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Liam
Professor
An intensive course covering advanced model control techniques and in-house AI model training for enterprises. Trainees will master multi-parameter lock methods, cost-effective LoRA fine-tuning strategies that save up to 90%, sample dataset curation workflows, and standardized packaging for proprietary AI model library handovers.
4.6 2.6K

Course Description

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Flash Sale -10%
  • 110 hours in total
  • 75 lessons
  • 24 challenges
  • 3 Certificates of completion
  • Lifetime access

Video

110 hours in total

Text material

382 pages

Assessments

24 challenges

Certificates

3 Certificates

What's included?

Outstanding features for highly customizable Courses, Units, Lessons, and Quizzes.

Comprehensive Knowledge

Proficiently apply multi-parameter lock techniques (Style Reference, Character Reference, Image Weight) to eliminate brand identity drift during large-scale asset production.

Working Pipeline

Formulate custom enterprise model training strategies using LoRA fine-tuning, saving up to 90% compared to building base models from scratch.

Practice

Standardize the input dataset curation pipeline (15–30 high-quality images), write detailed captions, and train proprietary models for physical products or in-house Virtual KOLs.

Real Experiment

Establish secure packaging, version control, and handover procedures for AI model libraries to enable independent in-house operations.

Course Lessons

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Created by

Liam

History Teacher
Liam brings over 8 years of practical experience in Multimedia Production, CGI/VFX, and Commercial Ad Design. A Digital Communication & Media graduate from Raffles University (Singapore), he has advised on visual and AI strategy for enterprise clients including The Grand Ho Tram, Nutifood Corp, NgocDung, Kangnam, and PICKDI Corp. Specializing in integrating Generative AI into commercial pipelines, he trains students in workflows that meet strict Korean partner standards.

Reviews

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4.7
1.5K ratings
5: 1.4K reviews
4: 100 reviews
3: 0 reviews
2: 0 reviews
1: 0 reviews
Trinh Quoc Huy
2 hours ago
5.0
Unexpected outcome from provided GEMs!
Adopting LoRA fine-tuning saved us 90% in costs compared to building base models from scratch. Standardizing the packaging and handover of in-house AI libraries was the key to maintaining our competitive edge in technology and data privacy.