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

For over a decade, our private Computer Science 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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1456 online computer science teachers

Hossein

Austria
$50

60-min

/h

AI and Machine Learning for Young Students: Understand How It Works and its coceptsTranslate this text using Google Translate.

AI and Machine Learning for Young Students: Understand How It Works and its coceptsTranslate this text using Google Translate.

Artificial intelligence is becoming part of everyday life, but many students use it without understanding what happens behind the screen. This beginner-friendly class helps young students build a clear and meaningful foundation in artificial intelligence and machine learning. As a student, you will learn how to think about AI: where its main ideas come from, how a machine learns from examples, why a model can make predictions, and why it can sometimes make mistakes. Instead of simply learning how to use AI applications, you will begin to understand the reasoning, mathematics and processes that make them work. Using simple explanations, visual examples and interactive exercises, we will explore data, patterns, algorithms, model training, classification, neural networks and real-world AI applications. We will also discuss the limitations of AI and how to evaluate its answers critically. No previous knowledge of AI, programming or advanced mathematics is required. Each lesson will be adapted to the student’s age, current knowledge and interests. I am a Master’s student in Artificial Intelligence at Johannes Kepler University Linz and also have a background in mechatronics. My goal is to make difficult ideas understandable and give students the foundation they need for future studies in mathematics, programming, robotics and artificial intelligence.

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Vincent

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El Salvador
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4.0

1 reviews

(1)

$28

60-min

/h

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Cambridge IGCSE / GCSE /A-Levels / O-Levels / Checkpoint in Computer Science & Information Technology (ICT)Translate this text using Google Translate.

Cambridge IGCSE / GCSE /A-Levels / O-Levels / Checkpoint in Computer Science & Information Technology (ICT)Translate this text using Google Translate.

With over seven years of experience in teaching Computer Science & Information Technology (ICT), I have developed a strong expertise in delivering high-quality education across multiple internationally recognized curricula, including Cambridge IGCSE, GCSE, A-Levels, O-Levels, and Checkpoint. My passion lies in equipping students with coding, cybersecurity, and digital literacy skills, ensuring they are well-prepared for the evolving demands of the digital world. Expertise & Teaching Areas: ✅ Programming & Software Development: Python, Java, C++ ✅ Cybersecurity: Ethical hacking, data protection, network security ✅ Digital Literacy: ICT applications, online safety, cloud computing ✅ Data Science & AI: Data analysis, machine learning fundamentals ✅ Web Development: HTML, CSS, JavaScript Curriculum & Pedagogical Experience: 🔹 Cambridge IGCSE & GCSE ICT & Computer Science – Teaching core and extended syllabi, focusing on programming logic, databases, and networking. 🔹 Cambridge A-Levels & O-Levels Computer Science – Preparing students for advanced computing concepts, problem-solving, and algorithm development. 🔹 Cambridge Checkpoint ICT – Building foundational skills in digital technology and computer applications. Professional Impact: 📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams. 📌 Developed interactive lesson plans integrating real-world applications of technology. 📌 Conducted coding boot camps and cybersecurity workshops to enhance practical learning. 📌 Guided students in project-based learning, including app development and website design. With a strong commitment to student-centered learning and technological innovation, I am dedicated to shaping future tech leaders and empowering learners with skills relevant to careers in technology, data science, and software development.

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Robert

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Belgium
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Recently active
4.7

27 reviews

(27)

$49

60-min

/h

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2Students

Excel lessons, at your place, at my place or remotely, at your best convenience!Translate this text using Google Translate.

Excel lessons, at your place, at my place or remotely, at your best convenience!Translate this text using Google Translate.

As a Franco-Belgian management teacher, I give Excel lessons with passion! Whether remotely or face-to-face, I offer many examples and exercises to accompany you. I travel without problem throughout the region of Brussels and its surroundings, for lessons of at least 2 hours. For France, courses are only given remotely. Here are some key words that will be covered in my classes: Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking Do not hesitate to contact me to organize your lessons according to your needs and availability. Together, we will develop your Excel skills in an efficient and personalized way.

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Ammar

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Canada
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$25

60-min

/h

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1Students

Master AI, Machine Learning, Data Science, Python & Programming with a PhD Engineer and Professor | 25+ Years’ Expertise | All levelsTranslate this text using Google Translate.

Master AI, Machine Learning, Data Science, Python & Programming with a PhD Engineer and Professor | 25+ Years’ Expertise | All levelsTranslate this text using Google Translate.

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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Sohaib

Morocco
$13

60-min

/h

Learn the C programming language for beginners — Step-by-step programmingTranslate this text using Google Translate.

Learn the C programming language for beginners — Step-by-step programmingTranslate this text using Google Translate.

Do you want to learn to program but don't know where to start? This course is for you. As a student in Applied Computer Science & Cybersecurity at the Faculty of Sciences in Rabat, I have already helped several friends understand programming — it is this experience that made me want to teach more broadly. Why start with C? It's one of the best languages to begin with: it forces you to understand what's really happening behind the scenes, without any shortcuts. Once you've mastered the basics of C, learning any other language (Python, Java, JavaScript, etc.) becomes much easier. It's an excellent starting point, whether you're aiming for computer science studies or simply curious to understand how a program works. My method: "learning by doing," at your own pace. I don't impose a rigid program—I observe where you are and adapt the speed, examples, and exercises to your individual needs. From the very first session, you write and execute real code, not just theory. Each session ends with a concrete mini-project (a game, a calculator) that you can proudly showcase at the end. This course is suitable for: - Middle and high school students curious to discover the programming - Students starting their computer science studies - Anyone, beginner or otherwise, with no prerequisites Patience, teaching skills, and a genuine concern for seeing you progress at your own pace.

Florian

Japan
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5.0

3 reviews

(3)

$35

60-min

/h

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2Students

Logic, formal languages, and automata theory for computer scienceTranslate this text using Google Translate.

Logic, formal languages, and automata theory for computer scienceTranslate this text using Google Translate.

Experienced and patient teacher of logic for computer science. I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills. Logic The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof. Topics include: Propositional and Predicate Logic Syntax and semantics Natural deduction Semantic tableaux Correctness and soundness Completeness Formal languages and automata A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language. Topics include: Regular languages, context-free languages Finite automata, pushdown automata, Turing machines Regular expressions Regular grammar, context-sensitive grammar Pumping lemmas for regular and context-free languages

Léo

Switzerland
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Recently active
$82

60-min

/h

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Private lessons in econometrics, finance and trading in Geneva and SwitzerlandTranslate this text using Google Translate.

Private lessons in econometrics, finance and trading in Geneva and SwitzerlandTranslate this text using Google Translate.

• Teaching methodology and techniques: I favour a personalized approach, adapting the courses according to the profile and academic background of each student. • Typical course structure: tutoring in economics, econometrics, statistics and probability, financial mathematics, trading, investment, or political economy. Courses can take place at home, via videoconference, or at a pre-selected location, ideally quiet, free, and conducive to learning. • Specifics as a teacher: I offer support throughout the school year, with free corrections of exercises outside of class, regular availability, and the guarantee of being accessible until the end of the year, subject to the general conditions of Superprof. • Target audience: all levels, regardless of diploma, class or specific characteristics. ------- The path and the method are in there; take a little bit of each. Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online. I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises. Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam. All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me. My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress. My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).

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Our students evaluate their Computer Science teacher.

To ensure the quality of our Computer Science 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 263 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 Science 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 263 reviews.

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