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      "<div align=\"center\">\n",
      "<h1>Data, the Humanist's New Best Friend<br/>*Course Description*</h1>\n",
      "</div>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Course Supervisor**: <NAME>\u00e1rez<br/>\n",
      "**E-mail**: [<EMAIL>](mailto:<EMAIL>)<br/>\n",
      "**Instructor**: <NAME><br/>\n",
      "**E-mail**: [<EMAIL>](mailto:<EMAIL>)<br/>\n",
      "**Office**: UC 114<br/>\n",
      "**Office Hours**: Mondays 3:00pm-5:00pm<br/>\n",
      "**Meets**: Fall 2014, Mondays 12:30pm-2:30pm, Wednesdays 12:30pm-2:30pm<br/>\n",
      "**Room**: AB 148<br/>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Description"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This course is a hands-on and pragmatic introduction to computer tools and theoretical aspects of the new use of data by humanists of different disciplines. Furthermore, it will serve as an introduction to the techniques and methods used today to make sense of data from a Humanities point of view.\n",
      "\n",
      "In that sense, *Data, the Humanist's New Best Friend* is divided into three blocks (plus one extra block that covers a programming review):\n",
      "\n",
      "- Data Mining, explaining the past and predicting the future by means of data analysis.\n",
      "- Text Analysis, producing valuable information from text sources.\n",
      "- Networks Science, understanding complex structures by analyzing the relationships among their entities."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Justification"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We find computers and software in almost any field of study, from STEM disciplines (Science, Technology, Engineering and Mathematics), to Education and Arts. In the Humanities, for example, there is even a whole sub-discipline (or a discipline by itself, depending on who you ask) that tries to find answers to new and old questions by digital means. This approach, referred to as Digital Humanities, usually borrows methods from the sciences to analyze their own data, and produce interpretations and conclusions.\n",
      "\n",
      "Data is today the new currency: is easy to produce and easy to collect; although the analysis still remains as one of the most complex steps in the workflow of any analytical proccess. This tendency of focusing solely into the data as the Holy Grail that solves everything, yet arguable, is producing important advances in the theoretical framework of the Data Science. Which is later translated into methods and tools with the enough madurity to be extrapolated and used in other fields. One of those is the Digital Humanities.\n",
      "\n",
      "Being able to manipulate, manage and get value out of data is not only an in demand skill for researchers, but also a future-proof recipe for digital humanists in a field that is getting familiar with fast-paced introduction of innovative products to manage data.\n",
      "\n",
      "Unfortunately, in the Humanities, data may come in a variety of formats: from mere CSV files or tables, to books, blog posts, tweets, or even network data from social or literary networks. Obviously, critical thinking and content related courses are completely necessary, but if we do not teach courses on new tools and methods, our next generation of students will graduate with limited knowledge of what can be done and how. It is not only about tools, software or applications, but, rather, it is to give students the skills they need to adapt to the changing environment of research. We do not know if Python will be widely used in 5 or 10 years, but we have to prepare our students to go beyond the next trend and apply their knowledge to the newest and coolest tool.\n",
      "\n",
      "This course is focused in three main areas that I have surmised as the most important: data mining, text analysis, and network science. The election is not casual, is based on two principles:\n",
      "\n",
      "* Most common topics in conferences such as Digital Humanities (the biggest world conference in the field), Canadian Society of Digital Humanities, or the Summer Institute Innitiative.\n",
      "* More demanded skills in Digital Humanities job postings."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Philosophy of Teaching"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I have a strong background in Computer Sciences. When I first enrolled in Computer Engineering I was very disappointed because I did not see a computer until three months into my program. All my colleagues felt the same way. And when we finally were in front of a computer, we were limited to only what the teacher wanted us to do. My first years in college were so frustrating for a guy who wanted to be roboticist, with only studying mathematics, physics and more mathematics. After finishing my Bachelor\u2019s and Master\u2019s degrees, I decided that, if I ever had the chance to teach a computer science related course, that would be intended as a learning by doing course.\n",
      "\n",
