Introduction_to_computer_programming.ipynb

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  "metadata": {
    "colab": {
      "name": "Introduction_to_computer_programming.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "LhAWk7L9CTFS"
      ],
      "toc_visible": true,
      "authorship_tag": "ABX9TyNnK9aCEw/qtV9Ceo8fftgM",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/chefonc2979/introduction_to_programming/blob/main/Introduction_to_computer_programming.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jyom5v6wxrlV"
      },
      "source": [
        "# Introductions\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "*   Your name and rank\r\n",
        "*   Where do you work?\r\n",
        "*   What made you sign up for this course?\r\n",
        "*   What are you looking to gain from this class?\r\n",
        "\r\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BhEGx8NdaHtP"
      },
      "source": [
        "# Course Objective\n",
        "\n",
        "The goal of this course is to provide you with the foundational knowledge necessary to be familiar with the python programming language. This course also serves as an introduction to software development fundamentals and is starting point for future courses.\n",
        "\n",
        "Topics Covered\n",
        "- Abstraction\n",
        "- Variables\n",
        "- Arithmetic Operation\n",
        "- Strings\n",
        "- Control Flow\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GKGv22oGKCpb"
      },
      "source": [
        "# What is a programming language and the need for abstraction?\r\n",
        "\r\n",
        "An abstraction is a way — be it a piece of code like a library, or a language feature — that allows you to think of your code in a more human-friendly way than would be possible without it.\r\n",
        "\r\n",
        "An abstraction lets you picture systems as if you were actually manipulating it instead of the actual implementation, which is often complex and full of nasty details you don’t actually really care about.\r\n",
        "\r\n",
        "Programming language are high level abstractions that allow a user to write computer instructions using a human readable language."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "fCGBmSMxyK9P",
        "outputId": "f0dc6194-ecd2-4833-edc2-1523bbd96101"
      },
      "source": [
        "from IPython.display import YouTubeVideo\r\n",
        "YouTubeVideo('M41M9ATm49M')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"400\"\n",
              "            height=\"300\"\n",
              "            src=\"https://www.youtube.com/embed/M41M9ATm49M\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f5ca61d5890>"
            ],
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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ntuku2kKEMZI"
      },
      "source": [
        "# What is python?\r\n",
        "\r\n",
        "Python is a general-purpose coding language\r\n",
        "- Back end development\r\n",
        "-  Software development\r\n",
        "-  Data science/Machine Learning and Artificial Intelligence\r\n",
        "- Writing system scripts\r\n",
        "\r\n",
        "As of January 2021, Python ranks third in TIOBE’s index of most popular programming languages, behind C and Java\r\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        },
        "id": "I5cOoN5NTaCy",
        "outputId": "8804eb3b-2b27-4e39-f1c1-4775cdfc8190"
      },
      "source": [
        "from IPython.display import YouTubeVideo\r\n",
        "YouTubeVideo('Y8Tko2YC5hA')"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "        <iframe\n",
              "            width=\"400\"\n",
              "            height=\"300\"\n",
              "            src=\"https://www.youtube.com/embed/Y8Tko2YC5hA\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f1b93ebc210>"
            ],
            "image/jpeg": 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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hz2Y-vSQ-URQ"
      },
      "source": [
        "# Variables\r\n",
        "* A variable name must start with a letter or the underscore character.\r\n",
        "* A variable name cannot start with a number.\r\n",
        "* A variable name can only contain alpha-numeric characters and underscores (A-z, 0-9, and _ ).\r\n",
        "* Variable names are case-sensitive (name, Name and NAME are three different variables).\r\n",
        "* The reserved words(keywords) cannot be used naming the variable."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eqY-bpJB-fhK"
      },
      "source": [
        "# Comments\r\n",
        "Comments are used to document your codebase for other developers or for you to reference at later points. Guaranteed you will forget what a piece of code does if you don't use it often\r\n",
        "In python there are two ways two ways to add comments to your code\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "1.   For single line comments use a hashtag #\r\n",
        "2.   Triple quotes for multiline comments ''' '''\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "*   Comments are not a part of your codebase and don't change it's functionality\r\n",
        "*   Anything encapsulated by the comments will run at runtime\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "\r\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Bra0fDg6nnW7"
      },
      "source": [
        "## Strings"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dhCaP660yiGq"
      },
      "source": [
        "Assign your first name to the variable first_name"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WgRopro8yyBj"
      },
      "source": [
        "Assign your first name to the variable last_name"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ob8ou1bO0K0S"
      },
      "source": [
        "Print out your full name"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yTHjB-06zDY9"
      },
      "source": [
        "How would you determine how long your first name is? Your last name?\r\n",
        "\r\n",
