Create a wide range of design deliverables using ChatGPT Images 2.0, including logos, product photos, mockups, banners, wedding snapshots, wedding invitations, POP displays, menus, and product detail pages. This hands-on course teaches you how to write prompts to achieve the desired results and how to structure reusable templates.
38 learners
Level Beginner
Course period Unlimited
Reviews from Early Learners
5.0
RyuWoong
This lecture explains AI image generation by stripping away all the fluff and focusing only on the core essentials. You might be skeptical because the videos are short despite the high price, but it actually saves you time by providing concise explanations of key concepts and examples. The two major points of this lecture are: It is important to write prompts well. People often unconsciously omit background knowledge they already possess when explaining things to others. The same applies to writing prompts. If you leave out background knowledge when writing a prompt, it becomes difficult to get the desired result. If you look closely at the prompts, you will see they are written in quite a bit of detail. It is also important to understand the limitations of AI. Although AI is continuously evolving and its outputs are improving, limitations still exist. While it handles the general composition well, there are often "glitches" or errors in the fine details. To overcome these limitations, it is better to provide more detailed prompts or avoid those specific areas altogether. While you might think of this as a simple image generation course, I believe you can also learn how to write prompts and what kind of approach to take.
5.0
jinhee p
The lecture was easy to understand because it was structured systematically with step-by-step examples. I was able to clearly learn what Image 2.0 does well and what it struggles with, which I believe will allow me to generate images more efficiently by applying it to my practical work.
5.0
Sunny Sideup
It was great to have the capabilities and limitations of GPT IMAGE 2.0 clearly pointed out, and to be able to directly verify and observe the possible areas through practical examples. In practice, I experienced many limitations when using image generation or editing functions, such as the original image being altered, but I was able to learn a lot about how to overcome those limitations. Since the guidance provided clear directions for creating everything from light drafts to images for actual use, I think this is a lecture that not only designers but also bloggers and general users who need simple drafts can easily understand and learn from.
How to create design deliverables with ChatGPT Images 2.0
The ability to construct prompts to achieve the desired image results
Criteria for Evaluating the Advantages and Limitations of AI Image Models
How to Use Prompt Templates for Repetitive Tasks
Who is this course right for?
Those who want to use AI-generated images in their design work
Those who want to quickly create logo, mockup, and product detail page designs
Those who want to understand the possibilities and limitations of AI image models
Those who want to write prompts efficiently
333
Learners
46
Reviews
5
Answers
4.8
Rating
5
Courses
Hello. This is DX LAB's AI Lab.
DX LAB is a team where developers and designers experiment with AI, design, and digital production tools together and apply them to practical work.
Currently, online lectures are directly planned and conducted by designers belonging to DX LAB.
The designer leading the lecture is a UI/UX and content designer with four years of experience. Based on their experience running a design tech blog and producing online courses, they create AI and design content that can be immediately applied in practice.
At DX LAB's AI Laboratory, we aim for easy-to-understand explanations rather than complex theories, focusing on the process of creating actual results. We will guide you step-by-step so that even those new to AI and digital work can easily follow along.
All
24 lectures ∙ (1hr 54min)
Course Materials:
All
9 reviews
4.6
9 reviews
Reviews 1
∙
Average Rating 5.0
Edited
5
This lecture was perfect for quickly grasping the core essentials of how to use image generation AI in practice. The length was just right, so I was able to complete the course without feeling overwhelmed. In particular, testing all the different cases myself would have taken an enormous amount of time, but the instructor tested everything and clearly organized what works and what doesn't, which I think will significantly reduce my trial and error. I always found it tedious to write new prompts every time, so learning how to use template structures for repetitive tasks was a very useful tip I hadn't known before. I always wondered why my results looked strangely lacking compared to AI images made by others. I realized through this course that it was because I was demanding too much at once in a single prompt. I tried the 'stepping stone reference technique' I learned in the lecture, and it made it much easier to guide the image in the direction I wanted, and the results are definitely more solid and satisfying. I will make good use of what I've learned by adapting it to my own workflow. Thank you for the great lecture!
Hello Mongnu, thank you so much for leaving such a detailed and heartfelt review. In this course, I put the most effort into conveying ways to reduce unnecessary trial and error and efficiently utilize AI image generation in actual work. I am very happy and grateful that you recognized that aspect. I feel particularly rewarded knowing that applying the "stepping stone reference technique" was helpful to you. I hope the content covered in the course continues to be useful in your actual work, and I will return with even better content in the future. Thank you once again for leaving such a great review. ☺️
Reviews 5
∙
Average Rating 5.0
Edited
5
This lecture explains AI image generation by stripping away all the fluff and focusing only on the core essentials. You might be skeptical because the videos are short despite the high price, but it actually saves you time by providing concise explanations of key concepts and examples. The two major points of this lecture are: It is important to write prompts well. People often unconsciously omit background knowledge they already possess when explaining things to others. The same applies to writing prompts. If you leave out background knowledge when writing a prompt, it becomes difficult to get the desired result. If you look closely at the prompts, you will see they are written in quite a bit of detail. It is also important to understand the limitations of AI. Although AI is continuously evolving and its outputs are improving, limitations still exist. While it handles the general composition well, there are often "glitches" or errors in the fine details. To overcome these limitations, it is better to provide more detailed prompts or avoid those specific areas altogether. While you might think of this as a simple image generation course, I believe you can also learn how to write prompts and what kind of approach to take.
