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Hello! If you need help with game development, I'm here to help you find (and learn) effective techniques and solutions for your projects.
I've been a Game and Software developer since 2010. I have 10+ years of experience with Unity, C#, and Game Design, and I'm constantly updating my skills. I also have experience with Unreal Engine 5, Level Design, 3D Modeling, and Mobile Development.
I developed games for PC and Android. My background includes working on:
● SAK'D (2D metroidvania game, demo released on Steam)
● NekoSuki! ~ Kitty Love Adventure (action-adventure game, in development)
● Time Master (puzzle-platformer game, released on Steam)
● Baneville (an educational game for Brazilian schools)
I have knowledge and experience with:
● Unity, C#, async-await (UniTask), advanced programming concepts
● Unreal Engine 5, Blueprints, C++
● Godot Engine, RPG Maker, GameMaker, Ren'Py
● Game Design, Level Design, UI Programming, Game Optimization, QA
● Unity Addressables, Timeline
● Third-party assets and plugins: Platformer Project, Corgi Engine, ORK RPG Framework, Game Kit Controller, World Streamer 2, DoozyUI, RealtimeCSG, Rewired, Animancer, RealToon, Dialogue System for Unity, MicroSplat, MicroVerse, etc.
● Blender, VRoid Studio (3D Modeling, Rigging, Skinning, Animation)
● Photoshop, Krita, GIMP (Texturing, Image editing)
● Wwise Audio Middleware
● Generative AI: Stable Diffusion, ComfyUI, SwarmUI, NovelAI
● Mobile Development: Android (native), iOS (native), Flutter, Xamarin, Xamarin.Forms
● Kotlin, Swift, Dart, Java, Python
- Senior software architect and polyglot programmer with 18+ years of experience.
- Seasoned solutions architect with extensive experience in distributed and serverless architectures, primarily but not limited to AWS.
1/ Listed by TradingView as an official trusted pinescript developer and trader.
Username: Daveatt on TradingView
2/ AI automation specialist
Will develop your AI automation outreach, AI Customer Support Ticket Management, AI Appointment Setting
I turn builders into agentic engineers who ship faster, smarter, and with confidence—one-on-one.
WHAT I TEACH
• Agentic engineering fundamentals: design, orchestration, and evaluation of AI agents
• AI-assisted development: coding workflows that 2–5x velocity without sacrificing quality
• Generative AI: local and cloud image/video generation, diffusion models, and end-to-end pipelines
• Complex automated workflows: retrieval, tools, function-calling, evaluators, and monitoring
• Prompt engineering that scales: patterns, guards, and reproducibility
• Efficiency playbook: from Cursor/Copilot prompts to claude code, opencode, amp, repoprompt, CI, telemetry, and test harnesses.
WHY ME
• 13+ years building production apps across startups and Uber-scale systems
• 2 years hands-on in generative AI, local and cloud-hosted LLMs and image generation, prompt engineering, and automations
• I focus exclusively on 1:1 teaching—no cohorts, no fluff, just outcomes
HOW 1:1 WORKS
• Personalized roadmap tailored to your product, stack, and constraints
• Live build-and-architect sessions focused on your real projects
• Fast async support for quick questions and advice between sessions
• Project planning, code reviews, and architecture critiques
• Developer experience upgrades: templates, dev tools, CI, prompts, and guardrails
• Curated resources and practical exercises to lock in skills
OUTCOMES YOU’LL GET
• Ship agentic features in days, not months
• Choose the right approaches for your use case and budget
• Stand up local and cloud image/video generation with reproducible results
• Automate complex multi-step workflows with evaluation and monitoring
• Write prompts and system designs that survive real users
WHO THIS IS FOR
• Engineers and founders who want hands-on guidance, not theory
• Teams ready to integrate AI into production with confidence
READY TO LEVEL UP?
Software designer & developer for iOS, MacOS, other Apple platforms, Linux server backend systems, and interactive media platforms. Solid artistic and technical skills w/ a good feel for user experience and human / computer interaction. Specialization in AI (ex: Anthropic Claude, Kling AI, Stable Diffusion/TextualEmbedding, Kandinsky, Whisper, YOLO, etc.), designing and building AI and other systems on Apple and Linux platforms, VR, computer-generated art, product design & development, research projects.
Expert in resin-based 3D printing and all the details involved including support design, hollowing and resin drainage holes, orientation for printing, scaling and support requirements, maximizing resolution, resolving issues with software analysis of the post-sliced file before running into them when printing, setting up a 3D printing workspace, the mechanical process of removing the model, washing, curing, machine maintenance, 3D modeling, and more.
