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Find the Best Online Computer Programming Tutors & Teachers for Private Lessons

For over a decade, our private Computer Programming tutors have been helping learners improve and fulfil their ambitions. With one-on-one lessons online, you’ll enjoy high-quality, personalised teaching that’s tailored to your goals, availability, and learning style.

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1673 online computer programming teachers

Students' Choice

Khalil カル

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Japan
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4.9

69 reviews

(69)

19€

60-min

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5Students

Python for Beginners | Build Your First Project, Code with AI & Explore Machine Learning

Python for Beginners | Build Your First Project, Code with AI & Explore Machine Learning

Learn Python by building something you’ll actually use Ever wanted to code but had no idea where to begin? You’re in the right place. In these relaxed, one-on-one lessons, you’ll go from zero to writing real programs, with no experience required. Together, we’ll choose a project that fits your interests. Maybe it’s a video game you want to build or a quiz to challenge your friends, a chart built from your own spreadsheet, or a script that takes over a boring, repetitive task. Along the way, you’ll pick up the essentials (variables, loops, functions) and learn to read error messages without panic, so you can change your code with confidence. Where you can go next AI-assisted coding: Use tools like ChatGPT to brainstorm, decode errors, and improve your code, while learning to test its suggestions and explain how the final result works. Machine learning: Train a simple model on a real dataset and see how well it predicts. Your own project: Bring an idea from school, work, or a hobby, and we’ll break it into steps you can build at your own pace. Your instructor I’m an engineer with a master’s degree from Nagoya University and research experience in applied AI and computer vision. I explain every concept in plain language, then give you time to try it yourself with live feedback, so you’re never stuck alone. Ready to start? Send me a quick message and let's do your first coding project together.

George

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Egypt
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13€

60-min

/h

Learn Python, AI & Data Analysis Online | All Levels | Arabic & English

Learn Python, AI & Data Analysis Online | All Levels | Arabic & English

**Learn Programming, Python, Artificial Intelligence & Data Analysis with Practical Projects!** Are you looking to learn programming from scratch, improve your coding skills, or prepare for a future career in technology? I'm George Zakary, a Computer and Data Science graduate from Alexandria University and a programming instructor with hands-on teaching experience in Python, Data Analysis, Cybersecurity, and Backend Development. I offer personalized, interactive online lessons for students across Saudi Arabia, the UAE, Kuwait, Qatar, and other Gulf countries. **What can you learn with me?** - **Python Programming:** From basic concepts to functions, loops, data structures, and Object-Oriented Programming (OOP). - **Artificial Intelligence:** Introduction to AI, Machine Learning fundamentals, and practical applications. - **Data Analysis:** Learn to work with data using Python, Pandas, and practical examples. - **AI Automation:** Explore automation concepts and tools such as n8n. - **Backend Development:** Build web applications using Python and Flask. - **Cybersecurity Fundamentals:** Understand essential security concepts and safe computing practices. **Why choose my lessons?** My teaching approach focuses on simplifying complex technical concepts through real-world examples, live coding, practical exercises, and hands-on projects. Every lesson is adapted to your age, experience, learning pace, and personal goals. Whether you are a complete beginner, a school or university student, or a professional looking to develop new technical skills, I will help you learn step by step. **Lessons are available in Arabic or English, with clear explanations tailored to Arabic-speaking students.** **للطلاب في السعودية والإمارات والكويت وقطر وجميع دول الخليج:** أقدم دروس برمجة أونلاين باللغة العربية بأسلوب بسيط وعملي، سواء كنت مبتدئًا تمامًا أو ترغب في تطوير مستواك. سنتعلم خطوة بخطوة من خلال التطبيق العملي والمشاريع الحقيقية، مع خطة تعليمية تناسب مستواك وهدفك. **Start your programming journey today!**

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Farouk

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Algeria
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5.0

2 reviews

(2)

21€

60-min

/h

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1Students

Learn Object-Oriented Programming in JavaScript 🧠⚙️

Learn Object-Oriented Programming in JavaScript 🧠⚙️

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

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Roger Join

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France
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5.0

8 reviews

(8)

32€

60-min

/h

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4Students

🎓 Multidisciplinary Program – 📘 Mathematics, 🔬 Physics & 💻 Computer Science for All Levels!

