Crash_Code_Main.ipynb

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  "metadata": {
    "colab": {
      "name": "Crash_Code_Main.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "Uo8CBM9y0TFp",
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      "toc_visible": true,
      "authorship_tag": "ABX9TyMWBBCei31/PJA4EdlrpUHQ",
      "include_colab_link": true
    },
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/RobZuazua/CrashCode/blob/master/Crash_Code_Main.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "heading_collapsed": true,
        "id": "Uo8CBM9y0TFp"
      },
      "source": [
        "# How It Works"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "7QWELQ5VlDW2"
      },
      "source": [
        "Crash Code is an interview training program for software engineers.\n",
        "\n",
        "1. I clearly identify the [underlying technical concepts](#scrollTo=qTZX2XylbCAd) for each category of questions from Strings to Graphs.\n",
        "\n",
        "2. I create the [minimum set of coding questions](#scrollTo=QlJsQ5xpRHg5) that cover all identified technical concepts.\n",
        "\n",
        "3. **You effectively master the [underlying technical concepts](#scrollTo=qTZX2XylbCAd) by using this [minimum set of coding questions](#scrollTo=QlJsQ5xpRHg5).**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "heading_collapsed": true,
        "id": "qTZX2XylbCAd"
      },
      "source": [
        "# Part 1: Technical Concepts "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "AtoGZlcKXWHR"
      },
      "source": [
        "I identify the technical concepts by analyzing every question in the books *Cracking the Coding Interview*, *Elements  of the Programming Interview*, the top 100 most frequently asked questions on Leetcode, and Glassdoor. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "pUOC5nH5-0tY"
      },
      "source": [
        "## Strings"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "9MQcjsoPdHPG"
      },
      "source": [
        "[Full Analysis of every String question in CTCI, EPI, Leetcode.](https://github.com/RobZuazua/CrashCode/blob/master/Resources/Analysis/Strings.md)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "ks5_Wb1tkl2L"
      },
      "source": [
        "**Summary of analysis:** There are 7 concepts that can be used to solve the vast majority of String  questions."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "hidden": true,
        "id": "Gm_TijHValMA"
      },
      "source": [
        "'''\n",
        "1. Linear Time String Matching (Rabin Karp)\n",
        "2. Sliding Window (Fast/Slow, Fast/Catch Up)\n",
        "3. Two Pass\n",
        "4. Pre-fixing (Pre-sort, Pre-reverse, Pre-double)\n",
        "5. Work Backwards\n",
        "6. Two Pointer\n",
        "7. Additional Storage (Arrays, BitVectors)\n",
        "'''"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gbf2OJ1b4DR-",
        "outputId": "644a748d-7f7d-449e-d1d1-5ffb255a196d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        }
      },
      "source": [
        "#Run code to watch summary video\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('vFOIDvTkzBs')"
      ],
      "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/vFOIDvTkzBs\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f89c4c323c8>"
