{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "# Introduction\n",
    "#### CS 65: Introduction to Computer Science I"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## About me\n",
    "\n",
    "Eric Manley\n",
    "\n",
    "Email: <a href=\"mailto:eric.manley@drake.edu\">eric.manley@drake.edu</a>\n",
    "\n",
    "MS Teams: <a href=\"https://teams.microsoft.com/l/chat/0/0?users=eric.manley@drake.edu\">send me a message on MS Teams</a>\n",
    "\n",
    "Phone: 515-271-2177\n",
    "\n",
    "Office: Collier-Scripps 327\n",
    "\n",
    "Website: https://manley.wp.drake.edu/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Course Description\n",
    "\n",
    "An introduction to the field of computer science is provided emphasizing problem solving using a high-level programming language. Algorithms, basic data representation, language control structures, debugging, and program verification will be discussed. Objects will be introduced, used, and created."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "* problem solving\n",
    "* high-level programming language (Python)\n",
    "* *__algorithms__*\n",
    "* data representation\n",
    "* control structures\n",
    "* debugging\n",
    "* verification\n",
    "* objects\n",
    "\n",
    "**Computer Science:** not just computers or programming - these are tools"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Learning Objectives\n",
    "\n",
    "* Understand the fundamentals of CS\n",
    "* Design, document, develop, test, and debug algorithms in the Python programming language\n",
    "* Recognize common data structures and how to use them to efficiently solve problems\n",
    "* Solve computational problems by breaking them into manageable parts and synthesizing them into a coherent whole"
   ]
  },
  {
   "attachments": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Textbook\n",
    "\n",
    "![think_python2_medium.jpg](attachment:think_python2_medium.jpg)\n",
    "\n",
    "_Think Python 2nd Edition_ by Allen B. Downey (free, open source)\n",
    "\n",
    "https://greenteapress.com/wp/think-python-2e/\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "cell_style": "center",
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "Web-based version: https://greenteapress.com/thinkpython2/html/index.html\n",
    "\n",
    "PDF: http://greenteapress.com/thinkpython2/thinkpython2.pdf\n",
    "\n",
    "Buy hard-copy: http://amzn.to/1WmXPCx \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Programming Topics\n",
    "\n",
    "* Variables\n",
    "* Output\n",
    "* Expressions and Operators\n",
    "* Comments\n",
    "* Types and Type Conversion\n",
    "* Input\n",
    "* Calling Built-in Functions and Using Modules\n",
    "* Conditional Statements\n",
    "* Lists\n",
    "* Looping Statements (while and for loops)\n",
    "* Working with Files, including CSV and JSON file formats\n",
    "* Function Definitions, Arguments, and Return Values\n",
    "* Scope\n",
    "* String Processing\n",
    "* Tuples\n",
    "* Dictionaries\n",
    "* Introduction to Classes and Objects\n",
    "* Graphical User Interfaces\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Grading\n",
    "\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "cell_style": "split"
   },
   "source": [
    "Graded item | Weight in Final Grade \n",
    "-------------|-------------\n",
    "Programming Labs | 50% \n",
    "Content Quizzes | 30% \n",
    "Final Project | 20% "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "cell_style": "split"
   },
   "source": [
    "Course grade % | Letter Grade\n",
    "-------------|-------------\n",
    "$92.0 - 100.0$ | A \n",
    "$90.0 - 91.9$ | A- \n",
    "$88.0 - 89.9$ | B+ \n",
    "$82.0 - 87.9$ | B \n",
    "$80.0 - 81.9$ | B- \n",
    "$78.0- 79.9$ | C+ \n",
    "$72.0 - 77.9$ | C \n",
    "$70.0 - 71.9$ | C- \n",
    "$60.0 - 69.9$ | D \n",
    "$0.0 - 60.0$ | F "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Programming Labs\n",
    "\n",
    "* Short programming assignments\n",
    "* A few exercises with each lecture/topic\n",
    "* Practice programming concepts\n",
    "* Checks that you are becoming proficient with _algorithmic problem solving_ as well as Python _programming constructs_\n",
    "* Start in class, finish outside of class\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### Programming lab challenge exercises\n",
    "* Labs culminate in challenge exercise that you _turn in for credit_\n",
    "    - 4 points: full credit (passes automated tests, uses programming concepts as directed)\n",
    "    - 3 points: significant progress on challenge exercise\n",
    "    - 2 points: significant progress on non-challenge exercises (turn in whatever you have)\n",
    "    - 1 point: at least something is attempted\n",
    "    \n",