🎓 Multidisciplinary Program – 📘 Mathematics, 🔬 Physics & 💻 Computer Science for All Levels!

Are you looking for personalized support to succeed in mathematics, physics or computer science? Whether you are a middle school, high school, university student or simply curious to learn, this multidisciplinary program is for you! 💡 Why Choose this Program? This course offers comprehensive, tailored support to help you: Strengthen your foundations and fill in your gaps. Understand theoretical concepts in depth. Master problem-solving methods. Develop your computer skills, from introductory to advanced programming. Prepare effectively for your exams and competitions. With a human, motivating and caring approach, you will learn at your own pace in a calm and encouraging environment, without pressure or judgment. 📘 Mathematics – For All Levels Mathematics may seem complex and abstract, but with the right method and clear explanations, it becomes logical and accessible. This module covers: Middle school level: Arithmetic, fractions, proportions, basic geometry, statistics. High school level: Algebra, functions, equations, analytical geometry, probabilities. Preparation for exams: Brevet, Bac, entrance exams for grandes écoles. Advanced Mathematics: Differential and integral calculus, matrices, sequences and series for university level. 🔬 Physics – From Understanding to Application Physics allows us to understand the world around us, from the laws of motion to electromagnetic phenomena. This module will guide you through: Middle and high school level: Mechanics, electricity, optics, thermodynamics. University Level: Analytical mechanics, advanced electromagnetism, quantum physics, statistical thermodynamics. Scientific Methodology: Knowing how to analyze a problem, formulate a hypothesis, apply physical laws and interpret the results. Practical Applications: Virtual experiences, interactive simulations to better understand theoretical concepts. 💻 Computer Science – From Basics to Advanced Skills In an increasingly digital world, mastering IT is essential. This module adapts to your level and your objectives: Introduction to Computers: Understand how a computer works, use office software (Word, Excel, PowerPoint). Programming Beginner: Learn to code in Python, JavaScript or C/C++ with clear explanations and practical exercises. Advanced Programming: Optimized algorithms, complex data structures, object-oriented programming. Project Development: Creation of web applications, automated scripts, simple video games. Preparation for NSI Exams: Complete support to pass the Digital and Computer Science tests. 🎯 Interactive and Motivating Teaching Dynamic Online Course: Learn from home with an interactive format using audio and screen sharing. Method Adapted to Your Pace: Each course is designed according to your level and your objectives. Practical Exercises and Concrete Projects: To apply theoretical concepts and learn while having fun. Personalized Monitoring: Regular support to monitor your progress and adapt the program to your needs. Encouragement and Motivation: A positive approach to building your confidence in your abilities. 🔔 For Who? This program is aimed at: Middle school and high school students wishing to strengthen their foundations or aim for excellence. University students in science or computer science looking to deepen their knowledge. Candidates for exams and competitions preparing for the Brevet, the Bac, or entrance exams to the grandes écoles. Passionate self-taught people who want to learn to program or better understand the scientific world. Adults in professional retraining wishing to acquire IT skills. 🚀 Ready to Succeed? Join the "🎓 Multidisciplinary Program – 📘 Mathematics, 🔬 Physics & 💻 Computer Science for All Levels!" and benefit from personalized support to achieve your goals. Whether you want to improve your grades, pass your exams or develop programming skills, this program will give you knowledge, confidence and motivation. Register today and take the first step towards success!

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Ammar

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Canada
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5.0

2 reviews

(2)

21€

60-min

/h

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2Students

Master AI, Machine Learning, Data Science, Python & Programming with a PhD Engineer and Professor | 25+ Years’ Expertise | All levels

Master AI, Machine Learning, Data Science, Python & Programming with a PhD Engineer and Professor | 25+ Years’ Expertise | All levels

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.

