diff --git a/Cyberbullying Classification/README.md b/Cyberbullying Classification/README.md
index 770611f3c1..8aa4cf0784 100644
--- a/Cyberbullying Classification/README.md	
+++ b/Cyberbullying Classification/README.md	
@@ -1,4 +1,4 @@
-# Fetal Health Classification
+# Cyberbullying Classification
 
 ## Overview
 The goal is to analyze tweets to classify them into categories of cyberbullying and non-cyberbullying using NLP techniques and machine learning models.
@@ -6,7 +6,7 @@ The goal is to analyze tweets to classify them into categories of cyberbullying
 ## Dataset
 The dataset contains over 47,000 tweets labeled into six categories: Age, Ethnicity, Gender, Religion, Other type of cyberbullying, and Not cyberbullying.
 
-Link to the dataset: [Fetal Health Classification Dataset](https://www.kaggle.com/datasets/andrewmvd/cyberbullying-classification/data)
+Link to the dataset: [Cyberbullying Classification Dataset](https://www.kaggle.com/datasets/andrewmvd/cyberbullying-classification/data)
 
 
 ## Models Used
diff --git a/Cyberbullying Classification/cyberbullying-classification.ipynb b/Cyberbullying Classification/cyberbullying-classification.ipynb
index b07324f519..38f5a68bf5 100644
--- a/Cyberbullying Classification/cyberbullying-classification.ipynb	
+++ b/Cyberbullying Classification/cyberbullying-classification.ipynb	
@@ -4717,7 +4717,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.13"
+   "version": "3.11.0"
   },
   "papermill": {
    "default_parameters": {},