      "After several years, I understood the point of acquiring all the mathematical knowledge they had taught us, but even so, I found that it is not the best way to teach computer sciences. People need participate and experience through trial and error. For this reason I believe the teacher must play the role of a \"facilitator\" of learning, and not the role of the \"expert\" that only gives information in one direction. I am sure that teaching is an amazing and practical way of learning for teachers, and, therefore, there must be a proper environment in the class for students to freely share and express their ideas.\n",
      "\n",
      "Personally, I believe that one successful way to reach students is by \u201cspeaking\u201d their own language. Keeping myself up to date with all the trends and technologies they usually use, may mean students feel more comfortable and confident in class. On the other hand, making the content more appealing, as well as challenging is a plus, so as to catch the interest and attention of the students.\n",
      "\n",
      "Positive attitude is a must have for a teacher, and passion for what she or he teaches is very important as well. The teacher, in this case me, must be able to involve students so they can take an active part in the learning process. Daily small activities are intended to achieve this, promoting pair or group work whenever possible."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Methodology"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "As stated previously, the content is divided into 1+3 blocks of content: a programming review to get the hands on Python and the IPython Notebook, including the setup and in-class activities; data mining and analysis,  with activities and one assignment; text analysis and processing, with activities and one assignment; and graphs and networks analysis, also with activities and one assignment.\n",
      "\n",
      "The course will employ the format of micro-lectures, as it has been [demonstrated](http://www.sciencemag.org/content/332/6031/862.full?ijkey=GMW4zTHNMM1Tc&keytype=ref&siteid=sci) that students from classes using this format outperform those from traditional lecture classes. The students are also report being happier and more engaged. Classes will be split to two hours on Mondays, and two more on Wednesdays. Officially Wednesdays are one class hour plus one lab hour, but there will not be distinction between them.\n",
      "\n",
      "All micro-lectures will be delivered in the form of interactive, downloadable, and executable IPython Notebooks, made available on the [course website](http://nbviewer.ipython.org/github/versae/data_for_humanists/). Students must come to class prepared as they are expected to take an active part in the lecture and activities. After teacher explained concepts from the recommended readings, and in order to ensure active participation in class, students will be assigned activities during the class to be solved, either in small groups or in pairs, in a short period of time. While students are working in their activities, teacher will help with doubts, and finally will show the answer to the class.\n",
      "\n",
      "Moreover, after each of the main blocks of contents, students will have to complete assignments to put into practice concepts learned in class.  Overall, this course is a highly interactive course that will allow students to actively learn by doing.\n",
      "\n",
      "The use of electronic devices is highly recommended, as long as they can be used to run and experiment with the examples and activities from the micro-lectures."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Classes. Attendance (10%) and Participation (15%)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notebooks with the content, related exercises and the readings, will be available for the students on the [course website](http://nbviewer.ipython.org/github/versae/data_for_humanists/). The readings in the course calendar are suggested to aid the student, but they are not required to understand the lectures (although they are good research material). Every day, to promote active learning, small activities will be proposed for the students to solve, when students are supposed to work in pairs or small groups. For this reason the room should be a laboratory, as some students may not have a laptop.\n",
      "\n",
      "After finalizing each block, an assignment that covers as many concepts of the lectures as possible is proposed. Then students have more than one week to complete it, individually or in pairs."
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "IPython Notebooks"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "***Goal***: Deliver the content in an interactive way, but according to the needs and interests of the students, while keeping students engaged.\n",
      "\n",
      "In order to make the lectures more practical, the notebooks are pieces of code that run in the browser, so students can interact with them. Notebooks might be long. The idea behind having long Notebooks is to cover as much content as possible, so depending on the interest and needs of the students, lectures can go deep in one direction or another. In this way, we can have students more engaged with the lectures at the time that they actively participate in the class by exposing their interests."
