Generative AI for Coders

Designed with you in Mind

By exploring the process of constructing generative AI models, coders gain the skills and knowledge necessary to leverage these models and frameworks in their development projects. This enables them to enhance software development processes, create innovative applications, and solve complex problems using AI-generated solutions across various contexts. Participants will achieve the following learning objectives:

• Image Generation Mastery
  Proficiency in creating image synthesis models, with hands-on experience in diverse datasets and conditional generation.
• Audio Synthesis Competence
  Ability to generate realistic audio, with practical applications in music, speech, and attribute control.
• Text Generation Proficiency
  Solid understanding of text generation, applied in creative writing, dialogue generation, and content summarization.
• Multimodal Integration Capability
  Integration of generative AI across images, audio, and text, exploring cross-modal tasks for cohesive project development.
• Evaluation and Quality Control
  Skills in evaluating diversity and quality of generated content, implementing metrics for practical utility and model effectiveness.
• Build Your Own
  Apply acquired skills in a down-to-earth project, crafting a simple yet impactful generative AI application across image, audio, or text domains.

Participants are expected to be familiar with basic statistics and Python.

Meet Your Instructor

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Victor Palacios serves as the Director of Data Science and Artificial Intelligence Partnerships at the University of San Francisco, where he develops strategic industry collaborations and supports applied AI innovation across the Data Institute. He holds three graduate degrees: an MS in Information Science from Nagoya University in Japan, an MS in Data Science from USF, and he is currently completing a third master's in Computer Science.

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