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Foundations of Hybrid AI Filmmaking: Generative Tools, Live Performance, and Human Authorship

FILM TV X 478.61

An introduction to generative AI in filmmaking, taught from the perspective of the director and cinematographer. After a concise overview of where AI in film stands today, what it can do, and what it should do, the course moves quickly from fully generated images and video toward hybrid production: live-action footage, shot by students at home, combined with AI-generated characters, environments, and effects. In the first weeks, students use large language models as writing and development partners, then use image and video generation to develop a visual style, pitch a project, and create a short, fully AI generated proof-of-concept. The second half of the course treats AI as an extension of the camera. Through film-at-home assignments using their own smartphone or camera, students learn to capture image and video that AI tools can reliably read and transform: even lighting and careful exposure; deliberate lens, framing, and camera-movement choices; tracking markers and clean plates; and a practical approach to turning an ordinary room into a stage for an AI-generated world. Assignments include performance capture, in which students record themselves or a collaborator and transpose that performance onto an AI-generated character, and world manipulation, in which the space around a live-action performance is transformed. Effective visual storytelling and photographic best practices are through lines of the course. Lens language, composition, and continuity matter as much to a convincing AI-assisted image as they do on a traditional set, and they are the skills that separate intentional work from generic output. All generative work is done in two consolidated, browser-based platforms, Adobe Firefly and Magnific. The course culminates in a short hybrid scene and a before-and-after breakdown of how it was made. Throughout, students examine the ethical, legal, and professional questions raised by generative AI: copyright, authorship and artistry, consent and likeness, labor, and disclosure. Students must have access to a smartphone or digital camera, editing software, and the AI tools and credits listed under requirements.

Duration
As few as 6 weeks
Units
4.0
Current Formats
Live Online
Cost
Starting at $960.00

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About This Course

An introduction to generative AI in filmmaking, taught from the perspective of the director and cinematographer. After a concise overview of where AI in film stands today, what it can do, and what it should do, the course moves quickly from fully generated images and video toward hybrid production: live-action footage, shot by students at home, combined with AI-generated characters, environments, and effects. In the first weeks, students use large language models as writing and development partners, then use image and video generation to develop a visual style, pitch a project, and create a short, fully AI generated proof-of-concept. The second half of the course treats AI as an extension of the camera. Through film-at-home assignments using their own smartphone or camera, students learn to capture image and video that AI tools can reliably read and transform: even lighting and careful exposure; deliberate lens, framing, and camera-movement choices; tracking markers and clean plates; and a practical approach to turning an ordinary room into a stage for an AI-generated world. Assignments include performance capture, in which students record themselves or a collaborator and transpose that performance onto an AI-generated character, and world manipulation, in which the space around a live-action performance is transformed. Effective visual storytelling and photographic best practices are through lines of the course. Lens language, composition, and continuity matter as much to a convincing AI-assisted image as they do on a traditional set, and they are the skills that separate intentional work from generic output. All generative work is done in two consolidated, browser-based platforms, Adobe Firefly and Magnific. The course culminates in a short hybrid scene and a before-and-after breakdown of how it was made. Throughout, students examine the ethical, legal, and professional questions raised by generative AI: copyright, authorship and artistry, consent and likeness, labor, and disclosure. Students must have access to a smartphone or digital camera, editing software, and the AI tools and credits listed under requirements.

Winter 2027 Schedule

Date
Details
Format
 
-
Monday, Thursday 10:00AM - 1:00PM PT
REG#
411419
Fee:
$960.00
Live Onlineformat icon
Remote Classroom
Updating...
Notes

Internet access required to retrieve course materials.

This course will utilize a third-party software that is not provided by the University. Students are expected to exercise appropriate care and judgment when using this software and must not upload, enter, or otherwise disclose personal, sensitive, confidential, or proprietary information, including intellectual property or proprietary business information. All course-related activities should be completed using publicly available, fictitious, anonymized, or otherwise non-identifiable data.

Do not use Magnific with protected information such as student information, health information, confidential financial information, personnel conduct data, etc. In general, any data classified by UC as Protection Level 3 or 4 should not be used. Please be advised that in the absence of a UC agreement covering UC’s (including its staff, faculty and students) use of Magnific, your use of Magnific constitutes personal use and obligates you, as an individual, to assume responsibility for compliance with the terms and conditions set forth in Magnific own Terms of Use.

Deadline
Refunds only available from November 02, 2026 to January 17, 2027
Schedule
Type
Date
Time
Location
Lecture
Mon Feb 1, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Thu Feb 4, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Mon Feb 8, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Thu Feb 11, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Mon Feb 15, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Thu Feb 18, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Mon Feb 22, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Thu Feb 25, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Mon Mar 1, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Thu Mar 4, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Mon Mar 8, 2027
10:00AM PT - 1:00PM PT
Remote Classroom
Lecture
Thu Mar 11, 2027
10:00AM PT - 1:00PM PT
Remote Classroom