Programming courses in C, C++ or Java languages. - Paris

Translated by GoogleSee original

Programming courses in C, C++ or Java languages.

From 12 € /h

Hello !

Do you want to learn programming or improve your skills in C, C++ or Java?

In this course, we progress according to your level, needs, and objectives. Whether you want to learn the basics, delve deeper into advanced concepts, or simply solve programming exercises and problems, I will guide you progressively and tailored to your needs.

You can contact me for, among other things:

- learn the basics of the language of your choice: C, C++ or Java;
- to delve deeper into more advanced concepts;
- to understand and correct a program;
- solving programming exercises;
- learn to analyze and solve programming problems;
- to prepare you for practical work, homework or exams.

The goal is to understand the concepts and logic of programming, and not just to reproduce code.

The course is therefore adapted to your situation: we can start from scratch, review certain concepts that you do not master sufficiently or work directly on the problems and exercises that pose a difficulty for you.

You choose the language and objectives, and we build the course according to your needs.

Location

Online from Morocco

About Me

Are you having trouble with programming? Are you a beginner in C, C++ or Java and don't know where to start? Do you understand the concepts in the course but struggle to apply them to the exercises?

I can support you gradually, adapting to your level and your goals.

I am a Computer Systems and Network Engineer, and I have been teaching programming languages online for several years. My computer science background includes algorithms, procedural and object-oriented programming, C++, C, Java, Python, software development, databases, and client-server architectures.

A method adapted to your level

I do not believe that one student must necessarily follow the same path as another.

At the beginning of a session, I therefore seek to understand your level and to verify the knowledge necessary to address the subject.

If certain fundamentals are not sufficiently mastered, we will review them together before moving on. The goal is to avoid simply "moving on" to the next concept when a previous difficulty might be holding you back.

Understand before you memorize

In programming, knowing the syntax of a language is not enough. Above all, you need to understand how to think about a problem and how to build a solution.

Therefore, I prefer:

- simple and progressive explanations;
- concrete examples;
- exercises adapted to your level;
- solving problems step by step;
- active participation of the student;
- Regularly checking for understanding.

I also encourage you to explain your own reasoning and propose your solutions. This allows me to pinpoint precisely what is understood and what still needs to be explained.

C, C++ or Java programming

I can assist you with, among other things:

- the basics of programming;
- algorithms;
- programming in C, C++ or Java;
- procedural programming;
- object-oriented programming;
- understanding and correcting programs;
- solving programming exercises and problems;
- Support in your learning and projects.

The courses are conducted via videoconference and can be adapted to your level, whether it is a beginner's course, a refresher course, or a specific need.

My goal is simple: to help you understand programming and gradually become capable of solving problems on your own.

Education

• State engineering degree in Computer Systems & Networks;
• Teaching diploma;
• Diploma in educational consulting;
• Experience in academic university research.

Experience / Qualifications

• Programming language teacher;
• Webmaster of several technology websites;
• IT Researcher and Self-Employed Entrepreneur.

Age

Adults (18-64 years old)

Student level

Beginner

Intermediate

Advanced

Duration

120 minutes

The class is taught in

Arabic

French

English

Skills

Java

C - c++

Computer programming

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Youssef

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Matías

4.85

(13)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Adam

4.85

(13)

Learn to code with method and logic
Whether it's to succeed in the NSI (Digital Sciences and Technology) specialization in high school, design personal projects, or prepare for higher scientific studies, mastering code relies on solid algorithmic thinking. I help students understand the structure of programming languages and the logic of data.

Subject areas and languages taught:

Algorithms & Logic: Designing data structures and solving problems.

Programming Languages: Python, C/C++, C# and Java.

Data Management: Analysis and SQL queries / databases.

Basic Web Development: HTML & CSS for creating structured pages.

The goal is to take the student from simply writing code to true autonomy in development.

Ahmed

4.85

(13)

Python is the programming language these days. It is simple, nice and almost all modern applications use it. With Python, we can now create artificial intelligence models that reduce human effort and give us more accurate and reliable results. The Java and C languages are not lacking in importance, they also make it possible to create applications optimized in terms of RAM.

