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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Professional Data Science Course</title>
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<div class="container">
<h2 id="cmpt843">CMPT 733: Big Data Programming II (SFU, Spring 2023)</h2>
<h3 id="objectives">Objectives</h3>
<p> From CMPT 726 and CMPT 732, students have learned machine learning algorithms and big data programming tools. However, when facing a real-world data problem, we find that there is still a gap between what is addressed by machine learning or data engineering and what we are going to do in practice.</p>
<p>The goal of this course is to fill this gap, enabling the students to apply what they have learned to solve real-world problems. To achieve this goal, our course will cover a set of important topics that a data scientist should know, and teach students about state-of-the-art approaches. After taking this course, students should feel confident when being asked to extract value from real-world data sets, and know how to ask interesting questions about data, how to choose proper tools, how to design data-processing pipelines, and how to present final data products. </p>
<h3 id="topics">Topics</h3>
<ul>
<li>Introduction to Data Science</li>
<li>Data Preparation</li>
<li>Visualization</li>
<li>Statistics</li>
<li>Deep Learning</li>
<li>Practical Machine Learning (AutoML, Explainable AI, Feature Engineering)</li>
<li>Anomaly Detection</li>
<li>Cloud Computing</li>
<li>Responsible Data Science</li>
<li>Communication </li>
</ul>
<h3 id="logistics">Logistics</h3>
<ul>
<li><b>Instructor: </b><a href="https://stevenbergner.github.io">Steven Bergner</a></li>
<li><b>TAs: </b><a href="https://coursys.sfu.ca/2023sp-cmpt-733-g1/">Hiren Naresh Bangani, Gonick Nalwa, Aditya Bhadreshkumar Panchal</a></li>
<li><b>Lectures: </b>Thu 2:30 PM - 4:20 PM (<a href="https://roomfinder.sfu.ca/apps/sfuroomfinder_web/?q=AQ3153">AQ3153</a>)</li>
<li><b>Lab G101: </b>Tue 1:30 PM - 5:20 PM (<a href="https://roomfinder.sfu.ca/apps/sfuroomfinder_web/?q=SECB1010">SECB1010</a>)</li>
<li><b>Lab G103: </b>Thu 9:30 PM - 1:20 PM (<a href="https://roomfinder.sfu.ca/apps/sfuroomfinder_web/?q=SECB1010">SECB1010</a>)</li>
</ul>
<h3 id="grading">Grading</h3>
<ul>
<li>Assignments: 11 × 3% = 33%</li>
<li>Blog Post: 20% </li>
<li>Final Project: 47% (2% proposal + 15% milestone + 15% final presentation + 15% code&report&video)</li>
</ul>
<h3 id="project">Final Project</h3>
<ul>
<li><a href ="https://nbviewer.jupyter.org/github/sfu-db/bigdata-cmpt733/blob/master/FinalProject/project-instruction.ipynb">Instructions</a></li>
<li><a href="./final-project-sp20.html">Final Project Showcase 2020</a> </li>
<li><a href="./final-project-sp19.html">Final Project Showcase 2019</a> </li>
<li><a href="./final-project-sp18.html">Final Project Showcase 2018</a> </li>
</ul>
<h3 id="blogpost">Blog Post</h3>
<ul>
<li> <a href ="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Blog/blog-post.ipynb">Instructions</a> </li>
<li> <a href="https://medium.com/sfu-big-data">Blog Post Showcase 2019-2021</a> </li>
</ul>
<h3 id="schedule">Schedule</h3>
<table class="table table-bordered">
<thead>
<tr class="info">
<td><b>Week</b></td>
<td><b>Date</b></td>
<td><b>Event Type</b></td>
<td><b>Description</b></td>
<td><b>Course Materials</b></td>
</tr>
</thead>
<tbody>
<tr>
<td rowspan="2">Week 1</td>
<td>Thursday <br/> Jan 5</td>
<td> Lecture 1</td>
<td> <b>Course Introduction</b> <br/> What/Why Data Science? <br/> Data Science Lifecycle <br/> Questions that data scientists can answer <br/> Course Logistics </td>
<td> <a href="Lectures/lec1.pdf">[slides]</a></td>
</tr>
<tr>
