diff --git a/Upper&Lower.ipynb b/Upper&Lower.ipynb
new file mode 100644
index 0000000..5881430
--- /dev/null
+++ b/Upper&Lower.ipynb
@@ -0,0 +1,305 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyNIPZXRxw5cmK7YVNFfjVK9",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/JUHYUNCHOI/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/Upper%26Lower.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 문제   "
+      ],
+      "metadata": {
+        "id": "RrI1b3dteklM"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### **upper & lower**\n",
+        "\n",
+        "```python\n",
+        ">>> 'Julia'.upper() # 모두 대문자로 만들어 주는 함수입니다.\n",
+        "JULIA\n",
+        ">>> 'Julia'.lower() # 모두 소문자로 만들어 주는 함수입니다.\n",
+        "julia\n",
+        "```\n",
+        "\n",
+        "**사용 예시1**)\n",
+        "\n",
+        "사용자로부터 입력받은 이름 중에 Julia가 있는지 확인하는 프로그램을 완성하고자 합니다.\n",
+        "\n",
+        "사용자가 우리가 원하는대로 Julia로 입력을 할까요?\n",
+        "\n",
+        "고객들은 각기 다른 방식으로 입력할 것입니다.\n",
+        "\n",
+        "Julia, JULIA, julia 등등\n",
+        "\n",
+        "그런데 아래 코드와 같이 구현한다면 JULIA, julia이름은 찾아지지 않을 것입니다.\n",
+        "\n",
+        "```python\n",
+        "name_list = ['Julia', 'Girin', 'Jane', 'JULIA', 'julia']\n",
+        "\n",
+        "for name in name_list:\n",
+        "    if name == 'Julia':\n",
+        "        print(f'{name}을 찾았음')\n",
+        "\n",
+        "'''\n",
+        "결과:\n",
+        "Julia을 찾았음\n",
+        "'''\n",
+        "```\n",
+        "\n",
+        "이를 방지하기 위해 upper() 또는 lower()을 사용 할 수 있습니다.\n",
+        "\n",
+        "```python\n",
+        "name_list = ['Julia', 'Girin', 'Jane', 'JULIA', 'julia']\n",
+        "\n",
+        "for name in name_list:\n",
+        "    if name.upper() == 'JULIA':\n",
+        "        print(f'{name}을 찾았음')\n",
+        "\n",
+        "'''\n",
+        "Julia을 찾았음\n",
+        "JULIA을 찾았음\n",
+        "julia을 찾았음\n",
+        "'''\n",
+        "```\n",
+        "\n",
+        "```python\n",
+        "name_list = ['Julia', 'Girin', 'Jane', 'JULIA', 'julia']\n",
+        "\n",
+        "for name in name_list:\n",
+        "    if name.lower() == 'julia':\n",
+        "        print(f'{name}을 찾았음')\n",
+        "\n",
+        "'''\n",
+        "Julia을 찾았음\n",
+        "JULIA을 찾았음\n",
+        "julia을 찾았음\n",
+        "'''\n",
+        "```\n",
+        "\n",
+        "**사용 예시 2**)\n",
+        "\n",
+        "기린 학교 학생들의 이름을 학교 사이트에 이쁘게 꾸미고 싶습니다. 그런데 학생들 이름이 대문자 소문자 각기 뒤죽박죽 정리되어 있습니다.\n",
+        "\n",
+        "name_list = [’girin’, ‘julia’, ‘James’, ‘paul’, ‘Alex’, ‘Jamie’]\n",
+        "\n",
+        "이름 그대로 사이트에 올리게 되면 너무 못생길 것 같아 첫 자는 대문자 나머지는 소문자로 바꾸고 싶습니다.\n",
+        "\n",
+        "이럴 경우 upper(), lower()을 사용하면 좋습니다.\n",
+        "\n",
+        "```python\n",
+        "name_list = ['girin', 'julia', 'James', 'paul', 'Alex', 'Jamie']\n",
+        "\n",
+        "for name in name_list:\n",
+        "    print(f'{name[0].upper()}{name[1:].lower()}', end = '  ')\n",
+        "             --------------   ----------------\n",
+        "             첫번째는 대문자    나머지는 소문자\n",
+        "'''\n",
+        "결과:\n",
+        "Girin  Julia  James  Paul  Alex  Jamie\n",
+        "\n",
+        "```\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "6t2zB2lGemaU"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 문제    "
+      ],
+      "metadata": {
+        "id": "M_WboZUkeqOd"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1. 다음 코드의 결과는 무엇 일까요?\n",
+        "\n",
+        "```python\n",
+        ">>> var = 'Julia'\n",
+        ">>> var.upper()\n",
+        "```\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "Ac7HMnwievpv"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "답)   \n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "11EU_dCOfAlR"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "2. 다음 코드의 결과는 무엇 일까요?\n",
