The landscape of digital content is shifting rapidly, moving away from basic filters and simple mobile applications toward professional, frame-by-frame generative workflows. For creators, marketers, and digital artists, mastering these advanced tools is no longer just a novelty; it is becoming a core technical requirement for high-end production. However, the barrier to entry remains high, heavily guarded by complex software interfaces, demanding hardware requirements, and a steep learning curve.
If you are looking to bypass consumer-level applications and dive directly into professional neural network rendering, you have likely encountered Video Creation By Using Artificial Intelligence. Authored by veteran 3D artist Yury Yeltsov, this program promises to teach the exact workflows used to generate highly stylized, temporally consistent animations and digital doubles. Yet, researching this program presents an immediate challenge: the search results are highly fragmented, dominated by discount resellers, forum group-buys, and conflicting information about what the curriculum actually entails.
This review cuts through the noise of the grey-market reseller ecosystem to examine the actual technical stack taught in the curriculum. We will break down the hardware requirements, the realities of using cloud-based rendering tools, the disparity in pricing across different platforms, and whether the advanced workflows justify the investment of your time and money.
At a glance
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Item |
Details |
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Course name |
Video Creation By Using Artificial Intelligence |
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Provider / Instructor |
Yury Yeltsov |
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Category |
Social Media / AI Video Production |
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Intent fit |
Commercial Investigation / Technical Verification |
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Buyer stage |
Decision (Comparing official vs. reseller platforms) |
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Pricing transparency |
Highly volatile (Official vs. Reseller disparity) |
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Policy transparency |
Not specified on public snippets |
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Trust signal status |
Confirmed (Instructor has 15+ years of industry experience) |
What this review helps you decide
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Question |
Why it matters |
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Is the technical stack outdated? |
AI tools evolve monthly; knowing if the taught software is still an industry standard prevents wasted effort. |
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Can my computer handle it? |
Local AI rendering requires significant GPU power, making hardware a primary bottleneck for many students. |
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Should I buy from a reseller? |
The massive price difference between the official site and discount platforms comes with hidden risks regarding support and updates. |
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Is this for beginners? |
Understanding the complexity of the software helps you gauge if you have the necessary technical baseline. |
Course overview
This program is positioned as a high-end technical deep-dive for digital creators who want to move beyond the limitations of basic mobile AI apps. Instead of relying on closed-ecosystem tools with rigid guardrails, the curriculum focuses on open-source and highly customizable neural networks. It is designed for users who want granular control over their visual outputs, from specific character consistency to complex video stylization.
Readers typically search for reviews of this program because the software it teaches—specifically Warpfussion and Stable Diffusion—is notoriously difficult to install, configure, and optimize. Furthermore, the search landscape is heavily populated by third-party Learning Management System (LMS) resellers offering the program at steep discounts. Prospective students need to know whether the core educational material holds up, what hidden costs exist in cloud computing, and whether the official support channels are necessary for success.
Who is Yury Yeltsov?
Understanding the instructor's background is crucial when evaluating an advanced technical program. Yury Yeltsov is a professional 3D illustrator and AI artist with over 15 years of experience in the creative industry. His background in traditional 3D modeling and illustration provides a strong foundation for his approach to generative AI.
Unlike instructors who simply jumped on the recent generative trend, Yeltsov’s long-term experience in digital art means he understands the fundamental principles of lighting, composition, and rendering. This background heavily influences the curriculum, which treats AI not as a magic button, but as a complex rendering engine that requires precise inputs, parameter tuning, and an understanding of visual aesthetics to produce professional results.
The Technical Stack: Warpfussion and Google Colab Explained
The core value of this program lies in its specific technical stack. It explicitly avoids consumer-grade mobile applications in favor of professional, PC-based AI models.
The primary tool taught is Warpfussion. Warpfussion is an advanced notebook interface for Stable Diffusion specifically optimized for video generation. Its main advantage is temporal consistency—the ability to keep the style, characters, and background stable from one frame to the next, reducing the flickering and morphing commonly seen in amateur AI videos. However, Warpfussion is highly complex, requiring users to manage dozens of parameters, mathematical weights, and rendering settings.
Because running Warpfussion locally requires an incredibly powerful graphics card (typically an Nvidia GPU with high VRAM), the curriculum heavily utilizes Google Colab. Google Colab is a cloud-based platform that allows users to run Python code and access powerful remote GPUs directly through their web browser. This bypasses the need for expensive local hardware, though it introduces its own learning curve regarding cloud environment setup, file path management, and potential subscription costs for premium cloud access.
Curriculum Breakdown: From Setup to Deepfakes
The curriculum is structured to take students from the initial software configuration through to advanced rendering techniques. Based on verified outlines, the program covers five or more comprehensive modules.
The journey begins with the Google Colab setup, teaching students how to mount their cloud drives, install the necessary dependencies, and launch the Warpfussion interface without encountering code errors. From there, it moves into the intricate Warpfussion settings, explaining what each slider and parameter does to the final video output.
A significant portion of the training is dedicated to LoRa (Low-Rank Adaptation). LoRa is a technique used to train the AI on specific subjects—such as a particular person's face or a specific art style—using a small dataset of images. The program teaches how to use LoRa for consistent character creation across different video scenes.
