Fundamentals of Dask Transcripts
Chapter: Welcome to the course
Lecture: Introduction

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0:00 Hi everyone. Welcome to fundamentals of DASK. We are so excited to get started with the second course on DASK.
0:07 Follow along with the course. All you need is some basic experience with Python programming The first Dask course getting started with,
0:14 Dask covered some basic Dask concepts and discuss 'Dask Data Frame' in detail. The topics in this course will be built on previous topics.
0:22 So if you haven't watched the first course yet, we encourage you to check it out. Working with 'NumPy', 'pandas' and 'scikit-learn'.
0:27 We'll help you follow the course better. But don't worry if you haven't used these before.
0:30 We'll explain everything we use. In this course will look at three more Dask collections, 'Dask Array' that helps parallize 'NumPy code',
0:39 'Dask Delay' that can parallelize general Python code and 'Dask Bag', which allows us to work with Unstructured and Messy Data.
0:46 In parallel, we're then going to take a deeper dive and look at 'Dask Schedulers' We'll also talk more about 'Dask-ML'.
0:53 For Machine Learning, which lets us parallelized 'Scikit-learn' code, will complete the course by scaling the Machine Learning code to the cloud.
1:01 I hope you're as excited as me to learn about Dask. Let's get started


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