Update pages/introduction.py

pages/introduction.py

@@ -1,12 +1,5 @@
 import streamlit as st 
 st.markdown("""<h2 style="text-align: center; display: inline; text-decoration: underline;">INTRODUCTION TO DATASCIENCE</h2>""",unsafe_allow_html=True)
-
-st.markdown("""<p style="font-family: 'Arial', sans-serif; font-size: 16px; color: blue;">Data science is a multidisciplinary field that combines statistics, programming, and domain expertise to extract meaningful insights from data. It involves collecting, cleaning, and analyzing vast amounts of structured and unstructured data to uncover patterns, trends, and valuable information.</p>""",unsafe_allow_html=True)
-st.markdown("""<p1 style="font-family: 'Arial', sans-serif; font-size: 16px; color: blue;">With the rise of digital technology, data is being generated at an unprecedented rate, and data science helps organizations make sense of it. By leveraging tools like Python, R, and machine learning algorithms, data scientists solve real-world problems in areas like healthcare, finance, marketing, and more.</p1>""",unsafe_allow_html=True)
-st.markdown("""<p2 style="font-family: 'Arial', sans-serif; font-size: 16px; color: blue;">For example, in e-commerce, data science is used to personalize customer recommendations, while in healthcare, it assists in disease prediction. Critical thinking and curiosity are essential for a data scientist to derive actionable insights from complex datasets. As businesses increasingly rely on data-driven decisions, data science has become one of the most sought-after and impactful career paths.</p2>""",unsafe_allow_html=True)
-import base64
-
-# Convert the local image to a Base64 string
 def get_base64_image(img_path):
     with open(img_path, "rb") as f:
         data = f.read()
@@ -23,3 +16,9 @@ html_code = f"""
 """
 st.markdown(html_code, unsafe_allow_html=True)
 
+st.markdown("""<p style="font-family: 'Arial', sans-serif; font-size: 16px; color: blue;">Data science is a multidisciplinary field that combines statistics, programming, and domain expertise to extract meaningful insights from data. It involves collecting, cleaning, and analyzing vast amounts of structured and unstructured data to uncover patterns, trends, and valuable information.</p>""",unsafe_allow_html=True)
+st.markdown("""<p1 style="font-family: 'Arial', sans-serif; font-size: 16px; color: blue;">With the rise of digital technology, data is being generated at an unprecedented rate, and data science helps organizations make sense of it. By leveraging tools like Python, R, and machine learning algorithms, data scientists solve real-world problems in areas like healthcare, finance, marketing, and more.</p1>""",unsafe_allow_html=True)
+st.markdown("""<p2 style="font-family: 'Arial', sans-serif; font-size: 16px; color: blue;">For example, in e-commerce, data science is used to personalize customer recommendations, while in healthcare, it assists in disease prediction. Critical thinking and curiosity are essential for a data scientist to derive actionable insights from complex datasets. As businesses increasingly rely on data-driven decisions, data science has become one of the most sought-after and impactful career paths.</p2>""",unsafe_allow_html=True)
+import base64
+
+