The curriculum also covers the creation of deepfakes. In this educational context, deepfakes are approached as a tool for digital doubles and creative filmmaking, focusing on face-swapping and maintaining facial consistency in moving footage. Finally, the program covers comprehensive video stylization, teaching students how to transform standard footage into various artistic mediums, such as anime, oil painting, or 3D animation. Once you master these stylization techniques, you can combine them with strategies for creating viral video content to maximize your reach on social media platforms.
What’s likely inside the course
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Theme area |
What it likely covers |
Confidence |
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Environment Setup |
Configuring Google Colab and mounting cloud storage for AI rendering. |
Confirmed |
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Warpfussion Mastery |
Navigating the interface, adjusting parameters, and managing temporal consistency. |
Confirmed |
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Custom Model Training |
Using LoRa to train the AI on specific faces or artistic styles. |
Confirmed |
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Advanced Video Output |
Creating deepfakes and applying complex stylization to raw video footage. |
Confirmed |
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Community Support |
Access to a private Telegram channel for troubleshooting and updates. |
Confirmed |
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Refund Policy |
Money-back guarantees or trial periods for the official purchase. |
Not specified |
Official vs. Reseller Pricing: What You Need to Know
One of the most prominent objections and points of confusion surrounding this program is the extreme pricing volatility. The official price for the program appears to be $997. However, the search engine results pages are dominated by grey-market resellers, LMS product pages, and Reddit "group-buy" threads offering the exact same video files for anywhere from $15 to $100.
This disparity requires careful navigation. The reseller ecosystem operates by purchasing the official program once and distributing the downloaded video files to multiple buyers. While the upfront cost is drastically lower, buying from a reseller comes with significant drawbacks.
First, AI technology evolves at a breakneck pace; a downloaded video file from six months ago may feature an outdated version of Warpfussion or a deprecated Google Colab notebook. Second, reseller purchases do not include access to the official private Telegram group. In a highly technical program where software breaks frequently and code dependencies change, lacking access to the instructor and the community for troubleshooting can render the downloaded videos practically useless. Pricing: not covered in this review in terms of guaranteeing a specific current rate, as the market fluctuates daily.
Hardware and Software Requirements
Understanding the hardware and software prerequisites is vital before attempting this curriculum. Because the program focuses on heavy neural network rendering, a standard office laptop will not suffice for local generation.
If you intend to run the software locally on your own machine, you will need a high-end PC with a powerful dedicated graphics card, ideally an Nvidia RTX series GPU with a minimum of 12GB to 24GB of VRAM. Attempting to run Warpfussion on insufficient hardware will result in out-of-memory errors or render times that take days for a few seconds of video.
To circumvent this, the program teaches the Google Colab workflow. While this allows you to run the software on a basic laptop or even a tablet, it is not entirely free. Heavy video generation typically requires a paid subscription to Google Colab Pro to access the necessary compute units and premium GPUs (like the A100 or V100) required for timely rendering. Prospective students must factor this ongoing cloud computing cost into their overall budget.
Who this is for
This program is designed for individuals who are willing to engage with complex, code-adjacent interfaces to achieve professional-grade visual results. It is best suited for digital artists, video editors, and creative directors who find consumer AI apps too limiting and want total control over their generative outputs.
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If you are… |
This may fit if… |
This may not fit if… |
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A digital artist or animator |
You want to integrate AI into your existing professional pipeline. |
You prefer traditional hand-keyframed animation workflows. |
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A video editor |
You want to offer high-end AI stylization and digital doubles to clients. |
You are looking for simple, one-click filters for quick social posts. |
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A technical enthusiast |
You enjoy tweaking parameters, managing cloud environments, and troubleshooting. |
You get easily frustrated by code errors or complex software setups. |
Learning experience and format
The learning experience is highly technical and screen-share heavy. Students can expect to watch over-the-shoulder demonstrations of software configuration, parameter tuning, and rendering workflows. Because the subject matter involves navigating complex interfaces and managing file directories, the instruction is necessarily detailed and methodical.
A major component of the official learning experience is the private Telegram channel. This community aspect is critical because open-source AI tools frequently update, and a workflow that worked perfectly one week might require a workaround the next. The Telegram group serves as a real-time troubleshooting hub. While the curriculum focuses heavily on visual rendering, many creators supplement this by leveraging ChatGPT for AI-driven content generation to script their videos before animating them, ensuring the final product has a strong narrative foundation.
If you are considering purchasing through a discount platform, you must verify what is actually included, as you will likely be navigating the technical hurdles entirely on your own without community support.
Pros and cons
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Likely strengths |
Possible drawbacks or open questions |
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Taught by a veteran 3D artist with deep industry knowledge. |
Official price point is a significant investment. |
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Focuses on professional, highly customizable AI tools. |
Steep learning curve for those unfamiliar with cloud computing. |
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Bypasses local hardware limits via Google Colab instruction. |
Google Colab Pro requires an ongoing monthly subscription. |
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Covers advanced techniques like LoRa and temporal consistency. |
Reseller market creates confusion regarding updates and support. |
The strengths of this program lie in its uncompromising approach to quality. By focusing on Warpfussion and Stable Diffusion, it equips students with the tools actually used by professionals, rather than consumer toys. The instructor's background ensures that the technical instruction is grounded in solid artistic principles.