<td>Thursday <br/> Jan 12/16</td>
<td> A1 due</td>
<td> <b>Assignment #1-1 and #1-2 due</b> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A1/A1-1.ipynb">[Assignment #1 (Part 1)]</a><br/>
<a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A1/A1-2.ipynb">[Assignment #1 (Part 2)]</a></td>
</tr>
<tr class="active">
<td rowspan="2">Week 2</td>
<td>Thursday <br/> Jan 12</td>
<td> Lecture 2</td>
<td> <b>Data Preparation</b> <br/> Data Collection <br/> Data Transformation </br> Data Cleaning <br/> Data Integration </td>
<td> <a href="Lectures/lec2.pdf">[slides]</a></td>
</tr>
<tr class="active">
<td>Thursday <br/> Jan 23</td>
<td> A2 due</td>
<td> <b>Assignment #2 due</b> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A2/A2-1.ipynb">[Assignment #2 (Part 1)]</a> <br/> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A2/A2-2.ipynb">[Assignment #2 (Part 2)]</a></td>
</tr>
<tr>
<td rowspan="2">Week 3</td>
<td>Thursday <br/> Jan 19</td>
<td> Lecture 3</td>
<td> <b>Data Visualization (Part I)</b> <br/> Introduction to Visualization <br/> Exploratory Data Analysis <br/> Visualization Principles</td>
<td> <a href="Lectures/lec3.pdf">[slides]</a></td>
</tr>
<tr>
<td>Tuesday <br/> Jan 31</td>
<td> A3 due</td>
<td> <b>Assignment #3 due</b> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A3/A3.ipynb">[Assignment #3]</a></td>
</tr>
<tr class="active">
<td rowspan="3">Week 4</td>
<td>Thursday <br/> Jan 26</td>
<td> Lecture 4</td>
<td> <b>Statistics (Part I) </b> <br/>Statistical Thinking <br/> EDA<br/> </td>
<td> <a href="Lectures/lec4.pdf">[slides]</a></td>
</tr>
<tr class="active">
<td>Monday <br/> Feb 6</td>
<td> A4 due</td>
<td> <b>Assignment #4 due</b> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A4/A4.ipynb">[Assignment #4]</a></td>
</tr>
<tr class="active">
<td>Friday <br/> Feb 10</td>
<td> Blog Post due</td>
<td> <b>Blog Post due</b> </td>
<td> [Blog Post Task]</td>
</tr>
<tr >
<td rowspan="2">Week 5</td>
<td>Thursday <br/> Feb 2</td>
<td> Lecture 5</td>
<td> <b>Practical Machine Learning (Part I)</b> </td>
<td> <a href="Lectures/lec5.pdf">[slides]</a></td>
</tr>
<tr>
<td>Tuesday<br/>Feb 14</td>
<td> A5 due</td>
<td> <b>Assignment #5 due</b> <br/> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A5/A5.ipynb">[Assignment #5]</a></td>
</tr>
<tr class="active">
<td rowspan="2">Week 6</td>
<td>Thursday <br/>Feb 9</td>
<td> Lecture 6</td>
<td> <b>Deep Learning (Part I)</b>
</td>
<td> <a href="Lectures/lec6.pdf">[slides]</a></td>
</tr>
<tr class="active">
<td>Wednesday <br/>Feb 22</td>
<td> A6 due</td>
<td> <b>Assignment #6 due</b> <br/> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A6/A6.ipynb">[Assignment #6]</a></td>
</tr>
<tr>
<td rowspan="2">Week 7</td>
<td>Thursday <br/>Feb 16</td>
<td> Lecture 7</td>
<td> <b>Data Visualization (Part II)</b> <br/>
Design Principles <br/>
Graph Drawing
</td>
<td> <a href="Lectures/lec7a.pdf">[slides 1]</a><a href="Lectures/lec7b.pdf">[slides 2]</a></td>
</tr>
<tr>
<td>Friday<br/>Feb 17</td>
<td> Proposal due</td>
<td> <b>Course Project Proposal due</b> <br/> </td>
<td> </td>
</tr>
<tr>
<td></td>
<td>Tuesday <br/>Mar 7</td>
<td> A7 due</td>
<td> <b>Assignment #7 due</b> <br/> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A7/A7.ipynb">[Assignment #7]</a>
</td>
<tr class="active">
<td rowspan="1">Week 8</td>
<td colspan="2">Reading Break (Feb 21 - 26)</td>
<td> <b>Suggestion: Start final project</b> </br>
</td>
<td></td>
</tr>
<tr>
<td rowspan="2">Week 9</td>
<td>Thursday <br/>Mar 2</td>
<td> Lecture 8 </td>
<td> <b>Practical Machine Learning (Part II)</b> <br/>
</td>
<td><a href="Lectures/lec8a.pdf">[slides 1]</a><a href="Lectures/lec8b.pdf">[slides 2]</a></td>
</tr>
<tr>
