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Adrian Segui
Rnn tutor
US$25.00 /15 min**📝 Profile Context / Summary** With 10+ years across enterprise IT and global freelancing, I am an AI-Stack Architect—not just a full-stack developer. In 2026, the industry has shifted decisively: software is no longer just written; it is architected, governed, and continuously learned. The most valuable engineers are no longer those who simply write code, but those who can turn code into cognition—engineers fluent in the AI-stack. I am that engineer. I design and build agentic platforms—systems where AI doesn't just assist but actively plans, builds, tests, and releases software. I have successfully delivered complex solutions across Medical, Fintech, Employee Management, and SaaS industries, handling everything from AI-native frontends to hyper-scalable microservices with autonomous agent orchestration. **🤖 AGENTIC AI & MACHINE LEARNING** 2026 is the breakout year of AI inferencing—where trained models generate predictions and outputs from new data. Most AI computing is now spent on inference rather than training. I specialize in: Agentic AI & Orchestration: LangChain, LlamaIndex, AutoGen, CrewAI—building multi-agent systems that plan, act, and adapt in real time. Full-stack agent platforms combining proprietary training data, planning models, and custom actuation layers. Generative AI & LLMs: OpenAI GPT-4/API, Google Gemini, Anthropic Claude, HuggingFace Transformers. Retrieval-Augmented Generation (RAG) with vector databases (Pinecone, Chroma, Weaviate, FAISS). AI-Native Development: 42% of committed code is now AI-generated, projected to reach 65% by 2027. I don't just use AI tools—I orchestrate AI agents across the entire SDLC: planning, design, build, test, deployment, and maintenance. Deep Learning & Classical ML: TensorFlow, PyTorch, CNNs (Computer Vision), RNNs/LSTMs (Time-Series/NLP), Scikit-learn, Pandas, NumPy. Model Deployment & Optimization: Model compression, quantization, edge computing, cost-per-prediction optimization. AI Governance & Security: AI-generated code carries roughly double the security risk violations of human-written code. I implement robust governance, testing, and security controls for AI systems. **⚛️ MODERN FRONTEND** React remains the most widely used UI library, with 67% of new enterprise React projects now built on Next.js—a 300% increase since 2023. React Server Components are now the default: Core: React 19, Next.js 16 (App Router, Server Components, Turbopack), Remix, Svelte 5 (runes), Astro. Styling: Tailwind CSS, shadcn/ui (1.87M weekly downloads), Framer Motion, Material-UI. State: Zustand (35% adoption, 35ms updates) vs Redux (38% adoption, 65ms), TanStack Query, Jotai. Build Tooling: Vite 8 with Rolldown (Rust-based, 10-30x faster builds), Turbopack. TypeScript: Used by 38% of professional developers, required in 72% of frontend job postings. **📱 MODERN MOBILE** React Native's New Architecture (stable since 2024) delivers significant performance improvements through synchronous native module calls: Frameworks: React Native (Expo), NativeScript, Flutter. Native: iOS (Swift/SwiftUI), Android (Kotlin & Jetpack Compose). Emerging: GPU-powered rendering for consumer and enterprise apps. **⚙️ MODERN BACKEND & API** Runtimes: Node.js (NestJS, Express), Bun, Deno, Python (FastAPI—57.9% developer usage, up 7% from 2024), Java (Spring Boot 4.0—modularized, Java 25 LTS support). Spring AI 1.0: Built-in support for integrating LLMs and AI services into enterprise Java applications. API Design: RESTful, GraphQL (Federation), gRPC, Webhooks, WebSockets. Event-Driven: Apache Kafka, RabbitMQ, AWS SNS/SQS. **☁️ DEVOPS & CLOUD (2026 Standard)** Cloud-native and Serverless adoption has surpassed 70% penetration in enterprise IT. Multi-cloud is now the standard—Gartner projects over 75% of cloud customers will adopt this model: Cloud: AWS, GCP, Azure (multi-cloud architecture). Containerization & Orchestration: Docker, Kubernetes (K8s), Helm. Serverless: AWS Fargate, Lambda, Cloudflare Workers—extending to data pipelines, real-time streaming, and event-driven microservices. IaC: Terraform, AWS CDK, Pulumi. CI/CD: GitHub Actions, GitLab CI, ArgoCD, Jenkins. **🗄️ DATABASES & SEARCH** Relational: PostgreSQL (PostGIS), MySQL, SQLite. NoSQL: MongoDB, DynamoDB, Firebase. Vector (AI): Pinecone, Chroma, Weaviate (for RAG and semantic search). Search: Elasticsearch, Algolia, Meilisearch. Caching: Redis, Memcached. **🔗 CRM, AUTOMATION & INTEGRATION** In 2026, the CRM market is consolidating around Salesforce, Microsoft, ServiceNow, and HubSpot as a durable challenger. Both platforms have invested heavily in agentic AI, predictive intelligence, and conversational AI: CRMs: Salesforce (Apex), HubSpot (Agentic Engagement Object), Zoho. Low-Code/No-Code: Gartner forecasts the low-code market at $44.5 billion in 2026, with 75% of new enterprise apps built on low-code platforms. Automation: VBA, Excel Macros, Google App Script, Bubble.io, n8n, Make, Zapier. Citizen Development: 80% of low-code users are now "citizen developers". **🚀 Why Partner With Me in 2026?** The software industry has crossed a clear threshold in 2026. Generative AI is no longer just helping developers write code faster—it is reshaping how software is planned, built, tested, and delivered. The role of the developer has evolved from coder to curator of intent, constraints, and outcomes. **I bring:** 10+ years of battle-tested engineering across the full spectrum. Agentic AI fluency—the ability to orchestrate AI agents across the entire SDLC. Systems thinking and architectural judgment—skills that AI cannot replace. Security-first mindset—AI amplifies what's already there; where code quality is managed, AI accelerates delivery; where it isn't, it accelerates technical debt and security exposure. Whether you need an AI-native application, a microservices overhaul, an agentic workflow orchestration, or an intelligent CRM integration—I deliver professional, scalable, and governable solutions. Let's architect intelligence together. **Contact me today.**
- Rnn
- PHP
- Python
- Android
- Java
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- C++
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- Node.js
- MongoDB
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- Elasticsearch
- Continuous Integration
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- VHDL
- VMware
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- Full Stack
- Docker
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- Google Cloud Platform
- Kotlin
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- HubSpot
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- React Native
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- iOS
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- Next.js
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- PyTorch
- Flutter
- Zoho crm
- Transfer learning
- OpenAI
- Event-Driven Architecture
- MLOps
- Astro.js
- Express.js
- AWS
- Scikit-learn
- Prompt Engineering
- Langchain
- Generative AI
- Google gemini
- Pinecone
- Weaviate
- Crewai
Varun Jewalikar
Rnn tutor
US$15.00 /15 min
Hi! I love Java, Python, Javascript, distributed systems, large scale systems, machine learning, natural language processing and image processing. My work has been featured on the AWS blog (https://tinyurl.com/chaosrunner), The Guardian (https://tinyurl.com/topvocab) , Billboard.com (https://tinyurl.com/topprofane) and other print/digital publications. I also own Amazon's chaos testing framework called AWSSSMChaosRunner (https://github.com/amzn/awsssmchaosrunner). I am a Senior Engineer at Amazon's Prime Video and have worked on scaling backend systems to millions of transactions-per-second, utilising various cloud technologies and primarily working with Java, Kotlin and Javascript. This involves image/audio/text processing systems, creating & managing databases/APIs for mobile/web applications and everything in between. I have 15yrs+ experience with backend engineering, cloud tech, nlp, signal processing and image processing. I can help you with any of these topics. I also love hackdays and have attended 20 hackdays in Europe in the last couple of years and collaborated with beginners/experienced developers on different kinds of projects. Thanks for reading and hope to talk to you soon!