I particularly enjoy teaching / mentoring, UI design and implementation, software product design and development, AI (generative, cognitive, analytical, etc.), in-depth vocal interactivity, robotics, game design and development, and/or building / leading a team.
Looking for an expert in Machine Learning, Data Science, Computer Vision, GAN, NLP, CHATGPT, GEMINI, Stable Diffusion, PyTorch, TensorFlow, LangChain, LlamaIndex, real-time chatbot agents, customer recommendation systems, churn modeling, dynamic pricing, fraud detection, and image recognition?
Let's talk.
At Google Brain Team, I was developing the TensorFlow library that is the most popular machine learning library. I love the using TensorFlow because I know the infrastructure very well. I have been working on Artificial Intelligence topics for about 4 years. I 'm following latest papers from AI projects and even have a blog that I review. I have also contributed several various open source AI projects, such as jax, flax, fastai, etc.
I have direct experience in the following technologies/topics:
✅ Machine Learning (Deep Learning, Clustering, Classification, Regression, SVM, PCA, KNN, etc)
✅ Computer Vision (Image Classification, Object Detection, Object Tracking, Image Segmentation, GANS, Pix2Pix, StyleGAN, etc.)
✅ Natural Language Processing, (RNN, Transforms, Named-Entity Recognition, Sentiment Analyzing, Summarizing, SOA Models(Bert, GPT, T5))
My toolkit:
✅ TensorFlow (Core, Addons, Datasets, TensorBoard, TFLite),
✅ PyTorch,
✅ Scikit-Learn,
✅ Numpy,
✅ Pandas,
✅Matploblib,
✅ NLTK,
✅OpenCV,
✅Knet.jl,
✅Jax,
✅spaCy,
✅Hugging Face,
I love working on challenging topics and it is of immense significance to me personally to develop high-quality software. I am a process-orientated person and most of my customers find it useful to finish tasks effectively.
See the power of our Stable Diffusion tutors through glowing user reviews that showcase their successful Stable Diffusion learning journeys. Don't miss out on top-notch Stable Diffusion training.
“Andrei strived to understand my issues even prior to booking a session, and his delight in helping felt palpable. After our consultation, I felt confident about my next steps, and I genuinely recommend him to anyone looking for thoughtful, practical guidance.“
Alexandre Apolinário / Dec 2025
Andrei Müller
Stable Diffusion tutor
“We focused on diagnosing and resolving persistent access issues affecting the ProsperPro join site, which was intermittently returning access errors to visitors. The objective was to identify the root cause, validate the technical setup, and establish clear next steps to ensure stable site availability.
The session was productive and collaborative, resulting in a clear diagnosis and corrective action plan. The issue was determined to be configuration-related rather than a platform or code defect. With propagation completing, the site is expected to stabilize without further intervention.“
Larry Combs / Dec 2025
Olajide Olanrewaju
Stable Diffusion tutor
“Great C++ tutor! He explains concepts clearly, focuses on problem-solving, and adjusts the pace based on my level. The sessions were well-structured, and the practice questions really helped me understand the topics better. Highly recommended.“
Qanoo Taweel / Dec 2025
Dejan B.
Stable Diffusion tutor
“Great session with Joel going in depth into my portfolio projects which has really helped reinforce my learning through discussing what I've done. Joel shared many real world experiences relevant to my projects. Gems of production level insights that you can only get from someone who has AAA first hand experience like Joel. Highly recommended!“
Zeshan Rasul / Dec 2025
Joel Gompert
Stable Diffusion tutor
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Arrange regular session times with Stable Diffusion tutors for one-on-one instruction.
Frequently asked questions
How to learn Stable Diffusion?
Learning Stable Diffusion effectively takes a structured approach, whether you're starting as a beginner or aiming to improve your existing skills. Here are key steps to guide you through the learning process:
Understand the basics: Start with the fundamentals of Stable Diffusion. You can find free courses and tutorials online that cater specifically to beginners. These resources make it easy for you to grasp the core concepts and basic syntax of Stable Diffusion, laying a solid foundation for further growth.
Practice regularly: Hands-on practice is crucial. Work on small projects or coding exercises that challenge you to apply what you've learned. This practical experience strengthens your knowledge and builds your coding skills.
Seek expert guidance: Connect with experienced Stable Diffusion tutors on Codementor for one-on-one mentorship. Our mentors offer personalized support, helping you troubleshoot problems, review your code, and navigate more complex topics as your skills develop.
Join online communities: Engage with other learners and professionals in Stable Diffusion through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Stable Diffusion skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Stable Diffusion in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Stable Diffusion is continually evolving, staying informed about the latest developments and advanced features is essential. Follow relevant blogs, subscribe to newsletters, and participate in workshops to keep your skills up-to-date and relevant.
How long does it take to learn Stable Diffusion?
