<h2>Course Objectives</h2>
<p>By the end of this course, you will be able to:</p>
<ul>
<li>Utilize data patterns to identify potential health risks and disease indicators.</li>
<li>Use computational tools to formulate and answer scientific questions.</li>
<li>Communicate discoveries through effective visualization.</li>
</ul>
<h2>What You Need to Bring to the Class (and Lab)</h2>
<p><img src="/teaching/apsc-3984/lectures/l1/1.png" alt="01"></p>
<h2>This Course Covers a Wide Range of Applications</h2>
<p><img src="/teaching/apsc-3984/lectures/l1/2.png" alt="02"></p>
<h3>Applications in This Course</h3>
<ul>
<li>Chick growth monitoring</li>
<li>Pig reproductive wellness</li>
<li>Dairy cow lactation and milk quality</li>
<li>Heifer spatial behavior</li>
<li>Canine aging and wellness</li>
</ul>
<h3>Skills You'll Develop</h3>
<ul>
<li>Data management and organization</li>
<li>Statistical analysis fundamentals</li>
<li>Data visualization techniques</li>
<li>Python programming basics</li>
<li>Real-world data analytics</li>
</ul>
<h2>This Course Required No Coding Experience</h2>
<p>But you need to have a high-level understanding to input <strong>meaningful prompts</strong>!</p>
<p><img src="/teaching/apsc-3984/lectures/l1/3.png" alt="0"></p>
<p>Continue with the next prompt...
<img src="/teaching/apsc-3984/lectures/l1/4.png" alt="0"></p>
<h2>Data Science in Livestock Farming</h2>
<p>Data-based animal management has been a trend to improve the monitoring accuracy and resolution (time and space) in many practical farming scenarios.</p>
<p><img src="/teaching/apsc-3984/lectures/l1/5.png" alt="0"></p>
<p>Effectively <strong>managing</strong>, <strong>interpreting</strong>, and <strong>expressing</strong> data are key components of the next generation of livestock farming.</p>
<h2>Ready to Start?</h2>
<p>Click the button below to dive into the first module!</p>


1. Descriptive Statistics

2. Pivot Tables

3. Functions

4. Case Study

5. Visualization

6. Multifacet Visualization

I. Excel Basics

This course is an introduction to data-based animal management for undergraduate students with no prior coding experience.

APSC-3984: Data-Based Animal Management

<h2>A. What Is a Pivot Table?</h2>
<p>It is an approach to <strong>summarize</strong> data in order to highlight <em>trends</em> and <em>insights</em>.</p>
<h2>B. Where to Start a Pivot Table?</h2>
<h3>Online Version</h3>
<p><img src="/teaching/apsc-3984/lectures/l3/1.png" alt="0"></p>
<h3>Desktop Version</h3>
<p><img src="/teaching/apsc-3984/lectures/l3/2.png" alt="0"></p>
<h2>C. Think of Each Column (Variable) in Your Dataset as a Poker Chip</h2>
<p>Each variable is an independent unit of information. When you build a pivot table, you place these chips on the board (rows, columns, values, or filters). Each chip you spend represents one variable being used to organize or summarize the data.</p>
<p><img src="/teaching/apsc-3984/lectures/l3/3.png" alt="0"></p>
<h2>D. Key Components of a Pivot Table</h2>
<p><img src="/teaching/apsc-3984/lectures/l3/5.png" alt="0"></p>
<h2>E. Examples</h2>
<p><img src="/teaching/apsc-3984/lectures/l3/6.png" alt="0"></p>
<p><img src="/teaching/apsc-3984/lectures/l3/7.png" alt="0"></p>
<p><img src="/teaching/apsc-3984/lectures/l3/8.png" alt="0"></p>
<p><img src="/teaching/apsc-3984/lectures/l3/9.png" alt="0"></p>
<h2>F. Your Turn</h2>
<p>Identify the grouping and aggregation terms in the following sentences.</p>
<blockquote>
<p>What is the maximum weight recorded for each day?</p>
</blockquote>