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Activities"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "***Goal***: Guarantee that students are understanding the lectures.\n",
      "\n",
      "Activities will be proposed daily, usually several times a day. These activities are conceived to put into practice the concepts of the lecture at the time it is explained. These activities will be evaluated only as participation. All activities, after students are given time to solve them, will be explained to the class by the teacher or by volunteers. The last of the activities may be left as a home activity, and be solved by the next class day."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Assignments (36%)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There will be three different assignments based on the three main practical blocks of content (excluding review), each of which will cover a real world case using Humanities data. All assignments need to be written as IPython Notebooks. Each assignment must have 5 different parts, evaluated as follows: getting and cleaning the data (2%), summarizing the data and extracting relevant information (2%), visualizing the information (2%), and stating the conclussions (2%). Furthermore, there is two more aspects to take into account: presentation (2%), and correctness, functionality and adequacy of code (2%). All assignments will be marked from 0 (not sent) to 100.\n",
      "\n",
      "* **Data Mining (12%)**. This assignment aims to validate the acquired knowledge of the student in terms of data wrangling, converting or mapping from one *raw* form into another format that allows for more convenient consumption of the data with the help of the libraries and methods explained during the class. This will include further data visualization, data aggregation, and a statistical measures. The assignment will include a Notebook template that students must fill in. In the template, there will be excerpts of code already done and others to be filled in. The dataset to be used will be also included, although students can use their own data sets if that is their aim. A proposal for this assignment is already accessible as the Notebook [Assignment 1](../Assignment1.ipynb).\n",
      "  \n",
      "  \n",
      "* **Text Analysis (12%)**. In this assignment the student is expected to extract information and run different analysis over the text *[Moby Dick; or The Whale](http://www.gutenberg.org/cache/epub/2701/pg2701.txt)*, by <NAME>, from [Project Gutenberg](http://www.gutenberg.org/), in order to come to conclusions without reading the book. Other text sources, web sources or coporas can be used by the student after teacher approval. The template for the assignment will include guidelines and functions prototypes for the student to run measures such as frequency distributions, word and letter counts, richness, average length per sentence and paragraph, entity extraction and grammatical structures. Visualizations are also required. Conclusions for this assignment needs to address the topic of the book and the writing style of the author for the book. The proposal will be aviable as the Notebook Assignment 2.\n",
      "\n",
      "\n",
      "* **Network Science (12%)**. Unlike previous assignments, the dataset is not given. Instead, the student is expected to use a graph of her or him choice from [Koblenz University repositories](http://konect.uni-koblenz.de/networks/). The graph can also be created by the student, although a minimum of 100 nodes and 300 relationships are mandatory in both cases. Smaller but more dense graphs can used upon aprroval by the teacher. The template for this assignment will be made availabel as the Notebook Assignment 3. It will include some guides on the expected analysis to run (degree, density, diameter, betweenness, average shortest path, closeness, clustering, modularity, and page rank), but this time there will not be code, and almost everything will need to be written by the student."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Final Project (39%)"
     ]
    },
    {
     "cell_type": "markdown",<commit_msg>Update course description<commit_after>{
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  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "<div align=\"center\">\n",
      "<h1>Data, the Humanist's New Best Friend<br/>*Course Description*</h1>\n",
      "</div>"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "**Course Supervisor**: <NAME>\u00e1rez<br/>\n",
      "**E-mail**: [<EMAIL>](mailto:<EMAIL>)<br/>\n",
      "**Instructor**: <NAME><br/>\n",
      "**E-mail**: [<EMAIL>](mailto:<EMAIL>)<br/>\n",
      "**Office**: UC 114<br/>\n",
      "**Office Hours**: Mondays 3:00pm-5:00pm<br/>\n",
      "**Meets**: Fall 2014, Mondays 12:30pm-2:30pm, Wednesdays 12:30pm-2:30pm<br/>\n",
      "**Room**: AB 148<br/>"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Description"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This course is a hands-on and pragmatic introduction to computer tools and theoretical aspects of the new use of data by humanists of different disciplines. Furthermore, it will serve as an introduction to the techniques and methods used today to make sense of data from a Humanities point of view.\n",
      "\n",
      "In that sense, *Data, the Humanist's New Best Friend* is divided into three blocks (plus one extra block that covers a programming review):\n",
      "\n",
      "- Data Mining, explaining the past and predicting the future by means of data analysis.\n",
      "- Text Analysis, producing valuable information from text sources.\n",
      "- Networks Science, understanding complex structures by analyzing the relationships among their entities."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Justification"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We find computers and software in almost any field of study, from STEM disciplines (Science, Technology, Engineering and Mathematics), to Education and Arts. In the Humanities, for example, there is even a whole sub-discipline (or a discipline by itself, depending on who you ask) that tries to find answers to new and old questions by digital means. This approach, referred to as Digital Humanities, usually borrows methods from the sciences to analyze their own data, and produce interpretations and conclusions.\n",
      "\n",
      "Data is today the new currency: is easy to produce and easy to collect; although the analysis still remains as one of the most complex steps in the workflow of any analytical proccess. This tendency of focusing solely into the data as the Holy Grail that solves everything, yet arguable, is producing important advances in the theoretical framework of the Data Science. Which is later translated into methods and tools with the enough madurity to be extrapolated and used in other fields. One of those is the Digital Humanities.\n",
      "\n",
      "Being able to manipulate, manage and get value out of data is not only an in demand skill for researchers, but also a future-proof recipe for digital humanists in a field that is getting familiar with fast-paced introduction of innovative products to manage data.\n",