            ],
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\n"
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "53Yu9nNz4dZS",
        "outputId": "cd6d5473-f55b-421e-c053-adca9799587b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        }
      },
      "source": [
        "#Run code to watch Linear Time String Matching conceptual deep dive\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('V-Y3Aez4oJo')"
      ],
      "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/V-Y3Aez4oJo\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f89c4c6add8>"
            ],
            "image/jpeg": 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          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yJgKke5W4mW-",
        "outputId": "3339f075-b96d-4e92-e8dc-d1d75f3e6364",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321
        }
      },
      "source": [
        "#Run code to watch Sliding Window conceptual deep dive\n",
        "from IPython.display import YouTubeVideo\n",
        "YouTubeVideo('bAcPMWxnTvY')"
      ],
      "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/bAcPMWxnTvY\"\n",
              "            frameborder=\"0\"\n",
              "            allowfullscreen\n",
              "        ></iframe>\n",
              "        "
            ],
            "text/plain": [
              "<IPython.lib.display.YouTubeVideo at 0x7f89c4c6aa90>"
            ],
            "image/jpeg": 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6XT2LmA+k/uqXsX+ZP0r91S9g5wNTW+KxHWdXpbLBRaSsvSb08GjAG1PDSlHN2VG9s0pRir+LAyBpUpKK/aQk+Ecz99rGZB0UnSSd51U2rSUYxtbht5IhzorZTnLnKaXuS+ZgldpLa9CZwcZOMlZptNcGiq0dWO6nBd+aXxZXrHwj7KJVF9W6mmVSUObbTenl70Xhg6jipZUk7uOaUYuVvVTd34BERxdRbJtdyS+AeLq/ez9tlaNFzjUaatThnd96zKNl7RmBv9MrffVPbl+pSpWnO2ecpW2ZpOVvMzAEgAgAAoEgACSCwGYAIABAEggAdfRmJjTq9u/Vzi4TttUXv8D7fBZOrioZXGOkZK2seN1vPz0+z/8ATL/6WF+M/wCYx07fjv09HHQulJJNrjqeRh+jVUqvNJWvmcUranpdI1HGDtt3HBSkqVNuNaDqSV3qpa9xmOnjh6dw665qGisth42LVml487HrYrEyqVMzSR4+LqZpt8NDccu2IBpPDzjGM5QkoT9GTTSl3M05MwDXD0VOTTllSjKTdr6JXdlxAyB1OFOMIzyTnFtxUnJQTkrNqyu1tW8oq62KjT5aSk/eyjAHpuVSnGf1OGbg+32YynHdqr7L6HJ9OqK+VqH5Ixh70rhVY4Sq9VTlbi1Zeb0IWGe+dNfxp/C5nOTk7ybb4t3ZUiNuqp76y8ISfxsWpwouSTnOzaV8iSXPac4AtUg4ylF7Ytp+DL0Ks4v6v0pWWiTb4WLYt3nm9aMZeNtffcxjJppptNaprRoDtxbxNJpVJzs9jjPsPlppc5qlGeVVJp5ZbG3q+7fbmaYypK8Y3eXq6LtubUFr8TVRVaMpSi4uEEusv9W3GNlFp72lbTfuLi5HEoOzdnZbXbReJrg6anWpxl6LnFPuvqbUMdkUssIxeVqOVb3pdttmOCdqtN8H8gNaVR1FJWhHLCU4rIne2rWvK/kZRxFRu0Xq9EopJ+5E4B2rU77G8r7no/idvW/WulGKcU5KUlFRyRvbstbEuL2lVxV9EouTlO/aeZtL8K4iVLJTeeNpyfZTVnGK2ytzengzTo6CdVu/oRck+d7J9+t1zsbV6qkmsQkpNrJbWdOPPitmj12kTHFRoyne1rJXbbtFLmyzw/ZlKM4yUbOVs2ivbeka0KmRVKeePacWp2U4Nq/Fc9vIVVUkrSq08vBTio+SBjkNIehUX5X77fMzNKO2S4xl8L/IiMwXpqDTzSkuCUc1/ejSDpJprO3zjFrydyjA6Zf9tD++qfyRGMjFONklPXMlsXBPnxsWhVccOrWv1r2xT+ytlwrlLU6bk7RWu3gkuLe5Hbgl+zvFS6yo89/u42uuW1vwRi/qpKUe1TnF2vvi9sXbY0xhjGVNqVlaTXq9pG/SNOSrVZZWoucmnZ21d9pVxWWVSjOSyrtRbtJJtLatqu1wHSDfXVO+/g1cDRSjGGGU1eDnKrOPGOZRt5RfmVxtOo5SqSfWRb0qR1hbcvw92hTGPtRj6kIR91372zOjVnB3g2ny38mt4RthHaniv7lL/wCWBWngq04qUacmns01l3La/A6cRGMZYyMUlaNNNLSKlnjmtyzXMekp/XzS06tqEeSgsqt5XCueUGrXTV1dXVrq9rrxT8ip7HTEs9JT3xnGUlw62lGX8ym/E5+mMBHDypRi21KlGUm/vNVNLxQwxw5HlzWeW+W9tL7bXIO3H9inhqO+NPrJfmqdr+XIcQQABBIICKJJIJAoACAQAAAJUWwISPsugY2wlLj2n/mZ8lkd1GO1tLxPuMHSUKUYLRJJGe3X8f7VxC6yy56o83pG1JNQhaMvSS2PwOnG1nTWdbfiePiMZUqtdmyMculrkq1FBSa0zbFwOE3xb+sa4JeZjY6yOHV2oPWn0rTlKpmpylGrl6yLkrQSVl1fNbm92m88kF1NH/zca4aeWpBvZdX/ACvR+65kCI9HBSjGGIo1FGTTU6anLLDPF5XfVbn7jPPGni4yoxUkpQtFNtZrK6Teu29mKdJVcTRUvRq9W5fBrzTLYjD5FSxEIZV2XOF3eEk9tnrldtDTS6pwpxrZG3KUXTtJ00oXd9WpO7snwOGdGUbXWjV001JNXttR3SpSviVGLcKkc8Gk2n21KPja5inUp0Wm5QeeLiruMno7/BCpXEDoxDzRjUslJuUZW0TkrPN4p+45zKAAA1nrTg+DlH5r4spBRv2m0uUc3zRaPoTXOLXw+ZmBu+p3yqvwivmyrlS9Sb75pf0mQAtUcW+zFpcHLMXwztUg+aMi9L04/mXxAU6mVSSXaatm4Lel3l6cpVOw5u1pNJu6uk38jF7X4npU5y6ymrXo5Ek8ulsurvu1uVXFGd4KnFayldvfLgviZyg4uzVnwZph5KMnrbSSjLg2rJmrqQyRpzd7XtNXeW9rLmtvnoBjRpZrtu0Yq8nt8O8io46ZE0ubu37tDSKyudOadpWd466rY1xVmzN01uqRftJ/AiNMPlk4w6tSb35nF9/BaFU4xq3i7xU9Hxjf9C9JfVSUXFTk7SvJReTgr8X8DGcMujafdJS+BVROOVuPBtEwm4u627uXMviNWpetGL8dj96MiIGjq/VqFvtOV/C1jMAWU5JOKk1F7Vd2fgTneXLfs3vbnsuWp4ecleMJNcbaeZFSjKPpJL+JP4MC0q/YcIxUU7ZnduUrcXw5E1JdbUVlbNkjx3KPyMS9Cpkmp2vbVd+73lFsTPNVm9zk7d19C1KrCCUopurucrZYvilvZlGm2pSS0jbM+F3ZE06M5JuMJSS2tRbSAmFW0aitfOkr3/EnfnsNpYmnNqVSm5T0zNTyqduKs93A5QQdtLFqdSr1ztCsrSaV1BrWDS4KyXcdc69LFTkqlRU4RrzqJydr0ZPtJfiWVWXNnjgurrfGYh1atSq1bPJu3Bbl4KyMSAREgAAASBCLFSyKKAAgBImEbuxs0WQZqBokCrTTvrY0jqwLjCvSnL0VJN8kfZSjpdap7D4a99h9R0FjFKiqbfahpbiuJz7n26/jv0yx0JTeU46mHcPBHvKEbuTPC6W6Rg+xTen2pfJGZLW+rjxqsHdye1tmJec1sRRHRwRYmxooFXtLgq0QXsVZBo9aafqya8HqvemdCwbllvOXWzpupqrxy6tKUr8vgc9DXND1lp+Zar9PE3nX62lCLqODjFRyty6uSWxq2x94VhRqWVlBSbe/N8E0bqjTjWpuaywnDNllfsuzVnyzLyKUZSpPWP7SEbNSyvK2ndS3bLPxLYqpVkm5NOF0uy1OMeCT1t8wM8TplilFQV8tpqd+LbW/Z5HOSQRAAAWp71xTRUmLs0+YlGza4AQAABpQV6kPzIzCAhMnO7WvpwvobwxFRySzvVpX04m84VUqzcpWptJPLZS7Viq4QWdWT3sjM+JERcviIKNScVsUpJdyZS5pCDkpTbSS2ye9vdzbAzAvyJ05gaS1pRfqylF9z1XzMjVTioSirtycdqSSsVp1XG9ra7bxjL4ooinC7tmS5y0RapSlC2ZWT2Pan3NaMssS98Kb/wDHH5Gk5OFJxfpVGpOO6Mdztub+HeBXFaqgv3S/mkc501681ClFSaXVrRO29nZUpKVKrSSV6Uo9XprJqLc142v4BXnKjNxz5Xl420NMQk4UaitrFwlb1ov/AEuJZpVlG0rVFGMcsnaMklZZXufJmsa0+oq032XCUW0oqLs+zJOy/KA6Oo9ZGcG7KU6Sb4RWaTflFnPiMS6jVuzCOkIJ6RXzfF7zpwMrU3FbZdfbwotL+ZnFSpucowjtk0kBU6sbqqFS3p0kn+aDcPhFG9WFOWGqKlC/U1IXqfampJpvkrpWRWtVpywqy02nCo0rzzWzJPh+FgxwxtdXdldXe2yNMVQdKrOm9sJON+K3PxNMTRhTbp9p1VpJ3Sgpb1a13bZe51YihGpGnXnLLDqaSk0s0pTvKKSV1raD8gjzAb4vDdW4tSzQnHNCdrXWzZuad00YEAkgASCCQBJAAgAAaUlpcuRuIzG0WsSWjBtXtotr3BwaSbWj2BWVrbPI1o4lwalF2aKtGckSk8d+N6YnUgoR09Z8eR59m9pOV6FrEkLdUyllF9xZIk1iK2IZEnzM2yC8iJbASiKrGTTUltTTXejspU1GpWaV8tOVSnpfbaz8E/ccTOmcnkpVYtqUbwbWjTWz3P3CC9abqYeNSXp059Xey1i05K/NO/mVypUX1fazJdY76xV07ZeF0tdfAwq1pTtmk3bZfYhCpJRcYrbo2l2rcL8Bq6oQX6t79O9pEZVvkvBNkRVAns835IlTS2RXjqBEIOTtFNvglc1xKtKK+1kjm32ls/QpKtJq2Z24LReSKAAAAAACx00Zt0q6bb7MHq7/AG0c1y0ajSklskrPuun8ihTkk+1HNyu18DpoVr3hGlCz1eZtxSW93OMm5Bes455ZFaF9L8DqqqMKdPMrrKpRinbNJpNyb93gcJtGurJTgp5dE22nbhpuKGIhFZJRuozjms3drVp6+BiXrVXN3dtiSS0SS2JFCAAALRdmnwd+QnJybk3dt3b5kAC053y8oqJosVUvB5neDTj/AM37DEAaQcHJud1HV2ivcr7Db6SpTrOWinBxS22tbKv8qOUAdXWOm8O1rlWe3G8np5JF6MY06kasZxlTV3bNlqWta1uOvcctWpma0taMY+SsUKPSw2JpU0qKblTqStVk45ey1lWl3svm8Ec6jlhiKU2lJONucoyadvCTOUXA7KtalVeealGo/ScLOMnxs7WZOIxalhqFFXvCdVy5p2y/GXmcQBrtjLPhJx30qimvyT7Mv8yh5nGXpVnDOkk1OLg78HZ/FIoABBJAJIJQAAAVL01qUNKewsFzOZczmVHqU6coULXTU8s9OFrfoZTk3CMXsSdvMrhZ5qav9h5X+V7PmayptSXA569PzPHJctUozik5QlFPY5RaT7rk1KLc8q+1ovE26Rry6+vG8lFzkst3lai7LTwR0157McbTCTOvDOCp1ak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          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Fw0OB8aA5BQu"