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Ali

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United Kingdom
5.0

2 reviews

(2)

52€

60-min

/h

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1Students

Machine Learning & AI Tutor | University Lecturer, MSc Distinction | Python, Coursework & Dissertations | Published Researcher

Machine Learning & AI Tutor | University Lecturer, MSc Distinction | Python, Coursework & Dissertations | Published Researcher

I teach machine learning, AI and Python online to university students, postgraduates, career changers and serious beginners across the UK and Europe. Lessons are in English. I hold an MSc in Electronics and Electrical Engineering with Distinction and I teach as a Visiting Lecturer on a Master's level module covering data analytics, machine learning and generative AI at a UK university. I also have two accepted international conference papers on deep learning for image classification. I set and mark postgraduate assignments myself, so I know where marks are won and lost on this kind of work. Who this is for Undergraduates and postgraduates on AI, ML, data science or computer science modules at any European university. Final year, Master's and thesis students working on a machine learning project. IB and A Level students moving into computing or engineering. Professionals retraining for data roles. Complete beginners who want to learn Python properly rather than copying it from videos. I work with students on UK, IB and continental European programmes. I have tutored engineering students in Germany and international school students across several countries, so an unfamiliar syllabus or a module taught in a different structure is not a problem. Send me the material and I will work from it. What we cover Python for data science with NumPy, Pandas, Matplotlib and scikit-learn. Deep learning using TensorFlow and Keras. Core theory including regression, classification, clustering, decision trees, random forests, neural networks and CNNs, together with the linear algebra, calculus and statistics underneath them. Computer vision and image classification, which is my published research area. Model evaluation, overfitting and hyperparameter tuning. Writing machine learning work up to academic standard, covering methodology, results and critical evaluation. How lessons work Send me your module handbook, assignment brief, thesis spec or the code that will not run, and I plan the session around it before we meet. Nothing generic. In the lesson I explain the concept with a worked example, then you take the keyboard while I watch and correct, because you learn far more doing it than watching me do it. You finish with annotated notes and a clear next step, and you can message me between sessions with questions. Practical details Online over Google Meet or Zoom with screen sharing and a shared whiteboard. Sessions run 60 or 90 minutes. I am based in the UK and teach across GMT and Central European time, with evening and weekend slots that suit students anywhere in Europe. Tell me your course, your deadline and exactly where you are stuck, and I will come back with a plan for the first session.

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Our students evaluate their Computer Programming teacher.

To ensure the quality of our Computer Programming teachers, we ask our students to review them.

Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.9 out of 5 based on 358 reviews.

“ Baia was instrumental in helping my daughter prepare for the OMPT-F exam. From the very first lesson, she was organized, knowledgeable, and focused on the areas that mattered most for success on the test. What sets Baia apart is her ability to explain complex mathematical concepts in a simple, structured way while building confidence at the same time. Her engineering background gives her a deep understanding of mathematics and allows her to explain not only how to solve problems, but also why the concepts work. She provided targeted practice materials, mock exams, and clear guidance on the key topics that carried the highest impact. Baia was always responsive to questions between lessons and consistently went above and beyond to ensure my daughter was fully prepared. Thanks to her support, my daughter developed a much stronger understanding of mathematics and a more positive attitude toward the subject. She now approaches challenging problems with far more confidence than before. I highly recommend Baia to anyone preparing for the OMPT exams, university mathematics, or looking for a patient, knowledgeable, and highly effective math tutor. ”

“ I recommend Khalil without a doubt to anyone looking to improve his/her German level in both writing and speaking. He is a very professional, structured and knowledgeable teacher. He was able to immediately evaluate my level of German during the very first lesson and adjust the teaching methodology and materials accordingly. I am truly impressed with his patience and dedication towards teaching the proper German pronunciation with all its complexities and difficulties as well as the proper rules when it comes to grammar and language. We also had lessons using Skype which is also a good option for those who have a limited amount of spare time or are too far apart from the teacher. It is obvious that Khalil loves what he is doing and is willing to put all his effort into his passion. I wholeheartedly recommend Khalil for anyone wanting to learn the language. ”

“ Ghous is a very kind and pleasant teacher. He explains everything clearly and is always responsive and supportive. He adapts to the student’s pace and is very flexible when it comes to scheduling and learning preferences. He has a strong command of Electrical Engineering topics and is able to explain even complex concepts in a simple and understandable way. Ghous is also very helpful with assignments, even when they are in a different language, which shows both his deep subject knowledge and his adaptability. I’m very satisfied with his lessons and would definitely recommend him to others. ”

To ensure the quality of our Computer Programming teachers, we ask our students to review them.

Only reviews of students are published and they are guaranteed by Apprentus. Rated 4.9 out of 5 based on 358 reviews.