Neural Networks in Business: From Foundations to Generative AI

CT Score

1500

#0 of 0 in QST BA

Difficulty

—/10

Workload

—h/wk

Median grade

—

from grade distribution

Would take again

—

n = 0 verified

Grade distribution

No distribution published for this course.

By professor: same course, different game

PROFESSORSCOREGRADEHRS/WKTERMS

Professor ratings →

Sections

No section data for this term yet.

In the tree

QSTBA 600, QSTBA 602, QSTBA 780, QSTBA 810, QSTBA 820. This course provides a basic introduction to the theory and implementation of artificial neural networks (ANNs) in Python. We will introduce students to Keras and PyTorch, Python packages / frameworks that support the implementation of neural networks. We will then develop an understanding of fundamental concepts behind neural network architecture. We will explore a variety of use cases, deal with various types of unstructured data (text, images, audio, time series), and gain hands-on experience, starting with the implementation of simple networks and building up towards harnessing the powers of more complex pre-trained ones. This is an intensive course. Students will pursue a hands-on group project over the duration of the course→QST BA 865→unlocks 0 courses

No mapped courses require this one yet. See on the map →

Study groups

0 active

🔒 Verified-only writes. You post as “sophomore, lecture section”: real enough to trust, anonymous enough to be honest.