{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# My Jupyter Notebook on IBM Data Science Experience"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Florian Noichl**  \n",
    "Junior Project Manager"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*My interest in Data Science comes from a strong curiosity to learn trends and derive predictions from data. I am pursuing this course to facilitate my start into a Data Science career as an engineer.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculates \"1 + 1\", ctrl+ent to run and show result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1+1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. First item\n",
    "2. Second item\n",
    "3. Third item\n",
    "----\n",
    "* Item A\n",
    "* Item B\n",
    "* Item C\n",
    "----\n",
    "Example | Table | Exercise\n",
    "--- | --- | ---\n",
    "random | cell | content\n",
    "1 | 2 | 3\n",
    "\n",
    "----\n"
   ]
  }
 ],
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  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
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 "nbformat": 4,
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