      },
      "source": [
        "To intuitively learn these concepts, [you must use each one to solve a question.](#scrollTo=QlJsQ5xpRHg5) "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "C_iLOQtI_Ahe"
      },
      "source": [
        "## Linked Lists "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "JrO6WCD1_RNT"
      },
      "source": [
        "## Stacks and Queues"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "89YgG2eY_ZKz"
      },
      "source": [
        "## Binary Trees"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "nrjhZAaI_nXC"
      },
      "source": [
        "## Heaps"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "7ZlF9-EA_pPV"
      },
      "source": [
        "## Graphs"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "FHPEm4g2_rKx"
      },
      "source": [
        "## Hash Tables"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "HaqBkO84_ulS"
      },
      "source": [
        "## Searching"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "2o2-C1_q_wTD"
      },
      "source": [
        "## Sorting"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "hV1XAT33_yIi"
      },
      "source": [
        "## Recursion"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "lzoTBHVU_zvo"
      },
      "source": [
        "## Dynamic Programming"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "heading_collapsed": true,
        "id": "QlJsQ5xpRHg5"
      },
      "source": [
        "# Part 2: Coding Questions"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "CHweop7K0cfJ"
      },
      "source": [
        "**Strings:** [JavaScript](https://colab.research.google.com/github/RobZuazua/CrashCode/blob/master/Notebooks/JavaScript_Strings.ipynb), [Java](https://colab.research.google.com/github/RobZuazua/CrashCode/blob/master/Notebooks/Java_Strings.ipynb), [Python](https://colab.research.google.com/github/RobZuazua/CrashCode/blob/master/Notebooks/Python_Strings.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "DsSI4lyUKFHs"
      },
      "source": [
        "**Linked Lists:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "K4dnl0ftK8vt"
      },
      "source": [
        "**Stacks and Queues:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "R6yuQ2BVLRz2"
      },
      "source": [
        "**Binary Trees:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "eD7hcBjlLkY2"
      },
      "source": [
        "**Heaps:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "N2dS215qK2nK"
      },
      "source": [
        "**Graphs:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "e-_kW2MELqfW"
      },
      "source": [
        "**Hash Tables:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "X4Tz8E_oLoSb"
      },
      "source": [
        "**Searching:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "5CpPuV68Kyx1"
      },
      "source": [
        "**Sorting:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "7eWbLrVzK4kF"
      },
      "source": [
        "**Recursion:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "kFzW-xXAK6TG"
      },
      "source": [
        "**Dynamic Programming:** "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "heading_collapsed": true,
