Wording tweaks

contents/labs/labs.qmd

@@ -2,10 +2,12 @@
 
 Welcome to the hands-on labs section where you'll explore deploying machine learning models onto real embedded devices, offering a practical introduction to ML systems. Unlike traditional approaches with large-scale models, these labs focus on interacting directly with both hardware and software. They help us show case various sensor modalities across different application use cases. This approach provides valuable insights into the challenges and opportunities of deploying AI on real physical systems.
 
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 ## Learning Objectives
 
+By completing these labs, we hope learners will:
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 * Gain proficiency in setting up and deploying ML models on supported devices enabling you to tackle real-world ML deployment scenarios with confidence.
 
 * Understand the steps involved in adapting and experimenting with ML models for different applications allowing you to optimize performance and efficiency.
@@ -56,4 +58,4 @@ Each lab follows a structured approach:
 
 ## Troubleshooting and Support
 
-If you encounter any issues during the labs, consult the troubleshooting guides and FAQs provided with each lab. For further assistance, feel free to reach out to our support team or engage with the community forums.    
+If you encounter any issues during the labs, consult the troubleshooting comments or check the FAQs within each lab. For further assistance, feel free to reach out to our support team or engage with the community forums.