diff --git a/01-Python_Introduction/Python_Crash_Course-with_solutions.ipynb b/01-Python_Introduction/Python_Crash_Course-with_solutions.ipynb
index 7508793..aea40d5 100644
--- a/01-Python_Introduction/Python_Crash_Course-with_solutions.ipynb
+++ b/01-Python_Introduction/Python_Crash_Course-with_solutions.ipynb
@@ -2,7 +2,11 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "<div style='background-image: url(\"../images/header.svg\") ; padding: 0px ; background-size: cover ; border-radius: 5px ; height: 250px'>\n",
     "    <div style=\"float: right ; margin: 50px ; padding: 20px ; background: rgba(255 , 255 , 255 , 0.7) ; width: 50% ; height: 150px\">\n",
@@ -11,13 +15,8 @@
     "            <div style=\"font-size: large ; padding-top: 20px ; color: rgba(0 , 0 , 0 , 0.5)\">A super quick crash course</div>\n",
     "        </div>\n",
     "    </div>\n",
-    "</div>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
+    "</div>\n",
+    "\n",
     "Seismo-Live: http://seismo-live.org\n",
     "\n",
     "##### Authors:\n",
@@ -28,14 +27,26 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "This notebook is a very quick introduction to Python and in particular its scientific ecosystem in case you have never seen it before. It furthermore grants a possibility to get to know the [IPython/Jupyter notebook](http://www.nature.com/news/interactive-notebooks-sharing-the-code-1.16261). [See here for the official documentation](http://nbviewer.jupyter.org/github/jupyter/notebook/blob/master/docs/source/examples/Notebook/Notebook%20Basics.ipynb) of the Jupyter notebook - a ton more information can be found online.\n",
     "\n",
     "\n",
-    "A lot of motivational writing on *Why Python?* is out there so we will not repeat it here and just condense it to a single sentence: **Python is a good and easy to learn, open-source, general purpose programming language that happens to be very good for many scientific tasks (due to its vast scientific ecosystem).**\n",
-    "\n",
-    "\n",
+    "A lot of motivational writing on *Why Python?* is out there so we will not repeat it here and just condense it to a single sentence: **Python is a good and easy to learn, open-source, general purpose programming language that happens to be very good for many scientific tasks (due to its vast scientific ecosystem).**"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "source": [
     "#### Quick Reference on How to Use This Notebook\n",
     "\n",
     "\n",
@@ -57,8 +68,17 @@
     "\n",
     "```bash\n",
     "$ ipython\n",
-    "```\n",
-    "\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "source": [
     "## Notebook Setup\n",
     "\n",
     "First things first: In many notebooks you will find a cell similar to the following one. **Always execute it!** They do a couple of things:\n",
@@ -71,13 +91,17 @@
     "\n",
     "This essentially makes the notebooks work under Python 2 and Python 3.\n",
     "\n",
-    "* Plots look quite a bit nicer (this is optional).\n"
+    "* Plots look quite a bit nicer (this is optional)."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# Plots now appear in the notebook.\n",
@@ -90,7 +114,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "---\n",
     "\n",
@@ -100,6 +128,8 @@
     "\n",
     "If you have any question regarding some specific Python functionality you can consult the official [Python documenation](http://docs.python.org/).\n",
     " \n",
+    "### Tutorials\n",
+    "\n",
     "Furthermore a large number of Python tutorials, introductions, and books are available online. Here are some examples for those interested in learning more.\n",
     " \n",
     "* [Learn Python The Hard Way](http://learnpythonthehardway.org/book/)\n",
@@ -107,12 +137,24 @@
     "* [The Official Python Tutorial](http://docs.python.org/2/tutorial/index.html)\n",
     "* [Think Python Book](http://www.greenteapress.com/thinkpython/thinkpython.html)\n",
     " \n",
+    "### Matlab\n",
+    "\n",
     "Some people might be used to Matlab - this helps:\n",
     " \n",
     "* [NumPy for Matlab Users Introdution](http://wiki.scipy.org/NumPy_for_Matlab_Users)\n",
-    "* [NumPy for Matlab Users Cheatsheet](http://mathesaurus.sourceforge.net/matlab-numpy.html)\n",
-    " \n",
-    " \n",
+    "* [NumPy for Matlab Users Cheatsheet](http://mathesaurus.sourceforge.net/matlab-numpy.html)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
+   "source": [
+    "### More\n",
+    "\n",
     "Additionally there is an abundance of resources introducing and teaching parts of the scientific Python ecosystem.\n",
     " \n",
     "* [NumPy Tutorial](http://wiki.scipy.org/Tentative_NumPy_Tutorial)\n",
@@ -133,7 +175,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "## Core Python Crash Course\n",
     "\n",
@@ -150,7 +196,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# Three basic types of numbers\n",
@@ -170,22 +220,25 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 2. Strings"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
+    "### 2. Strings\n",
+    "\n",
     "Just enclose something in single or double quotes and it will become a string. On Python 3 it defaults to unicode strings, e.g. non Latin alphabets and other symbols."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# You can use single or double quotes to create strings.\n",
@@ -210,7 +263,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "#### Exercise\n",
     "\n",
@@ -220,7 +277,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "name = \"kasper\"\n",