+        "\n",
+        "```python\n",
+        ">>> var = 'Julia'\n",
+        ">>> var.lower()\n",
+        "```\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "kuE1aIjjeygY"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "답)   \n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "7KzJffuYfEUB"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "3. 다음 학생들 중 julia가 몇 명인지 계산하는 프로그램을 만들려고 합니다. (ㄱ)에 들어갈 코드를 완성 하세요.\n",
+        "\n",
+        "```python\n",
+        "name_list = ['julia', 'girin', 'haha', 'james', 'Julia']\n",
+        "\n",
+        "count = 0\n",
+        "for name in name_list:\n",
+        "    if (ㄱ) == 'JULIA' :\n",
+        "         count += 1\n",
+        "\n",
+        "print(count)\n",
+        "```\n",
+        "\n",
+        "```python\n",
+        "결과:\n",
+        "2\n",
+        "```\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "CzNeg0iOe1Yy"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "답)   \n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "1C2RbeZ7fJM6"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "4. 다음과 같은 결과가 나오기 위해 (ㄱ)에 들어갈 코드를 완성 하세요.\n",
+        "\n",
+        "```python\n",
+        "name_list = ['julia', 'girin', 'haha', 'james', 'Julia']\n",
+        "\n",
+        "for name in name_list:\n",
+        "    print(ㄱ, end=' ')\n",
+        "```\n",
+        "\n",
+        "```python\n",
+        "결과:\n",
+        "JULIA GIRIN HAHA JAMES JULIA\n",
+        "```\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "JJY0ICe2e65M"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "답)   \n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "NwP8vabcfVIy"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "5. 다음과 같은 결과가 나오기 위해 (ㄱ)에 들어갈 코드를 완성 하세요.\n",
+        "\n",
+        "```python\n",
+        "name_list = ['julia', 'girin', 'haha', 'james', 'Julia']\n",
+        "\n",
+        "for name in name_list:\n",
+        "    print(ㄱ, end=' ')\n",
+        "```\n",
+        "\n",
+        "```python\n",
+        "결과:\n",
+        "Julia Girin Haha James Julia\n",
+        "```"
+      ],
+      "metadata": {
+        "id": "ZLO62rgre8js"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "답)    \n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "HtOB3u8yfcnC"
+      }
+    }
+  ]
+}
\ No newline at end of file
diff --git "a/Upper&Lower\354\210\231\354\240\234.ipynb" "b/Upper&Lower\354\210\231\354\240\234.ipynb"
new file mode 100644
index 0000000..a3b74ac
--- /dev/null
+++ "b/Upper&Lower\354\210\231\354\240\234.ipynb"
@@ -0,0 +1,232 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyPkAXbboIY9z/4/bsHQT9IB",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/JUHYUNCHOI/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/Upper%26Lower%EC%88%99%EC%A0%9C.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 설명"
+      ],
+      "metadata": {
+        "id": "oi4gzCRZzqcg"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "**시퀀스 자료형의 일부분을 잘라내는 것을 슬라이싱이라고 합니다.**\n",
+        "\n",
+        "**[시작하는 인덱스(포함): 끝나는 인덱스(불포함)]**\n",
+        "\n",
+        "\n",
+        "문자열(s**tring)**\n",
+        "\n",
+        "![스크린샷 2023-07-04 오후 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)\n",
+        "\n",
+        "```python\n",
+        ">>> s = 'julia'\n",
+        ">>> s[1:3]   # 인덱스 1부터 2까지 자름\n",
+        "'ul'\n",
+        "```\n",
+        "\n",
+        "**생략하여 사용하는 방법:**\n",
+        "\n",
+        "- **시퀀스자료형[**시작하는 인덱스(포함**): ]**\n",
+        "\n",
+        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)\n",
+        "\n",
+        "\n",
+        "\n",
+        "```python\n",
+        ">>> s = 'julia'\n",
+        ">>> s[3:]   # 인덱스 3부터 끝까지\n",
+        "'ia'\n",
+        "```\n",
+        "\n",
+        "시퀀스자료형[ : 끝나는 인덱스(불포함)]\n",
