Corrected numbering on weightings

Author: madeline-underwood

content/learning-paths/cross-platform/simd-loops/1-about.md

@@ -1,6 +1,6 @@
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 title: About single instruction, multiple data (SIMD) loops
-weight: 3
+weight: 2
 
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 layout: learningpathall

content/learning-paths/cross-platform/simd-loops/2-using.md

@@ -1,6 +1,6 @@
 ---
 title: Using SIMD Loops
-weight: 4
+weight: 3
 
 ### FIXED, DO NOT MODIFY
 layout: learningpathall

content/learning-paths/cross-platform/simd-loops/3-example.md

@@ -1,6 +1,6 @@
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 title: Code example
-weight: 5
+weight: 4
 
 ### FIXED, DO NOT MODIFY
 layout: learningpathall

content/learning-paths/cross-platform/simd-loops/4-conclusion.md

@@ -1,6 +1,6 @@
 ---
 title: Conclusion
-weight: 6
+weight: 5
 
 ### FIXED, DO NOT MODIFY
 layout: learningpathall

content/learning-paths/cross-platform/simd-loops/_index.md

@@ -9,7 +9,7 @@ learning_objectives:
   - Improve SIMD loop performance using Scalable Vector Extension (SVE), SVE2, and Scalable Matrix Extension (SME2)
   - Explore how SVE-indexed fmla and SME2 fmopa instructions accelerate matrix multiplication
   - Understand how SME2 kernels use ZA tiles and streaming attributes
-  - Describe what SIMD Loops contains and how kernels are organized across scalar, NEON, SVE/SVE2, and SME2 variants
+  - Describe what the SIMD Loops project contains and how kernels are organized across scalar, NEON, SVE/SVE2, and SME2 variants
   - Build and run a selected kernel with the provided runner and validate correctness against the C reference
   - Choose the appropriate build target to compare NEON, SVE/SVE2, and SME2 implementations