      "\n",
      "Unfortunately, in the Humanities, data may come in a variety of formats: from mere CSV files or tables, to books, blog posts, tweets, or even network data from social or literary networks. Obviously, critical thinking and content related courses are completely necessary, but if we do not teach courses on new tools and methods, our next generation of students will graduate with limited knowledge of what can be done and how. It is not only about tools, software or applications, but, rather, it is to give students the skills they need to adapt to the changing environment of research. We do not know if Python will be widely used in 5 or 10 years, but we have to prepare our students to go beyond the next trend and apply their knowledge to the newest and coolest tool.\n",
      "\n",
      "This course is focused in three main areas that I have surmised as the most important: data mining, text analysis, and network science. The election is not casual, is based on two principles:\n",
      "\n",
      "* Most common topics in conferences such as Digital Humanities (the biggest world conference in the field), Canadian Society of Digital Humanities, or the Summer Institute Innitiative.\n",
      "* More demanded skills in Digital Humanities job postings."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Philosophy of Teaching"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "I have a strong background in Computer Sciences. When I first enrolled in Computer Engineering I was very disappointed because I did not see a computer until three months into my program. All my colleagues felt the same way. And when we finally were in front of a computer, we were limited to only what the teacher wanted us to do. My first years in college were so frustrating for a guy who wanted to be roboticist, with only studying mathematics, physics and more mathematics. After finishing my Bachelor\u2019s and Master\u2019s degrees, I decided that, if I ever had the chance to teach a computer science related course, that would be intended as a learning by doing course.\n",
      "\n",
      "After several years, I understood the point of acquiring all the mathematical knowledge they had taught us, but even so, I found that it is not the best way to teach computer sciences. People need participate and experience through trial and error. For this reason I believe the teacher must play the role of a \"facilitator\" of learning, and not the role of the \"expert\" that only gives information in one direction. I am sure that teaching is an amazing and practical way of learning for teachers, and, therefore, there must be a proper environment in the class for students to freely share and express their ideas.\n",
      "\n",
      "Personally, I believe that one successful way to reach students is by \u201cspeaking\u201d their own language. Keeping myself up to date with all the trends and technologies they usually use, may mean students feel more comfortable and confident in class. On the other hand, making the content more appealing, as well as challenging is a plus, so as to catch the interest and attention of the students.\n",
      "\n",
      "Positive attitude is a must have for a teacher, and passion for what she or he teaches is very important as well. The process of teaching, interestingly, is in itself an amazing method of learning for an educator. For that reason, there must be an appropriate educational environment for students to freely share and express their ideas. The teacher is there to encourage the procurement of knowledge for the student, but they are also responsible for the instruction that comes from these exchanges. Daily small activities are intended to achieve this, promoting pair or group work whenever possible."
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "Methodology"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "As stated previously, the content is divided into 1+3 blocks of content: a programming review to get the hands on Python and the IPython Notebook, including the setup and in-class activities; data mining and analysis,  with activities and one assignment; text analysis and processing, with activities and one assignment; and graphs and networks analysis, also with activities and one assignment.\n",
      "\n",
      "The course will employ the format of micro-lectures, as it has been [demonstrated](http://www.sciencemag.org/content/332/6031/862.full?ijkey=GMW4zTHNMM1Tc&keytype=ref&siteid=sci) that students from classes using this format outperform those from traditional lecture classes. The students are also report being happier and more engaged. Classes will be split to two hours on Mondays, and two more on Wednesdays. Officially Wednesdays are one class hour plus one lab hour, but since class time is lab time too, there will be no change in room as we will occupy a computer lab.\n",
      "\n",
      "All micro-lectures will be delivered in the form of interactive, downloadable, and executable IPython Notebooks, made available on the [course website](http://nbviewer.ipython.org/github/versae/data_for_humanists/). Students must come to class prepared as they are expected to take an active part in the lecture and activities. After teacher explained concepts from the recommended readings, and in order to ensure active participation in class, students will be assigned activities during the class to be solved, either in small groups or in pairs, in a short period of time. While students are working in their activities, teacher will help with doubts, and finally will show the answer to the class.\n",
      "\n",
      "Moreover, after each of the main blocks of contents, students will have to complete assignments to put into practice concepts learned in class.  Overall, this course is a highly interactive course that will allow students to actively learn by doing.\n",
      "\n",
      "The use of electronic devices is highly recommended, as long as they can be used to run and experiment with the examples and activities from the micro-lectures."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Classes. Attendance (10%) and Participation (15%)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Notebooks with the content, related exercises and the readings, will be available for the students on the [course website](http://nbviewer.ipython.org/github/versae/data_for_humanists/). The readings in the course calendar are suggested to aid the student, but they are not required to understand the lectures (although they are good research material). Every day, to promote active learning, small activities will be proposed for the students to solve, when students are supposed to work in pairs or small groups. For this reason the room should be a laboratory, as some students may not have a laptop.\n",
      "\n",
      "After finalizing each block, an assignment that covers as many concepts of the lectures as possible is proposed. Then students have more than one week to complete it, individually or in pairs."