- Rnn
- Python
- MongoDB
- Machine learning
- Data Science
- JavaScript
- Deep Learning
- Node.js
- Flask
- Image Processing
- D3.js
- Matplotlib
- Amazon EC2
- CUDA
- Amazon S3
- Responsive Design
- NoSQL
- npm
- Front-End
- Bootstrap
- NLP
- Data Visualization
- PyMongo
- Webpack
- Caffe
- AWS DynamoDB
- Convolutional neural networks
- Word2Vec
- Doc2vec
- Shrine
- Aws elastic beanstalk
- AWS CDK
- AWS
Shahrukh Khan
Rnn tutor
US$15.00 /15 minAn accomplished PHP Developer specialising in Laravel with extensive experience in the full life cycle of the software design process including requirements definition, prototyping, proof of concept, design, interface implementation, testing and maintenance. xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx IF I CAN'T HELP YOU I WILL PROCESS FULL REFUND xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx =============================== Areas covered in web development =============================== • Creating Online Portals • Develop Local Search Engines • Streaming Videos • Broadcast Live Videos • Generating Reports • Sending SMS • Creating Blogs and discussion Board • Integrating social and transactional APIs whether it is for mailing or sending SMS. My skills include but not limited to: • PHP, NodeJS • SQL, MySQL, MongoDB • JavaScript, jQuery, ReactJS, React Native, VueJS • HTML5, Bootstrap 3, Bootstrap 4, Bootstrap 5, Material Design • CSS3, SASS, LASS, • Laravel, Codeigniter, OpenCart, Wordpress • Linux System Administration
- Rnn
- HTML/CSS
- PHP
- jQuery
- Ubuntu
- React
- JavaScript
- Vue.js
- SQL
- MySQL
- WordPress
- Linux
- Bash
- CodeIgniter
- Shell
- Laravel
- Amazon EC2
- Amazon S3
- Elasticsearch
- CentOS
- Cloud
- Front-End
- MariaDB
- Kibana
- Logstash
- Amazon RDS
- Javascript patterns
- Neural Networks
- DigitalOcean
- Microsoft SQL Server
- Deep Learning
- Front end workflow
- TensorFlow
- Convolutional neural networks
- Linux System Administration
- Server-Side Development
- Cnn
- AWS
Johnny (Yoni) Svechinsky
Rnn tutor
US$0.00 /15 minI'm well-versed with startups since the beginning of my software career. As such, I appreciate the effectiveness and value regular sync-ups bring to a project. Cryptocurrency and smart contracts are my passion and focus. Favorite Book: Godel Escher Bach
- Rnn
- Java
- C#
- C++
- SQL
- Bash
- PostgreSQL
- Amazon EC2
- Physics
- Windows Server
- Full Stack
- Data Science
- NLP
- Chrome Extension
- Rust
- AWS Lambda
- Truffle suite
- Python
- Django
- Flask
- Database
- API
- Shell
- Pandas
- Machine learning
- Zsh
- React
- Amazon RDS
- JavaScript
- Neural Networks
- Microsoft SQL Server
- Blockchain
- Redux
- Cryptocurrency
- Serverless
- Solidity
- Gensim
- PyTorch
- Zappa
- NestJS
- Vue.js
- AWS
RamKumar Manoharan
Rnn tutor
US$20.00 /15 minAgentic AI Architect | Designing Autonomous AI Systems, Multi-Agent Workflows & Enterprise GenAI Solutions I specialize in architecting and building next-generation Agentic AI systems that combine Large Language Models (LLMs), autonomous agents, retrieval systems, and workflow orchestration to solve real-world business problems at scale. My work focuses on creating intelligent AI ecosystems capable of reasoning, planning, tool usage, memory management, and multi-step decision making across enterprise environments. With 16+ years of experience in AI, Machine Learning, Data Engineering, and Generative AI, I have designed and implemented production-grade AI solutions spanning AI Agents, RAG systems, Knowledge Graph integration, AI copilots, intelligent automation, and multi-agent orchestration frameworks. Key Areas of Expertise Agentic AI System Design & Architecture Multi-Agent Collaboration Frameworks Retrieval-Augmented Generation (RAG) Knowledge Graph + LLM Integration AI Copilots & Autonomous Workflows Prompt Engineering & Reasoning Systems AI Evaluation & Hallucination Reduction LLM Fine-Tuning & Optimization AI Workflow Automation Enterprise AI Solution Engineering Conversational AI & AI Assistants AI Governance, Safety & Reliability Technologies & Frameworks Python, FastAPI, Streamlit LangChain, LangGraph, CrewAI, Semantic Kernel OpenAI GPT, Claude, Gemini, Llama, Mistral Amazon Bedrock, Azure AI Foundry, AWS SageMaker ChromaDB, Pinecone, FAISS, Weaviate Neo4j Knowledge Graphs Hugging Face Transformers Docker, Kubernetes, APIs, MCP-based Architectures Vector Databases & Embedding Pipelines AI Monitoring & Evaluation Frameworks Areas I Mentor & Consult On Building AI Agents from Scratch Enterprise Agentic AI Architecture RAG Pipeline Development Multi-Agent System Design LangGraph & CrewAI Implementations Knowledge Graph for LLMs AI Product Architecture Generative AI Project Guidance AI Startup Technical Strategy Production Deployment & Scaling of AI Systems I actively mentor developers, startups, engineers, and enterprises in transforming AI concepts into scalable intelligent systems with a strong focus on practical implementation, architecture clarity, and industry-ready solutions.