The drawbacks are primarily related to the inherent complexity of the subject matter and the fragmented market. The software is difficult to learn, the cloud computing costs can add up, and the prevalence of outdated reseller copies means many students may struggle to replicate the results shown in the promotional materials without official support.
Decision framework
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Decision factor |
What to check |
Why it matters |
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Technical aptitude |
Your comfort level with complex software and cloud environments. |
Warpfussion is not a one-click solution; it requires patience and troubleshooting. |
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Hardware vs. Cloud budget |
Whether you have a high-end GPU or are willing to pay for Colab Pro. |
Without adequate compute power, you cannot render the videos taught in the curriculum. |
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Purchase source |
Whether you are buying from the official site or a reseller. |
Resellers offer lower prices but strip away community support and crucial software updates. |
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End goal |
Whether you need professional consistency or just quick social media clips. |
If you only need basic effects, simpler mobile apps may be a better fit. |
Common mistakes to avoid
A frequent mistake prospective students make is underestimating the rendering time and computational power required for AI video. Many assume that because AI is "automated," it is instantaneous. In reality, rendering temporally consistent video through Warpfussion can take hours, requiring patience and careful parameter testing before committing to a final render.
Another common error is purchasing a heavily discounted version from a grey-market forum, only to discover that the included Google Colab notebook links are dead or the software version is no longer compatible with current dependencies. Without access to the official Telegram group, buyers are left stranded with broken workflows. Another mistake is focusing purely on creative output without a monetization strategy, such as applying AI outreach systems to automate meeting bookings to sell your new video services to corporate clients.
Alternatives to consider
If you are unsure whether this specific technical deep-dive is right for you, there are several alternative paths to explore:
- Free open-source tutorials: The AI community is highly active on video sharing platforms. You can find numerous free, albeit fragmented, tutorials on setting up Stable Diffusion and basic video notebooks.
- Consumer-grade AI video platforms: If you do not need granular control and just want quick results, cloud-based commercial platforms offer simpler, browser-based text-to-video generation without the need for complex setups.
- Traditional 3D animation training: If your goal is absolute control over lighting, physics, and character movement, learning traditional 3D software might be a more reliable, though time-consuming, alternative to generative AI.
FAQ
Do I need a powerful computer to take this course?
No, you do not strictly need a powerful local computer if you use the cloud-based methods taught. The curriculum heavily features Google Colab, which allows you to borrow powerful remote GPUs via your web browser, though this usually requires a paid Colab Pro subscription for heavy video rendering.
What is Warpfussion and why is it used?
Warpfussion is an advanced, open-source notebook interface built on top of Stable Diffusion. It is used specifically because it excels at maintaining temporal consistency—keeping characters and styles stable from frame to frame—which is the biggest challenge in AI video generation.
Is there a refund policy for Yury Yeltsov's course?
The official refund policy is not clearly stated on public snippets or the main sales pages. If you purchase through a third-party reseller or group-buy site, you should assume there are absolutely no refunds for digital downloads.
Can beginners take this course without prior AI knowledge?
Beginners can take the program, but they must be prepared for a steep learning curve. The curriculum walks through the setup process, but the software involves managing file paths, adjusting complex mathematical parameters, and occasional troubleshooting of code errors.
How do I access the private Telegram group?
Access to the private Telegram support group is typically granted only to students who purchase the program through the official channels. Buyers who use discount resellers or group-buys generally do not receive community access.
Are there hidden costs with Google Colab?
Yes, while Google Colab has a free tier, rendering high-quality AI video requires significant compute units. Students will likely need to upgrade to a paid Google Colab Pro or Pro+ tier to access the necessary GPUs and avoid frequent timeouts during long renders.
Verdict
Yury Yeltsov’s program offers a highly specialized, professional-grade education in generative video. It successfully bridges the gap between traditional digital art principles and cutting-edge neural network rendering. For creative professionals, 3D artists, and technical editors who want absolute control over their AI outputs, the deep dive into Warpfussion, LoRa, and temporal consistency is highly valuable.
However, this program is not for casual users looking for quick, one-click social media filters. The reliance on complex interfaces, the necessity of cloud computing subscriptions, and the steep learning curve make it a serious undertaking. Furthermore, prospective students must carefully weigh the risks of the reseller market; while the official price is a significant investment, the lack of support and updates from discount platforms can easily render the complex workflows unusable. Consider this program if you are ready to treat AI video generation as a serious, technical discipline.
Conclusion
Navigating the transition from basic AI tools to professional rendering environments requires expert guidance and a willingness to tackle complex software. This curriculum provides a clear roadmap through the difficult terrain of Warpfussion, Google Colab, and custom model training. By understanding the hardware requirements, the reality of cloud computing costs, and the importance of community support, you can make an informed decision on whether this technical deep-dive aligns with your creative and professional goals.
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