+        "\n",
+        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)\n",
+        "\n",
+        "```python\n",
+        ">>> s = 'julia'\n",
+        ">>> s[:3]   # 인덱스 0부터 2까지\n",
+        "'jul'\n",
+        "```"
+      ],
+      "metadata": {
+        "id": "XzHAZtamzsjx"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 문제"
+      ],
+      "metadata": {
+        "id": "sePkv2PF3sAk"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1. 다음 기린학교의 학생들 명단입니다. 모두 대문자로 출력하도록 코드를 완성하세요.    \n",
+        "\n",
+        "students = ['julia', 'girin', 'james', 'Conan']\n",
+        "\n",
+        "결과:\n",
+        "JULIA\n",
+        "GIRIN\n",
+        "JAMES\n",
+        "CONAN"
+      ],
+      "metadata": {
+        "id": "oIMgX8Z53-_F"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "uOwEjaswziQu"
+      },
+      "outputs": [],
+      "source": [
+        "# 다음 코드를 완성하세요.\n",
+        "\n",
+        "students = ['julia', 'girin', 'james', 'Conan']"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "2. 다음 기린학교의 학생들 명단입니다. 모두 소문자로 출력하도록 코드를 완성하세요.\n",
+        "students = ['julia', 'girin, 'james', 'Conan']\n",
+        "\n",
+        "결과: julia girin james conam"
+      ],
+      "metadata": {
+        "id": "cxjSAj_q4e_v"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# 다음 코드를 완성하세요.\n",
+        "\n",
+        "students = ['julia', 'girin', 'james', 'Conan']"
+      ],
+      "metadata": {
+        "id": "LEQ_LCxw4tiz"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "3. 다음 기린학교의 학생들 명단입니다. 첫글자만 대문자로 출력하도록 코드를 완성하세요.\n",
+        "\n",
+        "students = ['julia', 'girin', 'james', 'Conan'].  \n",
+        "결과:   \n",
+        "Julia  \n",
+        "Girin  \n",
+        "James   \n",
+        "Conan   "
+      ],
+      "metadata": {
+        "id": "jET4H0JQ4yxs"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# 답\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "YMJlnNK25VAm"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "아래 문제는 배운 내용과 관련 없는 문제입니다. 3급 시험문제를 대비한 문제이니 잘 풀어보세요^^ 어렵습니다. 잘 고민해 보는 시간을 가졌으면 좋겠습니다.   \n",
+        "\n",
+        "### 문제 11\n",
+        "\n",
+        "k에 3씩 더하여 크기가 작은 순으로 n개 출력하려 합니다.   \n",
+        "\n",
+        "두 자연수 k와 n을 전달받아, k에 3씩 더하여 크기가 작은 순서대로 n개 출력해 주세요.   \n",
+        "\n",
+        "\n",
+        "### 입력 설명\n",
+        "두 자연수 k와 n이 주어집니다.\n",
+        "\n",
+        "* k는 2 이상 100 이하인 자연수입니다.\n",
+        "* n은 1 이상 100 이하인 자연수입니다.\n",
+        "\n",
+        "### 출력 설명\n",
+        "k에 3씩 더하여 크기가 작은 순서대로 n개 만큼 출력해주세요.\n",
+        "\n",
+        "### 예제\n",
+        "| k | n | result |\n",
+        "| :--: | :--: | :-- |\n",
+        "| 7 | 5 | 7 10 13 16 19 |\n",
+        "| 3 | 4 | 3 6 9 12 |\n",
+        "\n",
+        "### 예제 설명\n",
+        "\n",
+        "<예제 #1>\n",
+        "7에서부터 3씩 더한 5개를 나열하면 7 10 13 16 19입니다.\n",
+        "\n",
+        "<예제 #2>\n",
+        "3에서부터 3씩 더한 4개를 나열하면 3 6 9 12입니다.\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "XefaQmh_7nh8"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# 답)\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "dc73kvTHVO2i"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
diff --git "a/\353\254\270\354\236\220\354\227\264\353\271\204\352\265\220.ipynb" "b/\353\254\270\354\236\220\354\227\264\353\271\204\352\265\220.ipynb"
new file mode 100644
index 0000000..bed9567
--- /dev/null
+++ "b/\353\254\270\354\236\220\354\227\264\353\271\204\352\265\220.ipynb"
@@ -0,0 +1,271 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyO/GvmS4oUixHXIVlvxlJEz",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/JUHYUNCHOI/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/%EB%AC%B8%EC%9E%90%EC%97%B4%EB%B9%84%EA%B5%90.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "컴퓨터에서 모든 데이터는 숫자로 표현됩니다. 즉, 문자열도 글자가 아닌 숫자로 표현되지요. 예를 들면 문자 'A'는 65로, 'B'는 66으로 표현합니다. 그리고 각 문자들은 정해진 숫자가 있는데, 이를 아스키(ASCII)문자라고 합니다.\n",