<td>Monday <br/>Mar 20</td>
<td> A8 due </td>
<td> <b>Assignment #8 due</b>
</td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A8/A8-1.ipynb">[Assignment #8 (Part 1)]</a> <br/> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A8/A8-2.ipynb">[Assignment #8 (Part 2)]</a></td>
</tr>
<tr class="active">
<td rowspan="1">Week 10</td>
<td>Thursday <br/>Mar 9</td>
<td> <b>Milestone Presentation</b> </td>
<td></td>
<td></td>
</tr>
<tr>
<td>Monday <br/>Mar 20</td>
<td> A8 due </td>
<td> <b>Assignment #8 due</b>
</td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A8/A8-1.ipynb">[Assignment #8 (Part 1)]</a> <br/> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A8/A8-2.ipynb">[Assignment #8 (Part 2)]</a></td>
</tr>
<tr class="active">
<td rowspan="2">Week 10</td>
<td>Thursday <br/>Mar 16</td>
<td> Lecture 9</td>
<td> <b>Statistics (Part II)</b> <br/>
<td><a href="Lectures/lec9a.pdf">[slides 1]</a><a href="Lectures/lec9b.pdf">[slides 2]</a></td>
</tr>
<tr class="active">
<td>Monday <br/>Mar 27</td>
<td> A9 due</td>
<td> <b>Assignment #9 due</b> <br/> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A9/A9-1.ipynb">[Assignment #9 (Part 1)]</a> <br/> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A9/A9-2.ipynb">[Assignment #9 (Part 2)]</a></td>
</tr>
<tr>
<td rowspan="2">Week 11</td>
<td>Thursday <br/>Mar 23</td>
<td> Lecture 10</td>
<td> <b>Deep learning (Part II)</b>, <br/> Natural Language Processing
</td>
<td><a href="Lectures/lec10a.pdf">[slides DL]</a><br/>
<a href="Lectures/lec10b.pdf">[slides NLP]</a><br/>
<a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Lectures/lec10/NLP_for_DS.ipynb">[NLP notebook]</a>
</tr>
<tr>
<td>Monday <br/>Apr 3</td>
<td> A10 due</td>
<td> <b>Assignment #10 due</b> <br/> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A10/A10.ipynb">[Assignment #10]</a> </td>
</tr>
<tr class="active">
<td rowspan="2">Week 12</td>
<td>Thursday <br/>Mar 30</td>
<td> Lecture 11 </td>
<td> Responsible Data Science
</td>
<td><a href="Lectures/lec11a.pdf">[slides 1]</a> <a href="Lectures/lec11b.pdf">[slides 2]</a></td>
</tr>
<tr class="active">
<td>Thursday <br/>Mar 30 <br/>
Monday <br/>Apr 17</td>
<td> A11 due</td>
<td> <b>Assignment #11 due</b> <br/> </td>
<td> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A11/A11-1.ipynb">[Assignment #11 (Part 1)]</a> <br/> <a href="https://github.com/sfu-db/bigdata-cmpt733/blob/master/Assignments/A11/A11-2.ipynb">[Assignment #11 (Part 2)]</a></a>
</td>
</tr>
<tr>
<td rowspan="2">Week 13+</td>
<td>Tuesday <br/> Apr 11</td>
<td> Final Project Presentation & Code </td>
<td> <b>Course Project Presentation</b> <br/>
</td>
<td></td>
</tr>
<tr>
<td> Wednesday <br/> Apr 12</td>
<td> Report & Video due </td>
<td> <b>Course Project Report due </b></td>
<td> </td>
</tr>
</tbody>
</table>
<h3 id="project-showcase">Final Project Showcase</h3>
<ul>
<li><a href="./final-project-sp20.html">Spring 2020</a> </li>
<li><a href="./final-project-sp19.html">Spring 2019</a> </li>
<li><a href="./final-project-sp18.html">Spring 2018</a> </li>
</ul>
<h3 id="references">References</h3>
<ul>
<li><a href="http://data8.org/">The Foundations of Data Science (Course)</a> </li>
<li><a href="http://www.ds100.org/">Principles and Techniques of Data Science (Course)</a> </li>
<li><a href="https://www.inferentialthinking.com/chapters/intro">Computational and Inferential Thinking: The Foundations of Data Science (Free Book)</a></li>
<li><a href="https://learningds.org/intro">Principles and Techniques of Data Science (Free Book)</a></li>
</ul>
<div class="row"><h4> </h4><hr><p class="text-center"> © Jiannan Wang & Steven Bergner 2023</p></div>
</div>
</body>
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