The composition of the course depends on the level of the student and his own objectives. The first session is a one-hour evaluation session which allows the diagnosis of the level and the needs of the student. From this diagnosis we establish together a program that we will follow during our course.

Generally the course allows the student to assimilate:
* Predefined Data Types & Variables;
* Conditional Structures & Loops;
* Functions ;
* Object-oriented programming (OOP);
* Digital engineering;
* An introduction to databases (Examples and uses)
* Relational Algebra
* LDD, LCD, LMD, LCT
* SQL queries (SELECT, UPDATE, ...)
* Creation of a database and automation of queries using the Python language
* Handling files (TXT, Excel, CSV, JSON, Word);
* Data science;
* Introduction and some applications of Artificial Intelligence.

I am waiting for you to start this adventure.

Adam

4.85

(13)

doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

Enrique

4.85

(13)

Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.

Gaëlle

4.85

(13)

While adults are still debating whether kids should use AI, they are already using it.
The question isn't "should they?" it's "how do we do it intelligently?"

In this course, your child will discover:
✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't
✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it
✓ What LLMs are (Large Language Models): in language they understand, not tech jargon
✓ Create with AI: custom avatars, interactive stories, real projects using real tools
✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do?
✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life

Why this is different:
Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI.
Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits.
And, more importantly: that they can control how they use it.

What they take home:
Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace

For curious kids asking "How does ChatGPT actually know things?"

Giuliano

4.85

(13)

Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

Do you want to create your own software?
Work with data or images?
Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!

Salah

4.85

(13)

Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Roger

4.85

(13)

Are you looking to deepen your knowledge of physics or master advanced techniques in Python programming? This course is designed to help you achieve a level of academic and technical excellence, whether you are a high school student, university student or professional looking to develop your skills.

With an interactive and effective teaching approach, you will benefit from personalized support to overcome obstacles, grasp complex concepts and improve your performance. Whether it is to succeed in difficult exams, high-level competitions or to create powerful applications in Python, this course will provide you with all the tools necessary to achieve your goals.

🎯 Why Choose This Course?
Advanced and Expertise Level: In-depth content and effective methodology to master complex topics in physics and programming.
Personalized Courses: Sessions adapted to your needs, your pace and your level.
Interactive Online Learning: Dynamic online courses with screen sharing and audio interaction for enjoyable and engaging learning.
Concrete Projects and Practical Applications: Development of practical projects to implement theoretical concepts.
Intensive Preparation for Exams and Competitions: Rigorous training with complex exercises and exam simulations to guarantee your success.
Flexibility and Comfort: Learn from home, according to your schedule, without having to travel.

🔬 Advanced Physics – From High School to University
This module offers a complete and in-depth program to prepare you for demanding secondary school exams, preparatory classes and scientific university courses:

1. Secondary Physics (High School and Preparatory Classes)
⚙️ Classical Mechanics: Kinematics, dynamics, Newton's laws, energy and work, oscillations.
🌊 Waves and Vibrations: Wave propagation, interference, diffraction, acoustics.
⚡ Electricity and Magnetism: Electric circuits, electrostatics, magnetostatics, electromagnetic induction.
🔦 Optics: Geometric optics (lenses, mirrors), wave optics (interference, diffraction).
🌡️ Thermodynamics: Laws of thermodynamics, thermodynamic cycles, entropy, changes of state.

2. University and Advanced Physics
🔄 Analytical Mechanics: Lagrangian, Hamiltonian, and generalized coordinates.
🌐 Advanced Electromagnetism: Maxwell's equations and the propagation of electromagnetic waves.
🧪 Quantum Physics: The postulates of quantum mechanics, the wave function, and the Schrödinger equation.
☢️ Nuclear and Particle Physics: The structure of the nucleus, radioactivity, and fundamental interactions.
🌌 Special Relativity: Lorentz transformations, time dilation, and length contraction.

