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Ashish
Modals tutor
US$15.00 /15 minAsk me anything :) I'll do my best guiding you in areas of front end development as well as back end development using JavaScript, Version Control System (Git) and best development practices. I'm an open source developer and has created several projects that are used by thousands of developers. I'm proficient in major frontend frameworks ie React, Angular and Angular JS. I've been to a lot of hackathons, won some of them nationally. Currently, I'm doing independent freelance projects and helping developers in area of web developement.
- Modals
- Node.js
- HTML/CSS
- Ruby on Rails
- jQuery
- MySQL
- Git
- Angular
- Meteor
- AJAX
- JSON
- Database
- API
- jQuery UI
- PostgreSQL
- Design
- GUI
- Version control
- GitHub
- Responsive Design
- OAuth 2.0
- Mongoose
- Repository
- Pipe
- Margin
- UI design
- Bootstrap
- MVC
- Web Development
- Requests
- BEM
- Grunt
- React
- Cross-Browser Compatibility
- Bootstrap 3
- Psql
- JavaScript
- Selectors
- Back-End
- Middleware
- Microsoft SQL Server
- Streams
- hapi.js
- Design thinking
- Performance Optimization
- RESTful API
- Express.js
Achin Sood
Modals tutor
US$10.00 /15 min
I am a full stack web developer working primarily on frontend using javascript (jQuery, react, redux). I have experience in developing a number of frontend plugins and ui libraries which could help in building the UX for almost all kinds of web applications
Tanisha Bhayani
Modals tutor
US$35.00 /15 min6 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 6 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.
- SQL
- Git
- Machine learning
- Computer Vision
- NLP
- Gunicorn
- Cython
- AI
- Python
- MySQL
- MongoDB
- Angular
- Flask
- PostgreSQL
- OpenCV
- Azure
- NumPy
- Matplotlib
- Pandas
- Tkinter
- Scipy
- Web Scraping
- TypeScript
- Scrapy
- GPU
- Web Development
- Docker
- React
- Google Cloud Platform
- Research
- Kubernetes
- Deep Learning
- TensorFlow
- Keras
- Responsive Web Development
- Cloud Functions
- Mobile App Development
- Deep Reinforcement Learning
- PyTorch
- Computer Vision Engineering
- Open Source Software
- OpenAI
- AWS SageMaker
- TensorFlow.js
- GPT
- Machine Learning Deployment
- Machine Learning Research
- GPT-3
- Deep Learning Pipeline
- Machine Learning System Design
- AWS
- OpenAI APIs
- Machine Learning Frameworks
- GPT-4
- Machine Learning Models
- AI Chatbot
Ahmet Özlü
Modals tutor
US$15.00 /15 min### About Me I am an experienced **AI and Computer Vision Specialist** with a **Master’s degree in Computer Vision** and a recipient of the **Google Inside Look 2019 Award**. My expertise lies in developing advanced solutions in **Deep Learning, Machine Learning**, and **Image Processing**, with a strong focus on building and optimizing AI-driven systems. I have successfully built AI teams using **Gemini**, **Groq**, and **Phidata**, enabling multi-agent collaboration for tasks such as **data collection, processing, and analysis**. Additionally, I specialize in **Face Recognition**, **Object Detection**, and **Video Analysis**, leveraging technologies like **TensorFlow**, **Keras**, and **OpenCV** to deliver impactful solutions. ### Key Achievements * Optimized an object detection pipeline for a startup, reducing processing time by 40%. * Built and deployed end-to-end ML models for image classification in production environments. * Guided junior developers in designing and training custom CNNs, improving team performance. ### Mentorship Philosophy I excel at breaking down complex AI concepts into digestible steps, empowering both beginners and experienced developers. Whether you're starting your journey in AI or looking to fine-tune and scale your solutions, I’m here to guide you with practical, hands-on advice. * **GitHub**: [github.com/ahmetozlu](https://github.com/ahmetozlu) * **Papers**: [Facial Expression Recognition](https://ieeexplore.ieee.org/document/8404767/) | [Automatic Age Estimation](https://ieeexplore.ieee.org/document/8404549/)
- PHP
- Android
- C#
- SQL
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- Database
- Arduino
- Object-Oriented Programming
- Blockchain
- VR
- Ethereum
- Solidity
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- Python
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- Jenkins
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- Spring data
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- Swagger
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- TensorFlow
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- RESTful API
- OpenAI
- Hibernate ORM
- MLOps
- Huggingface
- AI
- Langchain
- LLM
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- Google gemini
Alex V
Modals tutor
US$99.00 /15 minFull Stack Developer for 9 Years Currently Teaching on Codementor Exclusively on Wednesdays and Fridays. Please DM to schedule Full Stack Javascript Developer React + Redux + Node.js. Strapi.io Winner of multiple Ethereum Hackathons (EthGlobal, Gitcoin, AAVE, theGraph, Matic, Polygon, Badger) DeFi Yield Farming Strategy Developer Former Lead Dev at Ethereum Crypto / DeFi Startup Experienced in developing with Solidity, theGraph, Hardhat, Vyper, Brownie. Tons of Wordpress and some Python. Java during CS. Understanding of Bitcoin and Blockchain Technology (course at UNIMIB + experience) Bachelor in CS.