        "id": "zwpvhrYHQ3bk"
      },
      "source": [
        "# FAQ"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "HA7yVH19Xw7B"
      },
      "source": [
        "## How can I master the technical interview?\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "O-b21zWOX5VF"
      },
      "source": [
        "It comes down to you. Your level of sincerity, seriousness, and understanding ultimately determines how you will perform in your interviews.\n",
        "\n",
        "No \"5-step plan\" can replace your perceptions.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "Ic2pb26cYExC"
      },
      "source": [
        "## What must be understood?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "9HlZH33UYPMW"
      },
      "source": [
        "1. Intuitively understand the technical concepts within each category of questions.\n",
        "2. Be a proficient coder.\n",
        "3. Train your perceptions."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "Pnzg--qVYcaK"
      },
      "source": [
        "## What are the recurring concepts"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "6jO_gtxVYgx7"
      },
      "source": [
        "*   I identify every technical concept for each category of questions from Strings to Dynamic Programming by analayzing every question in the top 4 code prep resources (CTCI, EPI, top 100 Leetcode, and glassdoor.)\n",
        "\n",
        "* See [Part 1](#scrollTo=qTZX2XylbCAd) above for technical concepts\n",
        "\n",
        "* See [Part 2](#scrollTo=QlJsQ5xpRHg5) above for minimum set of questions that test all technical concepts"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "vYVfny4UY0Wa"
      },
      "source": [
        "## How do I most effectively understand these concepts?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "qm1nw5nrY6tj"
      },
      "source": [
        "*   To most effectively understand these concepts, you must use each of them to [solve a problem](#scrollTo=QlJsQ5xpRHg5) entirely on your own without using a solution.\n",
        "\n",
        "*   If you get stuck on any question for more than a few minutes, move on and come to my [daily office hours](https://discord.com/channels/748740514672803900/748740515117400066) where I will provide light guidance.\n",
        "\n",
        "*   Additionally each question has a hint that links the question to the concept. You may use the hint and watch the linked [youtube video](https://www.youtube.com/channel/UC4fdhO7egjaKfoJemwD2kIA) to gain understanding of the required concept."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "hH8GiIs5Y-S6"
      },
      "source": [
        "## Where else can I find you?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "hidden": true,
        "id": "z3L4RfN2ZDMG"
      },
      "source": [
        "*   Join our discord for FAQ and daily office hours from 5:00pm-5:15pm CST: https://discord.gg/e56GWrU\n",
        "\n",
        "*   Subscribe to our Youtube for more insights: https://www.youtube.com/channel/UC4fdhO7egjaKfoJemwD2kIA\n",
        "\n",
        "*   Subscribe to our mailing list for exclusive content: http://crashcode.training/\n",
        "\n",
        "*   Follow us on Twitter: https://twitter.com/RobZuazua"
      ]
    }
  ]
}