Instructor: International Business School Instructors

Prerequisites: ECON 213a and BUS 215f, previous experience coursework in Python. May not be taken for credit by students who took BUS/FIN 241f in prior years.

Course Description: <b>Course will meet M, W, Th from 8:30 AM–11:00 AM (ET)</b><br>
Offers a general topics course on machine learning tools, and their implementation through Python, and the Python packages, Scikit Learn, Keras, TensorFlow, and the Natural Language Toolkit (NLT). The course is oriented heavily to applications in business and finance, giving students the tools needed to survive in the modern data analytics space. It is not intended as a deep theoretical approach to machine learning. Students will finish the class with a basic understanding of how to execute predictive analytic algorithms, as well as rigorously test their performance. The course is statistical in nature.<br>
Instructor: Blake LeBaron<br>
<b>Instruction for this course will be offered both remotely and in a hybrid format. Meeting times for this course are listed in the schedule of classes (in ET).</b>
</br><b>Course will meet M, W, Th from 8:30 AM–11:00 AM (ET)</b>

Session: Session I

Day: M, W, Th

Time: 8:30am - 11:00am

Credit Hours: 4 Credits

Course Format: 2142

Enrollment Limit: 25 students

Course Classification: Available for Graduate Credit

Course Tuition: $3,100

Course Fees: None

Open to High School Students: No