Counselling in Math and Statistics for Analytical Professionals

Van 72 € /h

Personalized counseling in mathematics, statistics, algorithms and economic theory, tailored specifically for programming, data analysis, finance, banking, and informatics. Strengthen your theoretical foundations to write better code, optimize financial and economic models, improve analytical precision, and confidently navigate complex problem-solving tasks.

We will identify your specific theoretical gaps and tackle them directly, using intuitive explanations, guided problem-solving, and focused discussions. My goal is to help you confidently apply mathematical and theoretical concepts in your daily work, projects, or analyses. Reach out to discuss your particular needs, challenges, or topics of interest—together, we’ll develop a customized plan to strengthen your skills and enhance your professional performance.

Locatie

Online vanuit Oostenrijk

Over

I am Vladimir, a doctoral candidate in Computational Biology in Vienna.
My main expertise fields are Physics and Mathematics, my primary passion is research, with a diverse background in Computational Quantum Mechanics, Machine Learning, and Computational Biology.

Opleiding

Bachelor in Applied Mathematics and Physics with honors — Moscow Institute of Physics and Technology

Master of Mathematics and Computer Science - Moscow Institute of Physics and Technology / Skolkovo Institute of Science and Technology

Leservaring

8 years experience of tutoring High School and University Students
6 years experience in conducting national competitions in Math and Physics

Leeftijd

Kinderen (7-12 jaar oud)

Tieners (13-17 jaar oud)

Volwassenen (18-64 jaar oud)

Senioren (65+ jaar oud)

Niveau van de leerling

Beginner

Gemiddeld

Gevorderden

Duur

60 minuten

De les wordt gegeven in

Engels

Russisch

Vaardigheden

Computer programmeren

Computer modellering

Counseling (universitair niveau)

Beschikbaarheid typische week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Mathematics and Physics for University or High School Students

50 € /h

In our classes, we begin by discussing your goals and creating a study plan that fits your needs. I teach a broad range of Mathematics and Physics topics at both the high school and university levels, and my teaching approach is highly adaptable. Whether you thrive on a deep, rigorous exploration of core concepts or prefer a practical, example-driven path that builds from the basics to more advanced material, I’m here to support your learning style. We can work together to aim for success on a specific exam or to develop a general understanding of the subject. Throughout our lessons, we’ll pinpoint the most effective strategies for achieving your objectives, whether you seek to master theoretical foundations or excel in practical problem-solving. Lessons are available in both English and Russian, depending on your preference.

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I’ve worked across frontend, backend, DevOps, and AI, building enterprise-grade systems for real-world applications — from large-scale microservices to cognitive AI platforms.

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Whether you are a beginner exploring your first “Hello World,” a professional improving your stack, or a researcher/developer exploring AI systems, I can guide you step-by-step — conceptually, practically, and strategically.

🧩 What You Will Learn
🖥️ Front-End Development

Master how to build responsive, interactive, and high-performance interfaces:

HTML / HTML5 – Structure, semantics, forms, accessibility

CSS / CSS3 / SCSS – Layout, animations, responsive design, Flexbox, Grid

Bootstrap / Tailwind / Material UI – Rapid design frameworks

JavaScript (ES6+) – Functional programming, event loop, closures, async/await

TypeScript – Strong typing, interfaces, decorators, generics

React.js / Next.js – Components, hooks, state management, routing, APIs

Angular (1.x to 17) – Modules, dependency injection, RxJS, advanced architecture

Vue.js (optional) – Reactive programming, lifecycle management

jQuery / AJAX – Legacy support and backend communication

Web Performance – Lighthouse, Core Web Vitals, PWA, caching strategies

⚙️ Back-End & Enterprise Development

Build scalable, secure, and intelligent server-side systems:

C / C++ / Data Structures / Algorithms / OOPS

Java / J2EE / Spring / Spring Boot / Spring Cloud / Hibernate / Struts / Wicket

Microservices Architecture – API gateway, service registry, inter-service communication

Node.js / Express / NestJS – Modern JavaScript/TypeScript backend

REST & SOAP Web Services – API design, security, documentation (Swagger / Postman)

Python (Flask / FastAPI) – REST APIs, ML pipelines, automation

Shell Scripting (Linux/Unix) – Automation, cron jobs, log parsing, DevOps scripting

PHP / Laravel / CodeIgniter – Classic web backend development

Containerization & Orchestration: Docker, Kubernetes, Helm

CI/CD & Cloud: Jenkins, GitHub Actions, Azure DevOps Pipelines

☁️ Cloud & DevOps Mastery

Learn to build, deploy, and scale applications on the cloud:

AWS (EC2, S3, Lambda, DynamoDB, API Gateway, ECS)

Azure (App Services, Functions, CosmosDB, DevOps)

Google Cloud (GCP, Vertex AI, BigQuery, Cloud Run)

Monitoring & Logging: ELK Stack (Elasticsearch, Logstash, Kibana), Grafana, Prometheus

Infrastructure as Code (IaC): Terraform, AWS CDK, Azure Bicep

Version Control & Collaboration: Git, GitHub, GitLab, Bitbucket

CI/CD Pipelines: Build, test, deploy automation, rollback, release management

📱 App Development

Develop mobile and hybrid apps end-to-end:

Android (Java/Kotlin) – UI/UX, activity lifecycle, API integration

Hybrid Frameworks: Ionic, Cordova, React Native

Progressive Web Apps (PWA) – Offline-first, caching, mobile optimization

Firebase Integration: Auth, Firestore, Cloud Messaging

🤖 Artificial Intelligence & Machine Learning

Learn how modern AI systems are built and deployed:

AI Fundamentals: Neural networks, supervised/unsupervised learning

Machine Learning with Python: scikit-learn, TensorFlow, PyTorch

Natural Language Processing (NLP): Transformers, BERT, GPT

Computer Vision: OpenCV, YOLO, Image Classification

AI APIs & Integrations: Google DialogFlow, Azure Cognitive Services, OpenAI API

🧬 Generative AI, RAG & Agentic Systems

Special focus on real-world AI integration and automation:

Generative AI Models (GPT, Claude, Gemini, Llama, Mistral) – Practical implementation

Prompt Engineering – Designing powerful, reusable prompt frameworks

Retrieval-Augmented Generation (RAG) – Hybrid search + generation architectures

Agentic AI Systems – Building autonomous multi-agent workflows (e.g., AutoGPT, CrewAI)

Agentic RAG – Contextual memory, chaining, and reasoning systems

LangChain / LlamaIndex – RAG pipelines, document loaders, embeddings, vector DBs

Vector Databases: Pinecone, Chroma, Weaviate, FAISS

Knowledge Graphs & Context Management – Enterprise data linking with RAG

AI App Deployment: FastAPI + Streamlit + LangServe + Docker

Copilot & AI Tools: GitHub Copilot, ChatGPT API, Code Interpreter, Vertex AI Studio

Google AI Developer Kit (ADK) – Edge AI, TensorFlow Lite, Coral, and model serving

Voice AI & Conversational Design: Dialogflow CX, OpenAI Assistants, ElevenLabs

🔬 Data, Testing & Quality

Database Systems: MySQL, PostgreSQL, MongoDB, Oracle, DB2, Redis

Database Design: ERD, normalization, indexing, performance tuning

Testing Tools: JUnit, Mockito, Selenium, Cypress, Postman

TDD / BDD Practices: Unit, integration, and end-to-end testing

Logging & Monitoring: ELK, Splunk, Prometheus

Performance Optimization: Profiling, caching, concurrency

🧩 Operating Systems & Scripting

Windows / Linux / Ubuntu / Unix Administration

File Systems, Permissions, Networking, Process Management

Shell Scripting / Automation / Log Analysis

System Security and SSH Hardening

🧠 Bonus Topics

Mathematics for Programmers – Logic, combinatorics, probability, graph theory

Game Development Basics: Unity, Phaser.js, HTML5 Canvas

AI Ethics, Data Privacy, Responsible AI Design

Automation Projects & Web Crawling / Scraping: BeautifulSoup, Selenium, Puppeteer

No-Code / Low-Code Integrations: Zapier, Make, AI automations

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Course Overview
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✅ Libraries for real-world tasks (e.g., pandas, matplotlib)

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Teaching Style
Hands-on learning: You’ll write code in every session.

Project-driven: Build mini-projects like calculators, data visualizations, or simple web apps.

Adaptable pace: Lessons tailored to your level and goals (academic, professional, or hobby).

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Students preparing for exams or computer science courses

Professionals wanting to automate tasks or analyze data

Curious learners who want to start coding as a hobby

Practical Details
📍 Online or in-person (depending on your location)

⏱ Flexible scheduling to fit your availability

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Lesson Structure
Each lesson consists of a combination of:
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Who is this suitable for?
• Absolute beginners
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What can you expect?
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-- Techniques --
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-- Contents --
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-- Level --
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