        "How would you use this in a real application?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AlTZkaTQ3Jkg"
      },
      "source": [
        "What happens if I attempt to add two numbers together but they're strings?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lW9m4ohQ31Ok"
      },
      "source": [
        "Lets redo the first three excercises but this time use the built in input function to capture the users name and display a welcome message"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_5H-cHMWKmKq"
      },
      "source": [
        "# Arithmetic Operations\r\n",
        "\r\n",
        "Arithmetic operations work the same in programming as they normally would. 1 + 1 still equals 2. \r\n",
        "\r\n",
        "*   Addition denoted by the +\r\n",
        "*   Subtraction denoted by the -\r\n",
        "*   Multiplication denoted by the *\r\n",
        "*   Division denoted by the /\r\n",
        "*   Modulo denoted by the % (Returns the remainder from division)\r\n",
        "\r\n",
        "\r\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tkjpR9z31nZW"
      },
      "source": [
        "Convert a the temperature to Farenheight given an input of temperature in celsius\r\n",
        "\r\n",
        "*`(0°C × 9/5) + 32 = 32°F`*"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D12LL1j24zPM"
      },
      "source": [
        "Given a circle radius of 15. Calculate the area, circumference and diameter of that circle\r\n",
        "\r\n",
        "* A = Pi * Radius Squared\r\n",
        "* C = 2 * PI * Radius\r\n",
        "* D = 2 * R"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qPPek24FkUmX"
      },
      "source": [
        "# Control Flow\n",
        "\n",
        "In computer science, control flow (or flow of control) is the order in which individual statements, instructions or function calls of an imperative program are executed or evaluated.\n",
        "\n",
        "Within an imperative programming language, a control flow statement is a statement that results in a choice being made as to which of two or more paths to follow.\n",
        "\n",
        "A set of statements is in turn generally structured as a block, which in addition to grouping, also defines a lexical scope."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cw4uPIk0vyzP"
      },
      "source": [
        "## Boolean Logic\n",
        "\n",
        "A data type that has one of two possible values (usually denoted true and false) which is intended to represent the two truth values of logic and Boolean algebra.\n",
        "\n",
        "The Boolean data type is primarily associated with conditional statements, which allow different actions by changing control flow depending on whether a programmer-specified Boolean condition evaluates to true or false.\n",
        "\n",
        "\n",
        "\n",
        "*   and\n",
        "*   not\n",
        "*   or\n",
        "*   ==\n",
        "*   !=\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UDJchKU7gZ1T"
      },
      "source": [
        "Is A > B ?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8LP6n_ZHg93F"
      },
      "source": [
        "Is A == a?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vJWg-xLaitir"
      },
      "source": [
        "Is a > A?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "q5ZVsE5WgnCO"
      },
      "source": [
        "What is the value of True and True?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-ps_iGsXgw6S"
      },
      "source": [
        "What is the value of True and False?\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2Kod76zsjIis"
      },
      "source": [
        "True or False? not True and not False"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yOpislC_hTDi"
      },
      "source": [
        "True or False? It is not true and not false or true and not true?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "291vVXpyjVNS"
      },
      "source": [
        "# What's the point and why do we need to know this?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zVchKkIcoDuN"
      },
      "source": [
        "## If Statements\n",
        "\n",
        "In computer science, conditional statements, conditional expressions and conditional constructs are features of a programming language, which perform different computations or actions depending on whether a programmer-specified boolean condition evaluates to true or false.\n",
        "\n",
        "Password Checking Excercise"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1xO7cPeJBAvX"
      },
      "source": [
        ""
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "97cKzkcLoKsw"
      },
      "source": [
        "## Else Statement"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rrKQJhL6Be6q"
      },
      "source": [
        ""
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WN5ZFvfGoPrU"
      },
      "source": [
        "## Elif"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_rOiPti8CKYB"
      },
      "source": [
        ""
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OJn9n_arZmIJ"
      },
      "source": [
        "# Modulus/For Loop/List of Numbers Excercise (Print)\n",
        "# Modulus/For Loop/List of Numbers Excercise (Accumulation)\n",
        "\n"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LhAWk7L9CTFS"
      },
      "source": [
        "# Errors\r\n",
        "\r\n",
        "\r\n",
        "\r\n",
        "1.   Syntax Errors (Definitely your fault)\r\n",
        "2.   Logical Errors (Exceptions) (More than likely also your fault)\r\n",
        "\r\n",
        "\r\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OpU0METkhapN"
      },
      "source": [
        "1guess = 10"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pSiqkZvYhihO"
      },
      "source": [
        "class = false"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qvh1iyfviMtq"
      },
      "source": [
        "print('4' + 8)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Shs4DgRnibVY"
      },
      "source": [
        "print(10 / 0)"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}