<p>Based on the mission of our Taiwan AI Academy – enabling the employees from different industries with AI knowledge and technology, Technical Professionals Class offer the students 16-week course with 3 days in a week. 
</p>
<p>This course can be separated into two parts: (1) theory lecture with hands-on practice and (2) term projects:</p>
<dl>
<dt>(1) Theory lecture with hands-on practice:</dt>
<dd>During the first 8 weeks, we will teach our students the core and advanced knowledge of current artificial intelligence. Please refer below course roadmap for the detail of 10 topics. Students will learn the basic concept of these topics, and then practice with our examples. We will conduct the mid-term exam to our student after these topics. </dd>
<dt>(2) Term project:</dt>
<dd>In Technical Professionals Class, our goal is not only to make sure every student to learn the necessary knowledge of artificial intelligence, but also to make sure them able to resolve the problem they faces in their industries, by the skill we taught them in the first half of this Class. Our teaching assistants will guide the students from problem defining, data collection and cleaning, model survey and creation, and refine-tuning, even deployment. Although the students only have 8 weeks to finish their term project, most of these projects can reach the level of PoC (proof of concept) in the end of our Class. </dd>
</dt>
<p>Below are the 5 excellent projects during the past years: </p>
<dl>
<dt>Project 1: Farm HarvestBot</dt>
<dd>
<ul><li>Purpose: use AI technology – Object Detection, to automatically locate bell peppers among the leaves, and then classify the pepper found is matured or immature.
<li>Video: <a target=_blank href=https://drive.google.com/file/d/1_N8sM6h6wwX0RQG26A8_sQe9jILHlXVS/>https://drive.google.com/file/d/1_N8sM6h6wwX0RQG26A8_sQe9jILHlXVS/</a>
</ul>
</dd>
<dt>Project 2: Coffee Bean Selector</dt>
<dd>
<ul><li>Purpose: use Lego and other mechanics to build a pipeline which carries the coffee beans to the camera, for classification good bean or bean with problems, and then automatically send to two buckets respectively.
<li>Video: <a target=_blank href=https://drive.google.com/file/d/1RXlEt9eoRzCz95vgohlaC6R_06ddUKmF/>https://drive.google.com/file/d/1RXlEt9eoRzCz95vgohlaC6R_06ddUKmF/</a>
</ul>
</dd>
<dt>Project 3: Detect Drowsy Driving</dt>
<dd>
<ul><li>Purpose: use smartphone as an edge device. The app inside the smartphone will determine the driver whether to behave sleepy by the action in their face. Once the app finds drowsy driving, it will warn to driver by voice and suggest.
<li>Video: <a target=_blank href=https://drive.google.com/file/d/1MViaKekdCzHQSxGHjHFqtZK6r1LpdII2/>https://drive.google.com/file/d/1MViaKekdCzHQSxGHjHFqtZK6r1LpdII2/</a>
</ul>
</dd>
<dt>Project 4: Smart Trash Can</dt>
<dd><ul><li>Purpose: this smart trash can uses camera to determine what kind of trash the person is carrying, and automatically open the door for that kind of trash.
<li>Video: <a target=_blank href=https://drive.google.com/file/d/1xcPo3A7egBiw3gryeLtxdyGlJOdBDHZi/>https://drive.google.com/file/d/1xcPo3A7egBiw3gryeLtxdyGlJOdBDHZi/</a>
</ul></dd>
<dt>Project 5: MRT Crowd Estimation</dt>
<dd>
<ul>
<li>Purpose: 
<li>Picture:
</ul>
</dd>
</dl>