The time it takes to learn Stable Diffusion depends greatly on several factors, including your prior experience, the complexity of the language or tech stack, and how much time you dedicate to learning. Here’s a general framework to help you set realistic expectations:
Beginner level: If you are starting from scratch, getting comfortable with the basics of Stable Diffusion typically takes about 3 to 6 months. During this period, you'll learn the fundamental concepts and begin applying them in simple projects.
Intermediate level: Advancing to an intermediate level can take an additional 6 to 12 months. At this stage, you should be working on more complex projects and deepening your understanding of Stable Diffusion’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Stable Diffusion generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Stable Diffusion, contributing to major projects, and possibly specializing in specific areas within Stable Diffusion.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Stable Diffusion. Engaging with new developments, tools, and methodologies in Stable Diffusion is a continuous process throughout your career.
Setting personal learning goals and maintaining a regular learning schedule are crucial. Consider leveraging resources like Codementor to access personalized mentorship and expert guidance, which can accelerate your learning process and help you tackle specific challenges more efficiently.
How much does it cost to find a Stable Diffusion tutor on Codementor?
The cost of finding a Stable Diffusion tutor on Codementor depends on several factors, including the tutor's experience level, the complexity of the topic, and the length of the mentoring session. Here is a breakdown to help you understand the pricing structure:
Tutor experience: Tutors with extensive experience or high demand skills in Stable Diffusion typically charge higher rates. Conversely, emerging professionals might offer more affordable pricing.
Pro plans: Codementor also offers subscription plans that provide full access to all mentors and include features like automated mentor matching, which can be a cost-effective option for regular, ongoing support.
Project-based pricing: If you have a specific project, mentors may offer a flat rate for the complete task instead of an hourly charge. This range can vary widely depending on the project's scope and complexity.
To find the best rate, browse through our Stable Diffusion tutors’ profiles on Codementor, where you can view their rates and read reviews from other learners. This will help you choose a tutor who fits your budget and learning needs.
What are the benefits of learning Stable Diffusion with a dedicated tutor?
Learning Stable Diffusion with a dedicated tutor from Codementor offers several significant benefits that can accelerate your understanding and proficiency:
Personalized learning: A dedicated tutor adapts the learning experience to your specific needs, skills, and goals. This personalization ensures that you are not just learning Stable Diffusion, but exceling in a way that directly aligns with your objectives.
Immediate feedback and assistance: Unlike self-paced online courses, a dedicated tutor provides instant feedback on your code, concepts, and practices. This immediate response helps eliminate misunderstandings and sharpens your skills in real-time, making the learning process more efficient.
Motivation and accountability: Regular sessions with a tutor keep you motivated and accountable. Learning Stable Diffusion can be challenging, and having a dedicated mentor ensures you stay on track and continue making progress towards your learning goals.
Access to expert insights: Dedicated tutors often bring years of experience and industry knowledge. They can provide insights into best practices, current trends, and professional advice that are invaluable for both learning and career development.
Career guidance: Tutors can also offer guidance on how to apply Stable Diffusion in professional settings, assist in building a relevant portfolio, and advise on career opportunities, which is particularly beneficial if you plan to transition into a new role or industry.
By leveraging these benefits, you can significantly improve your competency in Stable Diffusion in a structured, supportive, and effective environment.
How does personalized Stable Diffusion mentoring differ from traditional classroom learning?
Personalized Stable Diffusion mentoring through Codementor offers a unique and effective learning approach compared to traditional classroom learning, particularly in these key aspects:
Customized content: Personalized mentoring adapts the learning material and pace specifically to your needs and skill level. This means the sessions can focus on areas where you need the most help or interest, unlike classroom settings which follow a fixed curriculum for all students.
One-on-one attention: With personalized mentoring, you receive the undivided attention of the tutor. This allows for immediate feedback and detailed explanations, ensuring that no questions are left unanswered, and concepts are fully understood.
Flexible scheduling: Personalized mentoring is arranged around your schedule, providing the flexibility to learn at times that are most convenient for you. This is often not possible in traditional classroom settings, which operate on a fixed schedule.
Pace of learning: In personalized mentoring, the pace can be adjusted according to how quickly or slowly you grasp new concepts. This custom pacing can significantly enhance the learning experience, as opposed to a classroom environment where the pace is set and may not align with every student’s learning speed.
Practical, hands-on learning: Mentors can provide more practical, hands-on learning experiences tailored to real-world applications. This direct application of skills is often more limited in classroom settings due to the general nature of the curriculum and the number of students involved.
Personalized mentoring thus provides a more tailored, flexible, and intensive learning experience, making it ideal for those who seek a focused and practical approach to mastering Stable Diffusion.