Learn the Technical Aspects of AI and ML in the Easiest Way Possible

What you will learn

Students who want to learn AI and ML

Students with some but limited coding experience

Students who want to learn AI and ML in the easiest way possible

Students who want access to lots of prebuilt models and resources

Description

Taking the time to learn the technical ins and outs of machine learning and artificial intelligence is a big step. However, a lot of people do not even make it past the first hurdle. Setting up Python, running in Terminals, learning what a Jupyter Notebook even is. All of these tasks come before the actual process of diving into learning to code in most instances. As a result of these extraneous hurdles, many people do not find it worthwhile to learn. There is no immediate reward or payoff for learning any of these things.

This course is specifically designed for the student that would like to skip that introductory step and dive straight into the code and playing with functional models. Whether you want to learn the basics of machine learning, or you want to run Mixtral itself, this course has a Colab Notebook that will suit your needs.


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You will literally not be able to find a majority of these Colab Notebooks anywhere else, as they are ones I have built out myself. Over six pages of notebook links are available to you as soon as you sign up for this course. The course is also broken up into six sections, which cover the six sections of Notebook Resources available to you overall.

English
language

Content

Introduction

Introduction

Narrow AI and Just Getting Started

Narrow AI and Just Getting Started

Micro and Small Models

Micro and Small Models

Medium and Large Models

Medium and Large Models

Audio and Visual Models

Audio and Image Generation Models

Agents and Function Calling

Agents and Function Calling