Thank you for the detailed review, RyuWoong ☺️ As you mentioned, writing prompts well is crucial, so I included the essential items to follow when crafting prompts in the lecture. In particular, the background information you mentioned is easy to overlook but very important! In a way, I feel it's similar to requesting a task from a person. It seems that prompt engineering remains important, especially due to the limitations in detail. I strongly agree with the points you made, and I will continue to provide great content in the future. Thank you once again for leaving such a detailed and kind review!
Reviews 1
∙
Average Rating 5.0
5
The lecture was easy to understand because it was structured systematically with step-by-step examples. I was able to clearly learn what Image 2.0 does well and what it struggles with, which I believe will allow me to generate images more efficiently by applying it to my practical work.
Hello jinhee p! Thank you so much for your valuable review 👍 I put a lot of effort into the screen planning to help with understanding, and I'm so glad it came through 😆 I will continue to provide helpful content in the future. Have a great weekend!
Reviews 4
∙
Average Rating 5.0
5
It was great to have the capabilities and limitations of GPT IMAGE 2.0 clearly pointed out, and to be able to directly verify and observe the possible areas through practical examples. In practice, I experienced many limitations when using image generation or editing functions, such as the original image being altered, but I was able to learn a lot about how to overcome those limitations. Since the guidance provided clear directions for creating everything from light drafts to images for actual use, I think this is a lecture that not only designers but also bloggers and general users who need simple drafts can easily understand and learn from.
Hello Sunny Sideup! Thank you so much for leaving such a detailed review 😊 As you mentioned, there are many cases where the original image changes unexpectedly or the desired result isn't achieved. That's why I structured the course so you could personally check what is possible and what requires caution. I am both happy and grateful to hear that it was actually helpful to you. I will continue to return with great content that helps many people. Have a wonderful day ✨
Reviews 4
∙
Average Rating 3.0
Edited
1
This course is essentially paying 138,600 KRW to purchase the 'prompt templates' for image generation introduced in the materials. The course content follows this pattern: 1) Enter the prompt attached in the course materials into GPT. 2) Then, this image is actually generated. At the very least, there should be a review and introduction of the complex prompts the instructor created (which span about two A4 pages), but there is none. The course content simply consists of demonstrating that images are generated when you paste the prompts from a notepad into GPT. The prompt lecture chapter only covers very general information and basic guides, such as the need for clear requirements and specifying desired camera angles. There is no actual instruction regarding the long, detailed prompts the instructor personally crafted for POP and wedding photo printing. It truly only demonstrates that images are generated when you plug them in. The only "application" mentioned is changing minor variations like titles and colors within those templates. I wondered why the course was so short, and now I see why. It feels like going to a math academy to learn the subject, but coming out with nothing but a formula sheet and no explanation of theory or fundamentals. This course might be useful for those who don't need detailed explanations and just want image generation prompts to plug into GPT. However, considering the intent is solely to provide templates, the tuition fee of nearly 140,000 KRW feels quite expensive.
Hello hwan, thank you for completing the course and leaving your honest feedback. I fully understand the disappointment you mentioned. You may have felt that the process of designing prompts from scratch was lacking, and you might have felt that more explanation was needed regarding why each element of a prompt is necessary. However, one of the key components we prepared for this course was verifying the actual implementation scope of image generation models. We directly experimented with resolution, aspect ratio, fonts, colors, positioning, spacing, and background removal. We identified what works well. We also summarized what can only be implemented as an approximation. We distinguished tasks that are more efficient to handle using editing tools. Without these established criteria, one can end up spending a lot of time during actual work. This is because it is easy to mistake a task that the model inherently struggles with for a problem with the prompt. This leads to constantly changing sentences and repeatedly generating images. Typical examples include tasks involving precise color values, coordinates, kerning, or transparent backgrounds. Conversely, if you know the potential range and limitations of the model, you can make quick judgments. You can divide the work between what to solve with AI and what to finish with editing tools. This also reduces unnecessary trial and error. The purpose of the experimental section was not just to introduce features, but to provide the criteria for judgment to reduce actual working time. The 'Stepping Stone Reference Method' was covered for the same reason. It is a method of not creating complex results all at once. You utilize the image created in the previous step for the next task. By breaking it down into steps like this, it is easier to maintain the consistency of the image and reduce errors. The prompt templates were also not prepared simply as sentences to be copied and used. They were tools to show you what needs to remain fixed during repetitive tasks. I also wanted to convey what needs to be changed for each task. There was also an aspect of providing examples of how much "fixing power" a prompt alone can have. We prepared this course believing that these contents could provide clear value in actual work. However, I feel a great sense of regret that this value did not seem to resonate sufficiently. That is why I have explained the intentions and the parts I consider important at such length. Thank you once again for leaving such specific feedback. I will ensure that your opinions are reflected in future improvements.
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