Jupyter_Notebook.ipynb

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   "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": {
    "tags": []
   },
   "source": [
    "# Data Science Tools and Ecosystem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Introduction\n",
    "\n",
    "In this notebook, we will explore various tools and libraries that are essential in the field of data science. We will also perform some basic arithmetic operations using code cells."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Science Languages\n",
    "\n",
    "Some of the popular languages that Data Scientists use are:\n",
    "1. Python\n",
    "2. R\n",
    "3. SQL\n",
    "4. Java\n",
    "5. Julia"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Data Science Libraries\n",
    "\n",
    "Some of the commonly used libraries used by Data Scientists include:\n",
    "1. Pandas\n",
    "2. NumPy\n",
    "3. Matplotlib\n",
    "4. Scikit-learn\n",
    "5. TensorFlow\n",
    "6. Keras"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Science Tools\n",
    "\n",
    "| Tool          | Description                                     |\n",
    "|---------------|-------------------------------------------------|\n",
    "| Jupyter       | Interactive computing environment               |\n",
    "| RStudio       | Integrated development environment for R        |\n",
    "| Apache Spark  | Cluster-computing framework                     |\n",
    "| TensorFlow    | Open-source machine learning library            |\n",
    "| Tableau       | Data visualization tool                         |"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Arithmetic Expression Examples\n",
    "\n",
    "In this section, we will see examples of arithmetic expressions in Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22"
      ]
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This a simple arithmetic expression to mutiply then add integers\n",
    "a = 5\n",
    "b = 4\n",
    "result = a * b + 2\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.5"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This will convert 200 minutes to hours by diving by 60\n",
    "minutes = 150\n",
    "hours = minutes / 60\n",
    "hours"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Objectives\n",
    "\n",
    "- List popular languages for Data Science\n",
    "- List commonly used libraries in Data Science\n",
    "- Create a table of Data Science tools\n",
    "- Perform arithmetic operations using Python code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Author\n",
    "\n",
    "Markus"
   ]
  }
 ],
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    "name": "ipython",
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