3. Intensive Preparation for Exams and Competitions
📘 Scientific methodology: Learn to analyze statements, structure responses and write clearly and precisely.
📝 Application exercises and past papers: Intensive training to master the concepts and pass your exams.
🔎 Solve complex problems with detailed explanations and effective strategies.
⏰ Time management: Practical tips to improve your time management during exams.

🐍 Advanced Python Programming – Focused on Efficiency
This module will teach you how to program efficiently and effectively in Python, with an emphasis on best practices and advanced techniques:

1. Mastering Advanced Concepts in Python
🔠 Advanced Syntax and Best Practices: Deepening of Python concepts.
📦 Object-Oriented Programming (OOP): Abstract classes, interfaces, and design patterns in Python.
🔄 Functional Programming: Using lambda, map, filter, reduce, generators and iterators.
⚡ Asynchronous Programming: Implementing asyncio for fast and responsive applications.
🧪 Unit Testing and Code Quality: Use of pytest, code coverage, and CI/CD.

2. Performance Optimization
🚀 Algorithm Optimization: Analysis of algorithmic complexity and use of efficient data structures.
⚙️ Profiling and Debugging: Performance evaluation with cProfile and code improvement.
🔒 Security and Robustness: Writing secure code and handling exceptions appropriately.
3. Practical Projects and Advanced Applications
🌐 Web Applications: Building high-performance web applications using Flask and FastAPI.
📊 Data Science and Machine Learning: Exploitation of Pandas, NumPy, Scikit-learn and TensorFlow.
🕸️ Advanced Web Scraping: Complex data extraction using BeautifulSoup and Selenium.
🤖 Automation and Efficient Scripts: Automation of tasks and development of efficient scripts.

🧑‍🏫 Methodology and Pedagogical Approach:
Learning by doing: Each theoretical concept is directly implemented through practical exercises.
Interactive Online Teaching: Using audio and screen sharing for seamless communication and dynamic learning.
Personalized monitoring: Regular support to assess your progress and answer all your questions.
Concrete projects: Development of complete projects to apply your programming skills.
Motivation and Confidence: A positive and encouraging approach to build your confidence in your abilities.

🎓 For whom?
This course is intended for:

- High school and preparatory class students who aspire to academic excellence.
- University students in science and computer science wishing to deepen their knowledge.
- Candidates for scientific competitions who are preparing for physics and programming tests.
- Developers looking to improve their advanced Python skills.
- Researchers and engineers who use Python for complex scientific applications.

🔔 Register now! Don't miss the opportunity to master advanced physics while developing skills in optimized and efficient Python. Join our program "🚀 Advanced Courses - 🔬 Physics from High School to University & 🐍 Advanced Python Programming Focused on Efficiency!" and progress at your own pace with confidence and motivation!

Baia

4.85

(13)

I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.

Hayat

4.85

(13)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Amr

4.85

(13)

Private Programming Lessons for you / your family / your company employees
Programming Tutor – IGCSE & Computer Science Subjects
Deeper understanding, stronger results

• Lecturer at the American University AUC
• Over 20 years of experience in training students for government employees, oil companies (BP), food companies (Nestle), banks (CIB), and telecommunications companies (Vodafone).

• Teaching curricula, syllabuses, courses:
o IGCSE (Computer Science 0478, ICT 0417)
o Programming and computer courses for all educational levels (from primary to university)
o Microsoft Windows, Word, Excel, PowerPoint, Outlook, MS-Project
o Programming, C, C++, VB.NET, C#, Python, Database, SQL, MQL, VBA
o HTML, CSS, JavaScript, Angular
o Different database systems
o Data analysis using Excel
o Computer and Information Colleges Curricula
o Using artificial intelligence in life and work

• Master office applications to improve your job performance.
• Prepare yourself to work as a Front-End / Back-End / Full Stack Developer
• Theoretical and practical training for market requirements
• Don't miss out on technology. Lessons are designed for the elderly, in a simple and understandable way (use of computers and their programs, use of mobile phones, dealing with the Internet and social media).
• Lessons are available in person or online.

Farouk

4.85

(13)

These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework

Ammar

4.85

(13)

A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.