+        "\n",
+        "\n",
+        "아래 아스키 문자를 관찰하다보면 'A'에서 'B'로 갈수록 숫자가 커지고, 'a'에서 'b'로 갈 수록 숫자가 커집니다. 이를 이용해서 알파벳 순서를 알애낼 수가 있습니다.   \n",
+        "\n",
+        "'A'와 'Z'중 어느 수가 더 클까요? 아스키코드를 보면 'A'는 65이고 'Z'는 90입니다.\n",
+        "     \n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "DT78gTiRbMg2"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### 아스키(ASCII)문자   \n",
+        "\n",
+        "![image.png](data:image/png;base64,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)"
+      ],
+      "metadata": {
+        "id": "wTvd7Weddue0"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "그렇다면 아래 코드의 결과는 True일까요 False일까요?\n",
+        "\n",
+        "```\n",
+        "'A' < 'Z'\n",
+        "```\n",
+        "\n",
+        "네 맞습니다. 이 코드의 결과는 True입니다.   \n",
+        "\n",
+        "이제 여러분들이 아래 코드의 각 결과를 생각해 보세요.   \n",
+        "```\n",
+        "'B' > 'D'\n",
+        "'F' < 'Z'\n",
+        "'d' > 'e'\n",
+        "'g' > 'a'\n",
+        "'k' < 'o'\n",
+        "```\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "---------\n",
+        "\n",
+        "\n",
+        "정답을 알아볼까요?\n",
+        "```\n",
+        "'B' > 'D'   # False\n",
+        "'F' < 'Z'   # True   \n",
+        "'d' > 'e'   # False\n",
+        "'g' > 'a'   # True\n",
+        "'k' < 'o'   # True\n",
+        "```\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "i4vDwflLd1eZ"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "이를 이용하여 문자열을 비교하는 코드를 작성하려고 합니다.   "
+      ],
+      "metadata": {
+        "id": "giXX4v-ze8P6"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 문제1"
+      ],
+      "metadata": {
+        "id": "WqHdhL-1jOR6"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "다음 각 줄의 결과는 True일까요? False일까요?\n",
+        "\n",
+        "\n",
+        "\n",
+        "1. 'd' < 'p'\n",
+        "2. 'apple' < 'zoo'\n",
+        "3. 'white' > 'flower'\n",
+        "4. 'D' < 'd'\n",
+        "5. 't' == 'T'"
+      ],
+      "metadata": {
+        "id": "d54t66AejMNG"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "답을 이곳에 입력하시오.\n",
+        "\n",
+        "1.         \n",
+        "2.         \n",
+        "3.          \n",
+        "4.          \n",
+        "5.           \n"
+      ],
+      "metadata": {
+        "id": "QTV4TA6Oj3So"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 문제2"
+      ],
+      "metadata": {
+        "id": "rv33g-DpfC3J"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "두개의 문자를 입력받아 먼저 나오는 단어를 출력하세요.   \n",
+        "\n",
+        "   입력예제:   \n",
+        "       'a'   \n",
+        "       'z'   \n",
+        "   출력예제:   \n",
+        "       'a'   "
+      ],
+      "metadata": {
+        "id": "WBebSh8mfKcj"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "# 답을 이곳이 입력하시오.\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "a41EgrYTfhju"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "# 문제3"
+      ],
+      "metadata": {
+        "id": "q_TElF6MhrAk"
+      }
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "위 문제는 같은 소문자끼리 비교하는 문제였습니다. 그렇다면 소문자 'a'와 대문자 'A'를 비교하였을 경우는 어떨까요?   'a'는 ASCII 문자에서 97이고 'A'는 65입니다. 그래서 'a'와 'A'를 다음과 같이 비교하였을 경우 그 값은 False입니다.   \n",
+        "\n",
+        "```\n",
+        "'A' > 'a'\n",
+        "```\n",
+        "('A' > 'a'는 컴퓨터에서 65 > 97로 바뀜)   \n",
+        "\n",
+        "그래서 'apple'과 'Zoo' 중 어느 단어가 사전에서 먼저 나오냐고 아래와 같이 묻는다면 결과는 'Zoo'가 될 것 입니다.   \n",
+        "\n",
+        "```\n",
+        "if 'apple' < 'Zoo':\n",
+        "    print('apple')\n",
+        "else:\n",
+        "    print('Zoo')\n",
+        "```\n",
+        "\n",
+        "결과:\n",
+        "```\n",
+        "Zoo\n",
+        "```\n",
+        "\n",
+        "(Zoo의 Z가 대문자이기 때문에 소문자인 a보다 숫자가 작음)\n",
+        "\n",
