DataScienceEcosystem.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",
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Add your code below following the instructions given in the course\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 1: Create a Jupyter Notebook**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "Name: DataScienceEcosystem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 2: Create markdown cell with title of the notebook using H1 style heading.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Science Tools and Ecosystem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 3 - Create a markdown cell for an introduction**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this notebook, Data Science Tools and Ecosystem are summarized."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "**Objectives:**\n",
    "* List popular languages that Data Scientists use.\n",
    "* List commonly used libraries used by Data Scientists.\n",
    "* Comment on Data Science tools."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 4 - Create a markdown cell to list data science languages**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some of the popular languages that Data Scientists use are:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "1. Python.\n",
    "2. R.\n",
    "3. SQL.\n",
    "4. Java.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 5 - Create a markdown cell to list data science libraries**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some of the commonly used libraries used by Data Scientists include:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. Pandas.\n",
    "2. Matplotlib.\n",
    "3. NumPy.\n",
    "4. TensorFlow."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 6 - Create a markdown cell with a table of Data Science tools**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "|Data Science Tools|\n",
    "---------\n",
    "|RStudio|\n",
    "|Apache Spark|\n",
    "|Jupyter|"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 7 - Create a markdown cell introducing arithmetic expression examples.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Below are a few examples of evaluating arithmetic expressions in Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 8 - Create a code cell to multiply and add numbers**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17"
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     "execution_count": 10,
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   "source": [
    "#This a simple arithmetic expression to mutiply then add integers\n",
    "(3*4)+5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 9 - Create a code cell to convert minutes to hours**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.3333333333333335 Hours\n"
     ]
    }
   ],
   "source": [
    "##This will convert 200 minutes to hours by diving by 60\n",
    "Hour = 60\n",
    "Minutes = 200\n",
    "Minutes_to_Hour = (Minutes / Hour)\n",
    "print(Minutes_to_Hour, \"Hours\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 10 - Insert a markdown cell to list Objectives**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Below the introduction cell created in Exercise 3, insert a new markdown cell to list the objectives that this notebook covered (i.e. some of the key takeaways from the course). In this new cell start with an introductory line titled: Objectives: in bold font. Then using an unordered list (bullets) indicate 3 to 5 items covered in this notebook, such as List popular languages for Data Science."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### **Exercise 11 - Create a markdown cell to indicate the Author's name**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Author\n",
    "Juan Sebastian Rodriguez "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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