2: Univariate probability

In this unit you will learn the basic concepts of probability theory.

Unit 3: Probability through multivariate model

In this unit, you will learn the basic concepts of multivariate probability.

Unit 4: Statistics

In this unit you will learn how to make parameters´ inference through statistics.

Unit 5: Decision Theory

In this unit you will learn the basic concepts of Decision Theory.

Unit 6: Information Theory

In this unit you will learn the basis of Information Theory.

Unit 7: Logistic regression

In this unit you will learn to implement a classification AI model from scratch.

Unit 8: Final Project

In this unit you will create your custom AI classification model from scratch: from collecting the data to the model´s final validation, you will be part of all the instances.

Teachers

Estanislao Escudero

I'm a Mechanical Engineer who looks forward to learn more about robotics and AI.