Gopal Chitalia
Modals tutor
US$20.00 /15 minI am [Gopal Chitalia](https://scholar.google.com/citations?user=QncMQEIAAAAJ&hl=en), a graduate student at Purdue University and working with Prof. [Jan Anders Mansson](https://www.purdue.edu/engineering/mdlab/mansson/) on fault detection in motors using deep learning in a joint project with Wistron. Additionally, I'm working with Prof. [Junjie Qin](https://engineering.purdue.edu/people/junjie.qin.1) on transfer learning application using LLMs for optimizing power networks. I have had the privilege of working at [Center for Building Science Lab](https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fcbs.iiit.ac.in%2F&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=UCjKsb98EbNq8jGvbf%2F5TEETyHMI1gnMx20lLBeQmog%3D&reserved=0) under the supervision of Prof. [Vishal Garg](https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.google.co.in%2Fcitations%3Fuser%3DvyH26MIAAAAJ%26hl%3Den&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=pDBa4RZtT0eg4rN%2FdvVtv3q%2F6goK1EEVT6%2F6UeGPcw4%3D&reserved=0). I have previously been a Research Assistant/Visiting ML Scholar at the [Smart Grid Research Unit](https://nam04.safelinks.protection.outlook.com/?url=http%3A%2F%2Fwww.sgru.eng.chula.ac.th%2F&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=UAp49aqIF2oxM3WIO5IS68gTyMLeYsKR5ENaosJMhvk%3D&reserved=0) (SGRU) under [Manisa Pipattanasomporn](https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fscholar.google.com.sg%2Fcitations%3Fuser%3D4W2KIQkAAAAJ%26hl%3Den&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=Pey86yYp3KpRPj9d9a97nzxLxQGMkQrN%2BFASqUqyheQ%3D&reserved=0) (Adjunct Faculty, Virginia Tech). In addition to my academic pursuits, I have also contributed to the industry in the domains of Energy Efficiency, IoT, and Machine Learning. I have worked at [ClevAir](https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fclevair.io%2Fen%2F&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=nonCkudNp3cFUL2CNs6rMHm0HyQXSnh9lhoJ76s5xus%3D&reserved=0) (Norway) as a **Data Scientist** and Growthworks.ai (CA, USA) as an **ML Scientist/Energy Demand Expert**. My research work on predicting short/long-term energy prediction in office/residential buildings using machine learning is published in [Applied Energy](https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.sciencedirect.com%2Fscience%2Farticle%2Fabs%2Fpii%2FS0306261920309223%3Fvia%253Dihub&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=V%2Bq5MVSeJ7deNpE%2F%2FEP1PYrsrEVWEH%2FwNK1yAG4CPlM%3D&reserved=0). The results improve the state-of-the-art results by 20-40%. I am also an active reviewer at Applied Energy. Furthermore, I have collaborated on a building-level dataset paper which has been published in [Nature Scientific Data](https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.nature.com%2Fsdata%2F&data=05%7C01%7Cgchitali%40purdue.edu%7C9ca93da4ba36440447b708db86ccdfe0%7C4130bd397c53419cb1e58758d6d63f21%7C0%7C0%7C638251986720958299%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=rtv6fVxtvuYsk5NAwwR8ujauC1AfX9cs32w4evIj%2BZU%3D&reserved=0). Previously, I have also worked with Prof. [Jyotirmay Mathur](https://scholar.google.co.in/citations?user=AmGPPL4AAAAJ&hl=en) at the [Centre for Energy & Environment](http://www.mnit.ac.in/dept_cree/index.php), MNIT Jaipur on Predicting time ahead heating/cooling energy demand HVAC systems. Moreover, as an independent research student, I also collaborated with Prof. [Praveen Paruchuri](https://scholar.google.com/citations?user=ILUqgKEAAAAJ&hl=en) of [Machine Learning Lab](https://mll.iiit.ac.in/), IIIT-H for Reinforcement Learning (RL) applications for controlling HVAC systems.
