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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.
As a mentor, I can help you with **Technical Guidance** (assistance with coding, debugging, optimization), **Design Insights** (feedback on mechanics, level design, UI), **Asset Advice** (guidance on using time-saving assets/tools), and **QA** (thorough testing and bug tracking), among other topics.
I can answer questions on topics such as **Development Challenges** ("How can I optimize my game for better performance?"), **Design Decisions** ("How to improve the game UX?", "What mechanics can make my gameplay more engaging?"), and **Troubleshooting** ("Why is my game crashing on startup?", "Why is my game build failing?", "How do I fix this bug in my C# code?"), among other topics.
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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
8 years of experience in building and managing AI Systems.
* I develop end-to-end AI systems from requirements analysis, and data gathering to deployment, implementing new methods/research papers, and turning projects into research outcomes. I have achieved substantial performance in DL/ML/RL models for CV and NLP domain problems.
* Implementing and deploying projects handling and maintaining scalability, research papers as well as POCs.
* Project planning, requirements gathering, and analysing requirements to define the system's architecture, and implementation timeline.
* Provide mentoring to junior developers for ML projects.
Website: [roshantanisha.github.io/?ref=codementor](http://roshantanisha.github.io/?ref=codementor)
Summary:
I like to work on technology that is smart, simple and sophisticated. This sums up the vast knowledge required to work on projects to excel in a working product. I like to train Deep Neural Networks and understand them well.
I have mentored many students for their AI careers, teaching them Machine Learning and Mathematics. I am a mentor for the RFS (Reach for the Stars) Programme by the Aga Khan Education Board for India. I am an alumnus of this program as well.
I have a cumulative experience of 8 years working in the product and service-based industry for creating Machine Learning projects.
I have done some innovative work that I am proud of and am continuing to do so. I try my best to contribute my expertise to the project I am working on.
Highly Experienced in Machine Learning, Deep Learning, Advanced Deep Learning, Artificial Intelligence, and Algorithms, including models in the production environment, and deploying ML models. Working with top Indian colleges like BITS, niche NLP and CV, real-estate startups, MNCs, and Fortune top 20 companies, working with sensitive anonymized datasets, and creating state-of-the-art models are some of my achievements. I have strong and correct knowledge of Deep Learning concepts from the above experiences.
I have good knowledge of predictive analysis, machine learning methodologies, modeling and cluster analysis of large datasets. I am proficient in utilizing SQL in RDBMS concepts. Experience in project documentation (functional and technical), developers and assisting team with project reports and status reports. Highly motivated learner with great team working skills Strong interpersonal, leadership and customer service skills.
I have published paper at BMVC 2017: https://arxiv.org/abs/1710.05158
Deep Learning Blogger: https://medium.com/@tushar20
Technical Skills: Tools: Lucene, Latex, Eclipse
Languages: Java, C, C++, R, Python
Machine Learning Libraries: TensorFlow, Scikit-Learn, Theano, Keras
Relational Database Management Systems: MySQL
Web framework: HTML, CSS, JavaScript
Hi, I’m a senior developer and AI engineer with 7+ years on Codementor, rated 5 stars across 93+ reviews. I specialize in Python, AI/ML, Agentic Ai, computer vision, automation, and full-stack development.
I focus on practical, scalable solutions — from debugging tough issues to building complete systems. I’m passionate about offline AI, human-like UI automation, and efficient system design.
Latest AI agent app - KarnAGT
You can also visit my GitHub to know more about my latest ai product development capabilities.
If you need sharp technical help grounded in real-world experience, I’m here to help.
** Full refund if I fail to solve the problem.**
Experienced Software Architect, Data Scientist and a polyglot programmer with 9+ years of experience in writing production software code using NodeJS, Go, C# .NET, Python, R, JavaScript, Java, C/C++, and others .
In my stint at Research Lab, I worked on building Chatbots, Augmented Reality powered apps, Data Science and Machine Learning.
I love explaining complicated things in the most simple way.
Certified in UiPath and Microsoft Power Platform, with 15 years of IT experience in analysis, design, development, integration, testing, and maintenance .
Proven expertise in designing and implementing end-to-end Robotic Process Automation (RPA) strategies for web, desktop, mainframe, PDF, SharePoint, and Excel applications using UiPath, integrated with Microsoft and Google OCR technologies.
Delivered 100+ UiPath RPA bots globally, with major projects for US clients, ensuring on-time, quality delivery.
Skilled in Microsoft Power Platform – including Power Automate Flows and Power Automate Desktop.
Hands-on experience in LLM, RAG, Prompt Engineering, Agentic Automation, and AI Agents.
See the power of our Generative AI tutors through glowing user reviews that showcase their successful Generative AI learning journeys. Don't miss out on top-notch Generative AI training.
“Very knowledgeable person, and good communication explain many thing for me. Recommended for AI consultant.“
Dineth Ponnamperuma / Mar 2025
Nitin kalra
Generative AI tutor
“Recommend Silvia! She provided clear and structured explanations to my questions for me, as someone without much previous knowledge in the field, breaking down complex concepts like tokenization, transformers, attention mechanisms, and fine-tuning in an easy-to-understand way.
My worries, about integrating LLM chatbots into my project were solved.
Silvia is patient, knowledgeable, and passionate!“
David Bernhardt / Feb 2025
Silvia Magrelli
Generative AI tutor
“Denys is a very patient mentor. His way of teaching is to help students thoroughly understand how something works step by step, rather than teaching only to solve a specific problem. This is my first time working with Denys, and I will continue learning with him in the future.“
Wee Hong Koh / Jan 2026
Denys Kniaziev
Generative AI tutor
“I highly appreciate the support during my algorithms midterm preparation. The teaching approach was thorough and interactive, prioritizing a step-by-step understanding of complex topics. Furthermore, the PDF summary provided at the end is an excellent review resource, as he specifically pointed out the fundamental gaps in my knowledge, which was great“
Ava / Jan 2026
Kishore Muniyandi
Generative AI tutor
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Frequently asked questions
How to learn Generative AI?
Learning Generative AI 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 Generative AI. 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 Generative AI, 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 Generative AI 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 Generative AI through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
Build real-world projects: Apply your Generative AI skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Generative AI in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
Stay updated: Since Generative AI 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 Generative AI?
The time it takes to learn Generative AI 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 Generative AI 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 Generative AI’s more advanced features and best practices.
Advanced level: Achieving proficiency or an advanced level of skill in Generative AI generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Generative AI, contributing to major projects, and possibly specializing in specific areas within Generative AI.
Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Generative AI. Engaging with new developments, tools, and methodologies in Generative AI 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 Generative AI tutor on Codementor?
The cost of finding a Generative AI 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 Generative AI 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 Generative AI 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 Generative AI with a dedicated tutor?
Learning Generative AI 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 Generative AI, 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 Generative AI 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 Generative AI 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 Generative AI in a structured, supportive, and effective environment.
How does personalized Generative AI mentoring differ from traditional classroom learning?
Personalized Generative AI 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 Generative AI.