Smart AI tool selection - You will learn how to tell image, styling and video tools apart, so you can choose the right model or workflow faster for a campaign, design task or social media content piece.
Confident work in ComfyUI - You will get comfortable with ComfyUI and RunComfy, understand nodes and data flow, and be able to launch, adjust and save workflows on your own instead of guessing each next step.
Polished image generation - You will build text-to-image workflows, set models, prompts and generation parameters, and create visuals that match a brief, brand style and communication goal rather than random outputs.
Precise creative control - You will learn to use ControlNet, LoRA and Refiner to guide composition, style and details more accurately, giving you results that are more predictable, repeatable and easier to refine.
Effective image editing - You will work with image-to-image, inpainting and upscaling, so you can fix errors, restyle visuals, fill missing areas and raise the quality of finished graphics without starting from scratch.
Animation from still images - You will explore image-to-video methods such as AnimateDiff and frame interpolation, allowing you to create short animations, loops and visual assets ready for online publishing.
Automated content pipelines - You will connect nodes into larger pipelines, create reusable presets and render image batches, which helps you cut production time and scale recurring creative tasks much more efficiently.
Responsible AI usage - You will understand licensing, copyright and deepfake-related risks, so you can use models and generated assets in a more responsible way and make better decisions in commercial work.
Basic computer skills - You should be comfortable using your operating system, installing applications, managing files and folders, and working in a web browser without needing extra technical assistance.
Basic graphics literacy - You should understand core digital image concepts such as file format, resolution, aspect ratio and quality, so you can assess generated results in a clear and practical way.
Technical English - You should understand simple technical terms and interface messages in English, because tool interfaces, model names and many workflows rely on English labels and wording.
Experimental mindset - You should be ready to test settings, compare variations and draw conclusions from results, because effective work with generative AI depends on iteration and patience.