    "* Submit using a tool called codePost - more on that later"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### Collaboration on labs\n",
    "\n",
    "* You can work _with_ other students - both actively engaged in problem solving\n",
    "* _may not_ copy code\n",
    "* Everyone writes up and submits individually, say who you worked with in comments of code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Content Quizzes\n",
    "\n",
    "* Blackboard\n",
    "* Mulitple choice, fill-in-the blank, short answer, etc.\n",
    "* Open book, note, etc.\n",
    "* Not timed, you'll have a day or two to complete\n",
    "* Checks that you're keeping up with topics covered by video lectures and readings\n",
    "* Individual - no collaborating"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "subslide"
    }
   },
   "source": [
    "#### tentative quiz schedule\n",
    "\n",
    "* Quiz 1: Friday, September 17th\n",
    "* Quiz 2: Friday, October 8th\n",
    "* Quiz 3: Friday, October 29th\n",
    "* Quiz 4: Friday, November 19th\n",
    "* Quiz 5: Friday, December 10th\n",
    "\n",
    "They may not all be worth the same amount"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Final Project\n",
    "* Creative project\n",
    "* Integrate many concepts - show that you know how to put them all together\n",
    "* Show you can break something big into smaller pieces\n",
    "* Individual\n",
    "* Due Tuesday, December 14th (finals week)\n",
    "\n",
    "We will not meet during finals week\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Tutoring Lab\n",
    "\n",
    "There are tutors for this course - you are encouraged to use them!\n",
    "\n",
    "https://www.drake.edu/access-success/tutoringpeerassistance/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Office Hours\n",
    "\n",
    "__Tentative schedule__\n",
    "* MWF 12:45-1:45pm\n",
    "* MW 3:30-4:30pm\n",
    "\n",
    "__Drop-in__\n",
    "* In person: Collier-Scripps 327\n",
    "* Online: <a href=\"https://teams.microsoft.com/l/chat/0/0?users=eric.manley@drake.edu\">Send me a message on MS Teams</a> (preferred for quicker response) or email \n",
    "\n",
    "__Reserve a time__\n",
    "* https://calendly.com/eric-manley/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Remote Work\n",
    "\n",
    "* I'll communicate if we need to switch to online-only whether temporary or permanent\n",
    "* If you need to work remotely, just stay caught up on Blackboard\n",
    "    - video lectures from Summer 2021 are in the Panopto tool on Blackboard\n",
    "    - I may add videos from the in-person course, but they probably won't be as good\n",
    "* Need extensions? Ask me\n",
    "* Need to change to remote for a longer time? Please communicate with me about it"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Disability Accomodation\n",
    "\n",
    "Coordinate them with Student Disability Services\n",
    "* Michelle Laughlin\n",
    "* michelle.laughlin@drake.edu\n",
    "* (515)271-1835\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hideOutput": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Collaboration Policy and Academic Integrity\n",
    "\n",
    "You _may_ work together on labs\n",
    "\n",
    "You _may not_ work together on projects and quizzes\n",
    "\n",
    "When working together, say who you worked with in the code comments\n",
    "\n",
    "When taking code from somewhere on the Internet, cite it in your comments and provide a link\n",
    "\n",
    "May not look at code from previous students in the course\n",
    "\n",
    "May not search the Internet for _solutions_\n",
    "\n",
    "First violation: 0 on that thing\n",
    "\n",
    "Second violation: F for the course"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Let's talk about the course Blackboard page"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Before you come to class next time...\n",
    "\n",
    "Download and install Thonny: https://thonny.org/\n",
    "\n",
    "It's an _Integrated Development Environment_ for beginners - a tool for writing and running your code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## With the rest of our time today\n",
    "\n",
    "You can write Python code in an _interactive mode_ right in your browser: https://www.python.org/shell/\n",
    "\n",
    "Try running the following lines\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello, world!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "2+3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = \"hello\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "minutes_per_day = 60*24"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"The number of minutes in a day is\",minutes_per_day)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Exercise:__ Calculate and print the number of seconds in a year."
   ]
  }
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