+        "대문자와 소문자의 숫자가 다르기 때문에 생기는 문제를 해결하기 위해 우리는 모두 대문자 또는 소문자로 바꾸어 비교해 줍니다.   \n",
+        "대문자로 바꾸는 명령어는 문자열.upper()이고 소문자로 바꾸는 명령어는 문자열.lower()입니다.   \n",
+        "\n",
+        "\n",
+        "```\n",
+        "if 'apple'.upper() < 'Zoo'.upper():\n",
+        "    print('apple')\n",
+        "else:\n",
+        "    print('Zoo')\n",
+        "```\n",
+        "\n",
+        "**다음 입력받은 두 단어에 upper()를 사용하여 사전에서 먼저 나오는 단어를 출력하세요. **\n",
+        "\n",
+        "입력예제:   \n",
+        "```\n",
+        "apple\n",
+        "Zoo\n",
+        "```\n",
+        "\n",
+        "출력예제:   \n",
+        "```\n",
+        "apple\n",
+        "```\n"
+      ],
+      "metadata": {
+        "id": "F9cRZzEsfhE9"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = input()\n",
+        "b = input()\n",
+        "\n",
+        "\n",
+        "# 다음 코드를 완성하시오.\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "8Z6KJ_y1yPYz"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
diff --git "a/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260(input).ipynb" "b/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260(input).ipynb"
new file mode 100644
index 0000000..8d631c5
--- /dev/null
+++ "b/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260(input).ipynb"
@@ -0,0 +1,106 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyN6ITmE69CUJVAXnObLGd/D",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/JUHYUNCHOI/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/%EC%8B%9C%ED%80%80%EC%8A%A4%EB%8D%B0%EC%9D%B4%ED%84%B0(input).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1. 다음 문자열을 입력받아 거꾸로 출력하는 프로그램을 완성하시오.\n",
+        "\n",
+        "   입력예제:\n",
+        "   abcdefg\n",
+        "\n",
+        "   출력예제:\n",
+        "   gfedcba"
+      ],
+      "metadata": {
+        "id": "XlIQ4LICVKyV"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "nWfikc6sVKQB"
+      },
+      "outputs": [],
+      "source": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "2. 다음 문자열을 입력받아 앞 두 글자만 출력하는 프로그램을 완성하시오.\n",
+        "\n",
+        "   입력예제:\n",
+        "   abcdefg\n",
+        "\n",
+        "   출력예제:\n",
+        "   ab"
+      ],
+      "metadata": {
+        "id": "hUg1nSsJVdFC"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "KSMu-TCfV36Q"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "3. 팰린드롬(Palindrom)이란 앞뒤로 똑같은 단어를 말합니다. 기러기, 토마토도 팰린드롬의 하나이지요.\n",
+        "\n",
+        "    영어단어 abccba, abcba도 팰린드롬입니다.\n",
+        "\n",
+        "    입력받은 문자열을 팰린드롬으로 만드는 프로젝트를 완성하세요. 예를들어, abc를 입력받으면 abccba를 출력합니다.\n",
+        "\n",
+        "    입력예제:\n",
+        "    배고파\n",
+        "\n",
+        "    출력예제:\n",
+        "    배고파파고배"
+      ],
+      "metadata": {
+        "id": "wqAj2M0zWZjq"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "CbBEbmTMWrEh"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
diff --git "a/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260\355\203\200\354\236\205.ipynb" "b/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260\355\203\200\354\236\205.ipynb"
new file mode 100644
index 0000000..d248c36
--- /dev/null
+++ "b/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260\355\203\200\354\236\205.ipynb"
@@ -0,0 +1,258 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyPwhCemII7AnoytwSGRxiCL",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/JUHYUNCHOI/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/%EC%8B%9C%ED%80%80%EC%8A%A4%EB%8D%B0%EC%9D%B4%ED%84%B0%ED%83%80%EC%9E%85.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1. 다음 문자열에서 6을 출력하세요.    "
+      ],
+      "metadata": {
+        "id": "apN1d060nf37"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "vVbs5Aq3eGg0"
+      },
+      "outputs": [],
+      "source": [
+        "a = '1234567'"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "2. 다음 리스트에서 사과를 출력하세요."
