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NGS for natural scientist
  • 1. Preface
    • How to use this book
    • Motivation
    • Genomic data science as a tool to biologist
    • Next Generation Science (also NGS)
  • 2. Getting started
    • A step by step pipeline tutorial
    • Sequencing chemistry explained by Illumina
    • Joining a course
    • RNA quality and Library prep
    • (optional) My click moment about "Why Linux"
  • 3. Good-to-know beforehand
    • Experiment design
    • Single-end and Paired-end
    • Read per sample and data size
    • Normalization - RPKM/FPKM/TPM
    • Gene annotation
  • 4. Setting up terminal
    • My Linux terminal
    • Linux environment
    • R and RStudio
    • PATH
  • 5. FASTQ and quality control
    • Getting FASTQ files from online database
    • FASTQ quality assessment
  • 6. Mapping/alignment and quantification
    • Salmon
    • DESeq2
  • 7. Visualization
  • 8. Single cell RNA-Seq
  • 9. AWS cloud and Machine Learning
    • Machine Learning in a nutshell
    • R vs Python
    • Setting up ML terminal
    • Data exploration
  • (pending material)
    • graphPad
    • readings for ML
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9. AWS cloud and Machine Learning

Once I told a senior that when things started to fall into places, it means that it was meant to be. And I think I am saying that I am meant to be working with Amazon...?

Previous8. Single cell RNA-SeqNextMachine Learning in a nutshell

Last updated 2 months ago

When I was living in Japan (I was there for 3 years during COVID) I am a loyal customer to Amazon - You could totally break your bank to shop on Amazon in the UK but the Japanese have delivery spirit in their blood and therefore JP Amazon is affordable to a point that it is comparable to storefront offer. I know I am drifting off - there are many cloud platform providers (CIPS) on the market, why AWS?

It was totally NOT because of this market analysis - and don't get me started on why IBM is clustering with Chinese providers, I am still in a shock when someone 8 years younger than me asked me "which one is better at quantum computing, *insert a boutique IT consultancy* and IBM?" - it was only because the company I was at funded fully on AWS courses while provided partial support only on Microsoft and Google. THAT was the reason.

Simply put sometimes choices are not totally rational but rational enough to be a reason. And more importantly it is about to learn the cloud infrastructure as a basis on cloud technology. UX/UI can always change in an overnight, but the concept behind does not change that much, and when one looks at the no-code environment trend nowadays, coding is really a job for programmer while brains born with different settings should work on more suitable jobs such as to train a high-scoring AI/ML model than to code for the AI/ML model.

Global Data Science Challenge

Duration - 1 month

Resources - AWS platform

Input - Normal working hour

outcome - exposure to ML; project experience;

prize if I scored better than 80% - AWS Machine Learning cert exam voucher

Enough for digression and time to get to work!

I thought for a second what is the best way I want this section to be - and this already has nothing to do with NGS anymore, although I don't think it is irrelevant to science - the point when I came up with a .

The competition I was at
lame idea
AWS Named as a Leader in the 2022 Gartner Cloud Infrastructure & Platform Services (CIPS) Magic Quadrant for the 12th Consecutive Year | AWS News Blog