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Building Generative AI Applications with Python

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COM SCI X 455

This course immerses students in the world of generative artificial intelligence (GenAI) and covers high-level browser-based tools, emphasizing the Python code behind them.

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Duration
As few as 11 weeks
Units
4.0
Current Formats
Online
Cost
Starting at $1,545.00

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What you can learn.

Explain the trade-offs between GAN, VAE, Diffusion, and Transformer architectures — and choose the
right one for a given constraint set
Build and evaluate generative models for text, images, and audio using Python and Hugging Face
Engineer effective prompts using zero-shot, few-shot, chain-of-thought, and structured output
techniques
Fine-tune foundation models using LoRA and QLoRA on domain-specific datasets
Design and implement multi-step agentic AI systems with memory, tool use, and self-reflection using
LangGraph
Develop multimodal applications combining text, image, and audio pipelines
Deploy a production-quality generative AI application with a live demo and documented GitHub
portfolio
Diagnose and explain common failure modes: mode collapse, hallucination, posterior collapse, latency
bottlenecks, and agent loop failures

About This Course

This 10-week hands-on course takes you from generative AI fundamentals to production-grade applications. You will build real systems using the same tools and frameworks used in industry — PyTorch, Hugging Face, LangChain, and modern LLM APIs — and leave with a deployable capstone project you can showcase on GitHub. 

Topics span diffusion models, large language models (LLMs), multimodal AI, prompt engineering, agentic AI systems, and fine-tuning with LoRA/QLoRA. Each week pairs conceptual depth with a hands-on lab. The course is designed for working professionals who want immediately applicable skills in the fastest-moving area of technology.

A note on this course's philosophy: information about generative AI is freely available online. This course
teaches judgment — when to use which tool, what breaks in production, and how to make defensible
architectural decisions. Every week includes failure case analysis, role-specific scenarios, and graded written
reasoning components that cannot be answered by running code.

Prerequisites
Before embarking on the Generative AI with Applications in Python course, it is imperative to establish a robust foundational knowledge. We suggest the following preparatory courses: Introduction to Data Science to acquaint yourself with the basic principles of data science and Machine Learning Using Python.

Fall 2026 Schedule

Date
Details
Format
 
-
This section has no set meeting times.
Instructor:
Megan Armani
REG#
410198
Fee:
$1,545.00
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Notes
Enrollment limited; early enrollment advised. Enrollment deadline: September 27, 2026.
Deadline
Refunds only available from July 27, 2026 to October 04, 2026
Course Requirements
Internet access required to retrieve course materials.
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