Added further LOs

Author: madeline-underwood

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

@@ -7,6 +7,12 @@ who_is_this_for: This is an advanced topic for software developers who want to l
 
 learning_objectives:
      - Improve SIMD code performance using Scalable Vector Extension (SVE) and Scalable Matrix Extension (SME).
+     - 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
+     - 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
+
 
 prerequisites:
     - An AArch64 computer running Linux or macOS. You can use cloud instances, refer to [Get started with Arm-based cloud instances](/learning-paths/servers-and-cloud-computing/csp/) for a list of cloud service providers.