diff --git a/src/content/docs/client-apis/swift.mdx b/src/content/docs/client-apis/swift.mdx
index 93fb794..ec747c1 100644
--- a/src/content/docs/client-apis/swift.mdx
+++ b/src/content/docs/client-apis/swift.mdx
@@ -9,5 +9,5 @@ See the following link for the full documentation of the `swift-ladybug` package
 
 <LinkCard
   title="Swift API documentation"
-  href="https://api-docs.ladybugdb.com/swift/documentation/lbug/"
+  href="https://api-docs.ladybugdb.com/swift/"
 />
diff --git a/src/content/docs/get-started/graph-algorithms.md b/src/content/docs/get-started/graph-algorithms.md
index af78a4d..d329438 100644
--- a/src/content/docs/get-started/graph-algorithms.md
+++ b/src/content/docs/get-started/graph-algorithms.md
@@ -14,7 +14,7 @@ in Python to run almost any graph algorithm on a Ladybug subgraph.
 ## Prepare the dataset
 
 A dataset of Nobel laureates and their mentorship network is provided
-[here](https://raw.githubusercontent.com/ladybugdb/ladybug/tutorials/main/src/network_analysis/data.zip).
+[here](https://huggingface.co/datasets/ladybugdb/python-tutorial/blob/main/nobel-mentorship.zip).
 Download the dataset to your local directory and unzip it.
 
 The nodes in the dataset are scholars who won Nobel prizes, as well as other
@@ -408,5 +408,4 @@ For performance and scalability, it's recommended to use Ladybug's native `algo`
 is available. If not, you can always fall back to using NetworkX, which has a far more extensive suite of
 graph algorithms.
 
-To reproduce the analysis shown in this tutorial, see the code
-[here](https://github.com/LadybugDB/tutorials/tree/main/src/network_analysis).
+To reproduce the analysis shown in this tutorial, run the code snippets above after placing the CSV files in `./data`.
diff --git a/src/content/docs/installation.mdx b/src/content/docs/installation.mdx
index ffde324..d564cd4 100644
--- a/src/content/docs/installation.mdx
+++ b/src/content/docs/installation.mdx
@@ -20,8 +20,8 @@ tar xzf lbug_cli-*.tar.gz`,
 macos: `curl -L -O https://github.com/LadybugDB/ladybug/releases/download/v${version}/lbug_cli-osx-universal.tar.gz
 tar xzf lbug_cli-*.tar.gz
 ./lbug`,
-    win: `curl -L -O https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip`,
-    winUrl: `https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip`,
+    win: `curl -L -O https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip`,
+    winUrl: `https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip`,
   },
 java: `<dependency>
   <groupId>com.ladybugdb</groupId>
@@ -41,7 +41,7 @@ tar xzf liblbug-*.tar.gz`,
 tar xzf liblbug-*.tar.gz`,
     win: `curl -L -O https://github.com/LadybugDB/ladybug/releases/download/v${version}/liblbug-windows-x86_64.zip`
 },
-  go: `go get https://github.com/LadybugDB/go-ladybug@v0.13.1`,
+  go: `go get github.com/LadybugDB/go-ladybug`,
 swift: `dependencies: [
   .package(url: "https://github.com/LadybugDB/swift-ladybug/", branch: "${version}"),
 ],`
@@ -100,10 +100,10 @@ Alternatively, you can download the Ladybug CLI directly.
 <TabItem label="Windows">
 
 Use a tool like `curl` to download the latest version of the Ladybug CLI to your local machine. Alternatively,
-simply open [this URL](https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip) in your browser.
+simply open [this URL](https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip) in your browser.
 
 ```bash
-curl -L -O https://github.com/LadybugDB/ladybug/releases/download/latest/lbug_cli-windows-x86_64.zip
+curl -L -O https://github.com/LadybugDB/ladybug/releases/latest/download/lbug_cli-windows-x86_64.zip
 ```
 
 Right-click on the `lbug_cli-xxx.zip` file and click on **Extract All**. This will create a directory