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##**Syllabus, schedule, notes**
###Below, you'll find links to lecture notes - this additionally serves as the syllabus as well as the course schedule.
###The lecture notes are in the form of browser-based slides [not PDF or ppt], but you can create PDFs out of them if you want, by printing to PDF using Chrome.
###Much of the lecture material is mine; that said, I do 'incorporate' figures and other material, from a variety of sites/sources - vendor websites, research papers, blog posts, books, etc.
###Links to future lectures are 'broken' [on purpose].
<!-- LECTURE/DISCUSSION SCHEDULE & LINKS -->
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<thead>
<tr>
<td><b>Week</b></td>
<td><b>Topic(s)</b></td>
</tr>
</thead>
<tbody>
<tr>
<td>1</td>
<td>
<ul>
<li><a target="_blank" href="Intro/slides.html">Introduction(s)</a>
<li><a target="_blank" href="Overview/slides.html">Data Science - an overview</a>
</ul>
</td>
</tr>
<tr>
<td>2</td>
<td>
<ul>
<li><a target="_blank" href="SourcesRepr/slides.html">Data sources, representation</a>
</ul>
</td>
</tr>
<tr>
<td>3</td>
<td>
<ul>
<li><a target="_blank" href="StorageFormats/slides.html">Data storage, formats</a>
</ul>
</td>
</tr>
<tr>
<td>4</td>
<td>
<ul>
<li><a target="_blank" href="EDA/slides.html">EDA [Exploratory Data Analysis]</a>
</ul>
</td>
</tr>
<tr>
<td>5</td>
<td>
<ul>
<li><a target="_blank" href="BigDataFund/slides.html">Big Data: fundamentals</a>
<li><a target="_blank" href="BigDataProc/slides.html">Big Data: processing</a>
</ul>
</td>
</tr>
<tr>
<td>6</td>
<td>
<ul>
<li><a target="_blank" href="BigDataProc/slides.html">Big Data: processing</a> [cont'd]
<li><a target="_blank" href="PythonOverview/slides.html">Python</a>: crash course :)
</ul>
</td>
</tr>
<tr>
<td>7</td>
<td>
<ul>
<li><a target="_blank" href="DM/slides.html">Data Mining</a>
</ul>
</td>
</tr>
<tr>
<td>8</td>
<td>
<ul>
<li><a target="_blank" href="DM/slides.html">Data Mining</a> [cont'd]
<li>Midterm review
<li><b> Midterm exam</b> [in class]
</ul>
</td>
</tr>
<tr>
<td>9</td>
<td>
<ul>
<li><a target="_blank" href="DM/slides.html">Data Mining</a> [cont'd]
<li><a target="_blank" href="ML/slides.html">ML</a>
</ul>
</td>
</tr>
<tr>
<td>10</td>
<td>
<ul>
<li><a target="_blank" href="ML/slides.html">ML</a> [cont'd]
</ul>
</td>
</tr>
<tr>
<td>11</td>
<td>
<ul>
<li><a target="_blank" href="Tools/slides.html">ML APIs, tools, platforms...</a>
</ul>
</td>
</tr>
<tr>
<td>12</td>
<td>
<ul>
<li><a target="_blank" href="genAI/slides.html">GenAI</a>
<li><a target="_blank" href="Spatial/slides.html">Spatial data</a>
</ul>
</td>
</tr>
<tr>
<td>13</td>
<td>
<ul>
<li><a target="_blank" href="Spatial/slides.html">Spatial data</a> [cont'd]
<li><a target="_blank" href="Viz/slides.html">Data visualization</a>
<li><a target="_blank" href="Appl1/slides.html">Applications_1:<br>- Business</a>
</ul>
</td>
</tr>
<tr>
<td>14</td>
<td>
<ul>
<li><a target="_blank" href="Appl2/slides.html">Applications_2:<br>- Medical/health<br>- Societal</a>
<li><a target="_blank" href="Appl3/slides.html">Applications_3:<br>- Environmental<br>- Agricultural<br>- Manufacturing</a>
<li>Thanksgiving - no class
</ul>
</td>
</tr>
<tr>
<td>15</td>
<td>
<ul>
<li><a target="_blank" href="Appl4/slides.html">Applications_4:<br>- Communications</a>
<li><a target="_blank" href="Appl5/slides.html">Applications_5:<br>- Knowledge<br>- Entertainment<br>- Commerce</a>
<li><a target="_blank" href="Governance/slides.html">Governance</a>
<li><a target="_blank" href="Wrap/slides.html">What's next?</a> [for you, data science]
</ul>
</td>
</tr>
<tr>
<td><b>Exam</b></td>
<td>
<ul>
<li><a target="_blank" href="https://classes.usc.edu/term-20243/final-examinations-schedule/"><b>Final: 12/12 (Thu), 2 pm</b></a>
</ul>
</td>
</tr>
</tbody>
</table>
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##Tools we might use (or not!):
###VDI:
####https://cloudapps.usc.edu/portal/webclient/#/desktop
###Whiteboards:
####https://webwhiteboard.com/
####https://www.tutorialspoint.com/whiteboard.htm
####https://canvas.apps.chrome/
####https://bytes.usc.edu/~saty/tools/lc/
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