docs: add links to Jupyter notebook tutorials

Author: thewtex

docs/cxx/tutorial/index.md

@@ -10,6 +10,9 @@ This tutorial will walk you through the process of *creating WebAssembly scienti
 6. Handle non-trivial data types a the wasm pipeline interface.
 7. Debug a wasm pipeline.
 
+This [Jupyter notebook
+tutorial](https://github.com/InsightSoftwareConsortium/ScientificImageAnalysisVisualizationAndArtificialIntelligenceCourse/blob/master/10_Create_Scientific_WebAssembly_Pipelines.ipynb) also provides an interactive walkthrough.
+
 ```{toctree}
 :maxdepth: 2
 :caption: 📖 Tutorial Steps
@@ -18,4 +21,4 @@ hello_world.md
 hello_pipeline.md
 inputs_outputs.md
 debugging.md
-```
+```

docs/python/introduction.md

@@ -14,6 +14,10 @@ At a system level, Linux, macOS, and Windows operating systems are supported on
 
 `itkwasm` Python packages are *highly modular*, have *a tiny footprint*, and have *minimal dependencies*; they only depend on `itkwasm`, `numpy`, and `pyodide` or `wasmtime` {octicon}`container`.
 
+This [Jupyter notebook
+tutorial](https://github.com/InsightSoftwareConsortium/ScientificImageAnalysisVisualizationAndArtificialIntelligenceCourse/blob/master/9_WebAssembly_Introduction.ipynb)
+provides further background information and related hands-on experiences.
+
 ## Environment dispatch
 
 There is a primary, pip-installable Python package. In browser environments, this will pull a corresponding [Emscripten](https://emscripten.org)-enabled Python package. For system Python distributions, this will bring in a corresponding [WASI](https://wasi.dev)-enabled Python package. When GPU-accelerated implementations of functions are available in other packages along with required hardware and software, simply pip-installing the accelerator package will cause function calls to invoke accelerated overrides registered with modern [package metadata](https://packaging.python.org/en/latest/guides/creating-and-discovering-plugins/#using-package-metadata).