Update YOLO11 docs (#16589)

Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>

docs/en/index.md

@@ -103,11 +103,15 @@ Ultralytics YOLO is the latest advancement in the acclaimed YOLO (You Only Look
 
 ### How can I get started with YOLO installation and setup?
 
-Getting started with YOLO is quick and straightforward. You can install the Ultralytics package using pip and get up and running in minutes. Here's a basic installation command:
+Getting started with YOLO is quick and straightforward. You can install the Ultralytics package using [pip](https://pypi.org/project/ultralytics/) and get up and running in minutes. Here's a basic installation command:
 
-```bash
-pip install ultralytics
-```
+!!! example
+
+    === "CLI"
+
+        ```bash
+        pip install ultralytics
+        ```
 
 For a comprehensive step-by-step guide, visit our [quickstart guide](quickstart.md). This resource will help you with installation instructions, initial setup, and running your first model.
 
@@ -119,11 +123,28 @@ Training a custom YOLO model on your dataset involves a few detailed steps:
 2. Configure the training parameters in a YAML file.
 3. Use the `yolo train` command to start training.
 
-Here's an example command:
+Here's example code:
 
-```bash
-yolo train model=yolo11n.pt data=coco128.yaml epochs=100 imgsz=640
-```
+!!! example
+
+    === "Python"
+
+        ```python
+        from ultralytics import YOLO
+
+        # Load a pre-trained YOLO model (you can choose n, s, m, l, or x versions)
+        model = YOLO("yolo11n.pt")
+
+        # Start training on your custom dataset
+        model.train(data="path/to/dataset.yaml", epochs=100, imgsz=640)
+        ```
+
+    === "CLI"
+
+        ```bash
+        # Train a YOLO model from the command line
+        yolo train data=path/to/dataset.yaml epochs=100 imgsz=640
+        ```
 
 For a detailed walkthrough, check out our [Train a Model](modes/train.md) guide, which includes examples and tips for optimizing your training process.
 
@@ -140,8 +161,27 @@ For more details, visit our [Licensing](https://www.ultralytics.com/license) pag
 
 Ultralytics YOLO supports efficient and customizable multi-object tracking. To utilize tracking capabilities, you can use the `yolo track` command as shown below:
 
-```bash
-yolo track model=yolo11n.pt source=video.mp4
-```
+!!! example
+
+    === "Python"
+
+        ```python
+        from ultralytics import YOLO
+
+        # Load a pre-trained YOLO model
+        model = YOLO("yolo11n.pt")
+
+        # Start tracking objects in a video
+        # You can also use live video streams or webcam input
+        model.track(source="path/to/video.mp4")
+        ```
+
+    === "CLI"
+
+        ```bash
+        # Perform object tracking on a video from the command line
+        # You can specify different sources like webcam (0) or RTSP streams
+        yolo track source=path/to/video.mp4
+        ```
 
 For a detailed guide on setting up and running object tracking, check our [tracking mode](modes/track.md) documentation, which explains the configuration and practical applications in real-time scenarios.