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Jupyter_Notebook.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<center>\n",
+    "    <img src=\"https://cf-courses-data.s3.us.cloud-object-storage.appdomain.cloud/IBMDeveloperSkillsNetwork-DS0105EN-SkillsNetwork/labs/Module2/images/SN_web_lightmode.png\" width=\"300\" alt=\"cognitiveclass.ai logo\">\n",
+    "</center>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### Add your code below following the instructions given in the course\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Data Science Tools and Ecosystem"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In this notebook, Data Science Tools and Ecosystem are summarized."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Objectives**\n",
+    "  \n",
+    "- List popular languages for Data Science.\n",
+    "- Identify key libraries used in Data Science.\n",
+    "- Explain the conversion of time units (e.g., minutes to hours).\n",
+    "- Describe open-source tools for data science development.\n",
+    "- Understand basic arithmetic operations in Python."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python",
+   "language": "python",
+   "name": "conda-env-python-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}