+      ],
+      "metadata": {
+        "id": "fxedNsj3nsT7"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = ['바나나','포도', '사과', '파인애플', '딸기']\n"
+      ],
+      "metadata": {
+        "id": "Ci7IueIbgXJr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "3. 다음 코드의 결과는 무엇인가요?   \n",
+        "\n",
+        "```\n",
+        "a = '안녕하세요. 오늘은 날씨가 좋군요.'\n",
+        "\n",
+        "print(a[5])  \n",
+        "```\n"
+      ],
+      "metadata": {
+        "id": "Pl9-E9xyn45d"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "3MHBirZ6oREr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "4. 다음 코드의 결과는 무엇인가요?   \n",
+        "\n",
+        "```\n",
+        "a = '안녕하세요. 오늘은 날씨가 좋군요.'\n",
+        "\n",
+        "for i in range(2,5):\n",
+        "   print(a[i], end = '')\n",
+        "```"
+      ],
+      "metadata": {
+        "id": "XkrVNaEToR9O"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "QDqYgEE3orsz"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "5. 다음 9부터 1까지 거꾸로 출력하는 프로그램을 완성하세요.\n",
+        "\n",
+        "   결과:   \n",
+        "   987654321   "
+      ],
+      "metadata": {
+        "id": "BWWeGRjjosWC"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = '123456789'\n"
+      ],
+      "metadata": {
+        "id": "3HmaNyoBo7Hj"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "6. 다음 리스트를 거꾸로 출력하는 프로그램을 완성하세요.   \n",
+        "   \n",
+        "   결과:   \n",
+        "   딸기 파인애플 사과 포도 바나나"
+      ],
+      "metadata": {
+        "id": "V7VScGpwpEl_"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = ['바나나','포도', '사과', '파인애플', '딸기']"
+      ],
+      "metadata": {
+        "id": "6uVX9iC4pKB1"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "7. 다음 리스트에서 포도, 사과, 파인애플만 출력하는 프로그램을 완성하세요.     \n",
+        "\n",
+        "   결과:   \n",
+        "   포도 사과 파인애플   "
+      ],
+      "metadata": {
+        "id": "LiVa4e7Kpioy"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = ['바나나','포도', '사과', '파인애플', '딸기']\n"
+      ],
+      "metadata": {
+        "id": "DfIA3JqTqBtA"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "8. 다음 리스트에서 파인애플, 사과만 출력하는 프로그램을 완성하세요.\n",
+        "\n",
+        "   결과:   \n",
+        "   파인애플, 사과"
+      ],
+      "metadata": {
+        "id": "uw-Oxk3sqFM6"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = ['바나나','포도', '사과', '파인애플', '딸기']"
+      ],
+      "metadata": {
+        "id": "4DaV-702qK9Q"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "9. 다음 문자열에서 오늘은만 출력하세요.   \n",
+        "\n",
+        "   결과:   \n",
+        "   오늘만   "
+      ],
+      "metadata": {
+        "id": "eiDpHPCRqSuV"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = '안녕하세요. 오늘은 날씨가 좋군요.'\n"
+      ],
+      "metadata": {
+        "id": "Tywra9GDqrQh"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "10. 다음 리스트에서 짝수 위치에 있는 아이템만 출력하세요.   \n",
+        "\n",
+        "    결과:   \n",
+        "    포도 파인애플 산딸기   "
+      ],
+      "metadata": {
+        "id": "PdVC1iqQq7s4"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = ['바나나','포도', '사과', '파인애플', '딸기', '산딸기']\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "-P755fh9lo-u"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
diff --git "a/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260\355\203\200\354\236\2052.ipynb" "b/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260\355\203\200\354\236\2052.ipynb"
new file mode 100644
index 0000000..e1d1c1f
--- /dev/null
+++ "b/\354\213\234\355\200\200\354\212\244\353\215\260\354\235\264\355\204\260\355\203\200\354\236\2052.ipynb"
@@ -0,0 +1,258 @@
+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "authorship_tag": "ABX9TyOxJmEKanXyqcRP/qd/0CqF",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/JUHYUNCHOI/Python-Data-Analysis-and-Image-Processing-Tutorial/blob/master/%EC%8B%9C%ED%80%80%EC%8A%A4%EB%8D%B0%EC%9D%B4%ED%84%B0%ED%83%80%EC%9E%852.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "1. 다음 문자열에서 '다'을 출력하세요.    "
+      ],
+      "metadata": {
+        "id": "apN1d060nf37"
+      }
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "vVbs5Aq3eGg0"
+      },
+      "outputs": [],
+      "source": [
+        "a = '가나다라마바사'"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "2. 다음 리스트에서 6을 출력하세요."