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "IPython Notebooks"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "***Goal***: Deliver the content in an interactive way, but according to the needs and interests of the students, while keeping students engaged.\n",
      "\n",
      "In order to make the lectures more practical, the notebooks are pieces of code that run in the browser, so students can interact with them. Notebooks might be long. The idea behind having long Notebooks is to cover as much content as possible, so depending on the interest and needs of the students, lectures can go deep in one direction or another. In this way, we can have students more engaged with the lectures at the time that they actively participate in the class by exposing their interests."
     ]
    },
    {
     "cell_type": "heading",
     "level": 4,
     "metadata": {},
     "source": [
      "Activities"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "***Goal***: Guarantee that students are understanding the lectures.\n",
      "\n",
      "Activities will be proposed daily, usually several times a day. These activities are conceived to put into practice the concepts of the lecture at the time it is explained. These activities will be evaluated only as participation. All activities, after students are given time to solve them, will be explained to the class by the teacher or by volunteers. The last of the activities may be left as a home activity, and be solved by the next class day."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Assignments (36%)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There will be three different assignments based on the three main practical blocks of content (excluding review), each of which will cover a real world case using Humanities data. All assignments need to be written as IPython Notebooks. Each assignment must have 5 different parts, evaluated as follows: getting and cleaning the data (2%), summarizing the data and extracting relevant information (2%), visualizing the information (2%), and stating the conclussions (2%). Furthermore, there is two more aspects to take into account: presentation (2%), and correctness, functionality and adequacy of code (2%). All assignments will be marked from 0 (not sent) to 100.\n",
      "\n",
      "* **Data Mining (12%)**. This assignment aims to validate the acquired knowledge of the student in terms of data wrangling, converting or mapping from one *raw* form into another format that allows for more convenient consumption of the data with the help of the libraries and methods explained during the class. This will include further data visualization, data aggregation, and a statistical measures. The assignment will include a Notebook template that students must fill in. In the template, there will be excerpts of code already done and others to be filled in. The dataset to be used will be also included, although students can use their own data sets if that is their aim. A proposal for this assignment is already accessible as the Notebook [Assignment 1](../Assignment1.ipynb).\n",
      "  \n",
      "  \n",
      "* **Text Analysis (12%)**. In this assignment the student is expected to extract information and run different analysis over the text *[Moby Dick; or The Whale](http://www.gutenberg.org/cache/epub/2701/pg2701.txt)*, by <NAME>, from [Project Gutenberg](http://www.gutenberg.org/), in order to come to conclusions without reading the book. Other text sources, web sources or corpora can be used by the student after teacher approval. The template for the assignment will include guidelines and functions prototypes for the student to run measures such as frequency distributions, word and letter counts, richness, average length per sentence and paragraph, entity extraction and grammatical structures. Visualizations are also required. Conclusions for this assignment needs to address the topic of the book and the writing style of the author for the book. The proposal will be aviable as the Notebook Assignment 2.\n",
      "\n",
      "\n",
      "* **Network Science (12%)**. Unlike previous assignments, the dataset is not given. Instead, the student is expected to use a graph of her or him choice from [Koblenz University repositories](http://konect.uni-koblenz.de/networks/). The graph can also be created by the student, although a minimum of 100 nodes and 300 relationships are mandatory in both cases. Smaller but more dense graphs can used upon aprroval by the teacher. The template for this assignment will be made availabel as the Notebook Assignment 3. It will include some guides on the expected analysis to run (degree, density, diameter, betweenness, average shortest path, closeness, clustering, modularity, and page rank), but this time there will not be code, and almost everything will need to be written by the student."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
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