@@ -229,22 +290,25 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "### 3. Lists"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
+    "### 3. Lists\n",
+    "\n",
     "Python has two main collection types: List and dictionaries. The former is just an ordered collection of objects and is introduced here."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# List use square brackets and are simple ordered collections of things.\n",
@@ -266,7 +330,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "### 4. Dictionaries\n",
     "\n",
@@ -276,7 +344,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# Dictionaries have named fields and no inherent order. As is\n",
@@ -304,7 +376,10 @@
   {
    "cell_type": "markdown",
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "slideshow": {
+     "slide_type": "slide"
+    }
    },
    "source": [
     "### 5. Functions\n",
@@ -315,7 +390,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# Functions are defined using the def keyword.\n",
@@ -339,7 +418,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "### 6. Imports\n",
     "\n",
@@ -349,7 +432,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# Import anything, and use it with the dot accessor.\n",
@@ -369,7 +456,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "How to know what is available?\n",
     "\n",
@@ -380,7 +471,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "print(dir(math))"
@@ -388,7 +483,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "Typing the dot and the TAB will kick off tab-completion."
    ]
@@ -396,7 +495,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "math."
@@ -404,7 +507,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "In the IPython framework you can also use a question mark to view the documentation of modules and functions."
    ]
@@ -412,7 +519,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "math.cos?"
@@ -420,7 +531,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "### 7. Control Flow\n",
     "\n",
@@ -430,7 +545,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "temp = [\"a\", \"b\", \"c\"]\n",
@@ -447,7 +566,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# Useful to know is the range() function.\n",
@@ -457,15 +580,23 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
-    "The second crucial control flow structure are if/else conditional and they work the same as in any other language."
+    "The second crucial control flow structure are ***if/else*** conditional and they work the same as in any other language."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "# If/else works as expected.\n",
@@ -479,15 +610,27 @@
     "    print(\"wait what?\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
+   "source": [
+    "List comprehensions are a nice way to write compact loops. Make sure you understand this as it is very common in Python."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
-    "# List comprehensions are a nice way to write compact loops.\n",
-    "# Make sure you understand this as it is very common in Python.\n",
-    "\n",
     "a = list(range(10))\n",
     "print(a)\n",
     "b = [i for i in a if not i % 2]\n",
@@ -503,7 +646,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "### 8. Error Messages\n",
     "\n",
@@ -513,7 +660,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "def do_something(a, b): \n",
@@ -524,7 +675,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "## The Scientific Python Ecosystem\n",
     "\n",
@@ -539,7 +694,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "### 9. NumPy\n",
     "\n",
@@ -549,7 +708,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -571,7 +734,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "### 10. SciPy\n",
     "\n",
@@ -581,7 +748,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "from scipy.interpolate import interp1d\n",
@@ -595,7 +766,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "### 11. Matplotlib\n",
     "\n",
@@ -605,7 +780,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -619,7 +798,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "slide"
+    }
+   },
    "source": [
     "## Exercises\n",
     "\n",
@@ -637,7 +820,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -652,7 +839,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "#### 99 Bottles of Beer\n",
     "\n",
@@ -674,7 +865,12 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "scrolled": true,
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "print(\"99 bottles of beer on the wall, 99 bottles of beer.\")\n",
@@ -684,7 +880,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "#### Ceasar Cipher\n",
     "\n",
@@ -714,7 +914,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "outputs": [],
    "source": [
     "sentence = \"Pnrfne pvcure? V zhpu cersre Pnrfne fnynq!\"\n",
@@ -739,7 +943,11 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "subslide"
+    }
+   },
    "source": [
     "### Encoder ###\n",
     "Idea: Iterrate over all letters of a sentence and find the key (k) which contains the letter as value (v) in the code dictionary"
@@ -748,7 +956,11 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "slideshow": {
+     "slide_type": "fragment"
+    }
+   },
    "outputs": [],
    "source": [
     "sentence = \"Geophysics with Python is fun!\"\n",
@@ -763,16 +975,10 @@
     "\n",
     "print(result)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
+  "celltoolbar": "Slideshow",
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
@@ -793,4 +999,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 1
-}
\ No newline at end of file
+}