Shailesh Nair
Rnn tutor
US$0.00 /15 minShailesh Nair is from Kerala, India where i work as Senior Engineering Manager and as a Senior Full Stack Developer using multiple technologies based on the requirement of Nordic clients.Below are some of the projects that i have worked, more can be seen in my Linkedin profile. 1. Have worked with Norwegian hedge funds to develop dynamic custom bars and real time streaming analytical app in C++,C#, Python, Spark, Kafka, Apache parquet, IQFeed API to process tick by tick data based on the mathematical indicators and oscillators. 2. Have worked for Norwegian based Renewable Energy Trading firms to build a market place for producers and consumers to trade and buy certificates, have used block chain frameworks like Polkadot (Substrate) and languages like TypeORM, reactJS, highcharts to build GUI and database capabilities using microservice architecture which maintained data in Postgres and SQl Azure (blobs and Tablestorage). 3. Have worked in building SASS web app to manage different community centres in sweden based on the languages like Php, Laravel, Mysql DB, etc. 4. Developed ETF Analysis Apps using C#, Power BI, MultiCharts and IQFeed API.
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See the power of our Rnn tutors through glowing user reviews that showcase their successful Rnn learning journeys. Don't miss out on top-notch Rnn training.
“Excellent Assist, ...Adrian once more was able to help me resolve the problem I was encountering with my Django / python APP. He is highly knowledgeable, I will certainly continue to employ his mentorship in the future.“
Hobby Williams / Apr 2026
Adrian Segui
Rnn tutor
“Sean is simply amazing! He resolved my task with React and TypeScript so fast and smooth. He is very very smart and knowledgeable. I highly recommend him. And he always give the best solutions. He is just born to be a programmer.“
vanya / Apr 2026
Sean Hurwitz
Rnn tutor
“Salako was incredibly helpful and reassuring, answering my many questions and follow-up questions with his expertise. He really helped me weigh each option and weigh the pros and cons of each one. Thank you!“
Aaron A / May 2026
SALAKO TESLIM
Rnn tutor
“Erick has been great at explaining system architecture for Python and Flask, as well as teaching me JavaScript. He is patient, knowledgeable, and explains everything clearly using a variety of tools and examples. I’ve really appreciated his teaching style and support.“
C / May 2026
Erick Alpizar Rivera
Rnn tutor
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Frequently asked questions
How to learn Rnn?
Learning Rnneffectively 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 Rnn. 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 Rnn, 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 Rnn 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 Rnn through forums and online communities. This engagement offers support, new learning resources, and insights into industry practices.
- Build real-world projects: Apply your Rnn skills to real-world projects. This could be anything from developing a simple app to contributing to open source projects. Using Rnn in practical applications not only boosts your learning but also builds your portfolio, which is crucial for career advancement.
- Stay updated: Since Rnn 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 Rnn?
The time it takes to learn Rnn 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 Rnntypically 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 Rnn’s more advanced features and best practices.
- Advanced level: Achieving proficiency or an advanced level of skill in Rnn generally requires at least 2 years of consistent practice and learning. This includes mastering sophisticated aspects of Rnn, contributing to major projects, and possibly specializing in specific areas within Rnn.
- Continuous learning: Technology evolves rapidly, and ongoing learning is essential to maintain and improve your skills in Rnn. Engaging with new developments, tools, and methodologies in Rnn 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 Rnn tutor on Codementor?
The cost of finding a Rnntutor 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 Rnn 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 Rnn 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 Rnn with a dedicated tutor?
Learning Rnn 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 Rnn, 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 Rnn 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 Rnn 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 Rnn in a structured, supportive, and effective environment.
How does personalized Rnn mentoring differ from traditional classroom learning?
Personalized Rnn 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 Rnn.
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