chore

_toctree.yml

@@ -1,7 +1,7 @@
 - title: Course introduction
   sections:
   - local: unit0/README
-    newlocal: unit1/1
+    newlocal: unit0/1
     title: Introduction
 
 - title: 1. Introduction to diffusion models

unit0/README.md

@@ -1,13 +1,4 @@
-# Introduction
-
-<CourseFloatingBanner
-    unit={0}
-    classNames="absolute z-10 right-0 top-0"
-/>
-
-## Welcome to the course on diffusion models 🤗 !
-
-## What to expect?
+# Hugging Face Diffusion Models Course
 
 In this free course, you will:
 - 👩‍🎓 Study the theory behind diffusion models
@@ -18,7 +9,7 @@ In this free course, you will:
 - 🧑‍🔬 Create your own custom diffusion model pipelines
 
 
-## Prérequis
+## Prerequisites
 This course requires a good level in Python and a grounding in deep learning and Pytorch.
 If it's not the case yet, you can check these free resources:
 - Python: https://www.udacity.com/course/introduction-to-python--ud1110
@@ -46,7 +37,7 @@ Advanced techniques for going further with diffusion
 
 About the authors:
 
-[**Jonathan Whitaker**](https://huggingface.co/johnowhitaker) is TODO.
+[**Jonathan Whitaker**](https://huggingface.co/johnowhitaker) is a Data Scientist/AI Researcher doing R&D with [answer.ai](https://www.answer.ai/). He likes teaching and making courses. His current focus is on generative AI, flitting between several modalities. You can find more info at: [johnowhitaker.dev](https://johnowhitaker.dev/).
 
 [**Lewis Tunstall**](https://huggingface.co/lewtun) is a machine learning engineer at Hugging Face, focused on developing open-source tools and making them accessible to the wider community. He is also a co-author of the O’Reilly book [Natural Language Processing with Transformers](https://www.oreilly.com/library/view/natural-language-processing/9781098136789/).