+      ],
+      "metadata": {
+        "id": "fxedNsj3nsT7"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = [1, 3, 4, 5, 6, 7, 8]\n"
+      ],
+      "metadata": {
+        "id": "Ci7IueIbgXJr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "3. 다음 코드의 결과는 무엇인가요?   \n",
+        "\n",
+        "```\n",
+        "a = '저의 이름은 기린입니다.'\n",
+        "\n",
+        "print(a[5])  \n",
+        "```\n"
+      ],
+      "metadata": {
+        "id": "Pl9-E9xyn45d"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "3MHBirZ6oREr"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "4. 다음 코드의 결과는 무엇인가요?   \n",
+        "\n",
+        "```\n",
+        "a = '저의 이름은 기린입니다.'\n",
+        "\n",
+        "for i in range(2,5):\n",
+        "   print(a[i], end = '')\n",
+        "```"
+      ],
+      "metadata": {
+        "id": "XkrVNaEToR9O"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "QDqYgEE3orsz"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "5. 다음과 같이 입력값을 거꾸로 출력하는 프로그램을 완성하세요.\n",
+        "\n",
+        "   결과:   \n",
+        "   사바마라다나가  "
+      ],
+      "metadata": {
+        "id": "BWWeGRjjosWC"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = '가나다라마바사'\n"
+      ],
+      "metadata": {
+        "id": "3HmaNyoBo7Hj"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "6. 다음 리스트를 거꾸로 출력하는 프로그램을 완성하세요.   \n",
+        "   \n",
+        "   결과:   \n",
+        "   7 6 5 4 3 2 1"
+      ],
+      "metadata": {
+        "id": "V7VScGpwpEl_"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = [1,2,3,4,5,6,7]"
+      ],
+      "metadata": {
+        "id": "6uVX9iC4pKB1"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "7. 다음 리스트에서 2, 3, 4 출력하는 프로그램을 완성하세요.     \n",
+        "\n",
+        "   결과:   \n",
+        "   2 3 4     "
+      ],
+      "metadata": {
+        "id": "LiVa4e7Kpioy"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = [1, 2, 3, 4, 5, 6, 7]\n"
+      ],
+      "metadata": {
+        "id": "DfIA3JqTqBtA"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "8. 다음 리스트에서 5, 4만 출력하는 프로그램을 완성하세요.\n",
+        "\n",
+        "   결과:   \n",
+        "   5, 4"
+      ],
+      "metadata": {
+        "id": "uw-Oxk3sqFM6"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = [1, 2, 3, 4, 5, 6, 7]\n"
+      ],
+      "metadata": {
+        "id": "4DaV-702qK9Q"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "9. 다음 문자열에서 '다라마'만 출력하세요.   \n",
+        "\n",
+        "   결과:   \n",
+        "   다라마   "
+      ],
+      "metadata": {
+        "id": "eiDpHPCRqSuV"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = '가나다라마바사'\n"
+      ],
+      "metadata": {
+        "id": "Tywra9GDqrQh"
+      },
+      "execution_count": null,
+      "outputs": []
+    },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "10. 다음 리스트에서 짝수 위치에 있는 숫자만 출력하세요.   \n",
+        "\n",
+        "    결과:   \n",
+        "    3 5 7  "
+      ],
+      "metadata": {
+        "id": "PdVC1iqQq7s4"
+      }
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "a = [2, 3, 4, 5, 6, 7, 8]\n",
+        "\n"
+      ],
+      "metadata": {
+        "id": "-P755fh9lo-u"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}
\ No newline at end of file