- HTML/CSS
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- Database
- Bash
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- Docker
- JavaScript
- Research
- Postman
- Dash
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- Airflow
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- Performance Optimization
- PyTorch
- Fastapi
- AWS
- Large Language Models
- Git
- Selenium
- NumPy
- Version control
- GitHub
- Pandas
- Machine learning
- Data Science
- Data Visualization
- Reinforcement Learning
- Deep Learning
- Data analytics
- TensorFlow
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Find your personal Modals tutor on Codementor today 
Users love our Modals tutors
See the power of our Modals tutors through glowing user reviews that showcase their successful Modals learning journeys. Don't miss out on top-notch Modals training.
“Thanks man! you already helped me to complete my task, also explain me what is the issue and you give me the solution. I was stuck in a task for around 3 days, a simple checkout with azure devops pipelines with lfs as submodule. and you gave me solution, even if i can't share the whole code. You are a wizard man! Thanks Highly recommend!“
Alejandro Zapeta / May 2025
Opeoluwa Lanre
Modals tutor
“In this lesson as well, Precious. was a great help: he clarified my doubts by clearly explaining the underlying concepts, supporting me with effective examples, and constantly encouraging me to give my best.“
none / May 2025
Nwoko Onyekachi Precious
Modals tutor
“Amazing is the one word that I would utilize to use this person. You were so patient and calm with my slowness in learning, and you were able to help so much in my problems. You not only took the time out to explain where the problems were stemming from, but how to resolve them and what I could do in the future. I 100 percent will contact you again if I have any issues or if anybody has any questions I would hands down recommend to you.“
Tiffany Myers / Jun 2025
Olajide Olanrewaju
Modals tutor
“I highly recommend Pazia as a tutor. She consistently looked for the most effective ways to help me grow, both technically and in my interview preparation. It was clear that she genuinely cared about helping me succeed and always tailored her approach to what would benefit me the most. Her dedication and insight made a big impact on my learning and confidence.“
Stella Chang / Jun 2025
Pazia Bermudez-Silverman
Modals tutor
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Arrange regular session times with Modals tutors for one-on-one instruction.
Frequently asked questions
How to learn Modals?
Learning Modals 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 Modals. 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 Modals, 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 Modals 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 Modals through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
- Build real-world projects: Apply your Modals skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Modals in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
- Stay updated: Since Modals 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 Modals?
The time it takes to learn Modals 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 Modals 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 Modals’s more advanced features and best practices.
- Advanced level: Achieving proficiency or an advanced level of skill in Modals generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Modals, contributing to major projects, and possibly specializing in specific areas within Modals.
- Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Modals. Engaging with new developments, tools, and methodologies in Modals 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 Modals tutor on Codementor?
The cost of finding a Modals 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 Modals 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 Modals 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 Modals with a dedicated tutor?
Learning Modals 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 Modals, 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 Modals 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 Modals 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 Modals in a structured, supportive, and effective environment.
How does personalized Modals mentoring differ from traditional classroom learning?
Personalized Modals 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 Modals.
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