Improved clarity and consistency in 'get started' call to action

Author: vdauwera

docs/hello_nextflow/index.md

@@ -12,7 +12,7 @@ The rise of big data has made it increasingly necessary to be able to analyze an
 
 During this training, you will be introduced to Nextflow in a series of complementary hands-on workshops.
 
-Let's get started! Click on the "Open in GitHub Codespaces" button below.
+Let's get started! Click on the "Open in GitHub Codespaces" button below to launch the training environment (preferably in a separate tab), then read on while it loads.
 
 [![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/nextflow-io/training?quickstart=1&ref=master)
 

docs/nf4_science/genomics/index.md

@@ -11,10 +11,9 @@ It builds on the [Hello Nextflow](../../hello_nextflow/) beginner training and d
 
 Specifically, this course demonstrates how to implement a simple variant calling pipeline with [GATK](https://gatk.broadinstitute.org/) (Genome Analysis Toolkit), a widely used software package for analyzing high-throughput sequencing data.
 
-!!! note
+Let's get started! Click on the "Open in GitHub Codespaces" button below to launch the training environment (preferably in a separate tab), then read on while it loads.
 
-    Don't worry if you're not familiar with GATK specifically.
-    We'll summarize the necessary concepts as we go, and the workflow implementation principles we demonstrate here apply broadly to any command line tool that processes genomics data.
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/nextflow-io/training?quickstart=1&ref=master)
 
 ## Learning objectives
 
@@ -40,9 +39,3 @@ The course assumes some minimal familiarity with the following:
 - Foundational Nextflow concepts and tooling covered in the [Hello Nextflow](../../hello_nextflow/) beginner training.
 
 For technical requirements and environment setup, see the [Environment Setup](../../envsetup/) mini-course.
-
-## Get started
-
-To get started, open the training environment by clicking the 'Open in GitHub Codespaces' button below.
-
-[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/nextflow-io/training?quickstart=1&ref=master)

docs/nf4_science/rnaseq/00_orientation.md

@@ -3,7 +3,7 @@
 The training environment contains all the software, code and data necessary to work through this training course, so you don't need to install anything yourself.
 However, you do need a (free) account to log in, and you should take a few minutes to familiarize yourself with the interface.
 
-If you have not yet done so, please follow [this link](../../../envsetup/) before going any further.
+If you have not yet done so, please the [Environment Setup](../../envsetup/) mini-course before going any further.
 
 ## Materials provided
 

docs/nf4_science/rnaseq/index.md

@@ -11,18 +11,23 @@ It builds on the [Hello Nextflow](../../hello_nextflow/) beginner training and d
 
 Specifically, this course demonstrates how to implement a simple bulk RNAseq processing pipeline to trim adapter sequences, align the reads to a genome reference and performs quality control (QC) at several stages.
 
+Let's get started! Click on the "Open in GitHub Codespaces" button below to launch the training environment (preferably in a separate tab), then read on while it loads.
+
+[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/nextflow-io/training?quickstart=1&ref=master)
+
 ## Learning objectives
 
 By working through this course, you will learn how to apply foundational Nextflow concepts and tooling to a typical RNAseq use case.
 
 By the end of this workshop you will be able to:
 
 - Write a linear workflow to apply basic RNAseq processing and QC methods
-- Handle domain-specific files such as FastQ and reference genome resources appropriately
+- Handle domain-specific files such as FASTQ and reference genome resources appropriately
 - Handle single-end and paired-end sequencing data
 - Leverage Nextflow's dataflow paradigm to parallelize per-sample RNAseq processing
+- Aggregate QC reports across multiple steps and samples using relevant channel operators
+
 <!-- TODO
-- Implement **[quality control aggregation??]** using relevant channel operators
 - Configure pipeline execution and manage and optimize resource allocations
 - Implement per-step and end-to-end pipeline tests that handle RNAseq-specific idiosyncrasies appropriately
 -->
@@ -37,9 +42,3 @@ The course assumes some minimal familiarity with the following:
 - Foundational Nextflow concepts and tooling covered in the [Hello Nextflow](../../hello_nextflow/) beginner training.
 
 For technical requirements and environment setup, see the [Environment Setup](../../envsetup/) mini-course.
-
-## Get started
-
-To get started, open the training environment by clicking the 'Open in GitHub Codespaces' button below.
-
-[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/nextflow-io/training?quickstart=1&ref=master)