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Since October 2024
Instructor since October 2024
Object-Oriented Programming (OOP) & Data Structures and Algorithms (DSA) Tutoring in Java, C, C++, and Python
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From 19 £ /h
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Master the Fundamentals: My tutoring sessions are designed to give students a solid foundation in Object-Oriented Programming (OOP) and Data Structures and Algorithms (DSA). Whether you're a beginner or need to strengthen your skills, we will cover the essential concepts that are critical for coding and software development.

Language Flexibility: I offer tutoring in Java, C, C++, and Python, providing flexibility for students to learn in the language they are most comfortable with or the one required for their academic needs. We’ll compare the nuances of these languages to help you develop a deeper understanding of programming concepts.

Comprehensive OOP Concepts: Learn the core pillars of OOP—encapsulation, inheritance, polymorphism, and abstraction—and how to implement them in real-world coding projects. My lessons focus on making these abstract concepts easy to grasp through hands-on practice and examples.

Data Structures & Algorithm Mastery: From arrays, linked lists, and stacks, to more complex structures like trees, graphs, and hash tables, I guide students through the implementation and usage of these critical data structures. We’ll also explore fundamental algorithms like sorting, searching, recursion, and dynamic programming, ensuring you can tackle coding problems efficiently.

Problem-Solving Skills: I focus on building strong problem-solving skills and critical thinking. We’ll work on a variety of programming challenges, competitive coding exercises, and real-world applications that sharpen your logical reasoning and coding proficiency.

Interactive & Engaging Learning: Every session is interactive, with plenty of coding exercises, real-time debugging, and immediate feedback. You’ll walk away with a thorough understanding of how to apply programming concepts in a practical way.

Exam Preparation & Beyond: Whether you're preparing for school exams, coding interviews, or personal projects, my tutoring is geared toward equipping you with the skills and knowledge you need to succeed. I also provide practice problems and quizzes to ensure continuous learning and improvement.
Extra information
Prior knowledge of programming is a plus but not compulsory
Location
location type icon
Online from United Kingdom
About Me
Engaging & Passionate Tutor: I believe that learning should be both exciting and meaningful. I thrive on the energy of students who are eager to understand complex concepts, and I am committed to making every lesson engaging and productive.

Personalized Approach: Every student is different, and I adapt my teaching style to meet individual needs. Whether you're a quick learner or need a bit more time, I tailor my lessons to ensure each student fully grasps the material at their own pace.

Hands-On Learning: I focus on practical examples and interactive problem-solving, especially in subjects like Computer Science and Physics. My students don't just memorize formulas—they understand how to apply them in real-world scenarios.

Encouraging & Supportive: My teaching philosophy is centered around encouragement and building confidence. I create a safe space where students feel comfortable asking questions and exploring new ideas without fear of making mistakes.

Structured & Organized: I provide clear lesson plans, assign homework to reinforce key concepts, and regularly assess progress to ensure continuous improvement. Parents and students can expect transparency and structured guidance throughout the tutoring process.

Experienced Tutor: With over two years of experience in Computer Science, Mathematics, and Physics, I have worked with students across a variety of learning levels. My expertise spans programming, algorithms, mathematical reasoning, and physical sciences.

Committed to Long-Term Success: I’m not just focused on short-term exam results—my goal is to foster a deep understanding of the subject matter that will benefit students in their future studies and careers. I equip students with the tools and mindset needed to approach new challenges with confidence.
Education
Student at Manchester Metropolitan University, Completed A-Levels with a B in Mathematics, Completed IGCSE with 6 B's in every subject except Computer Science and Islamiat.
Experience / Qualifications
Software Engineer, Freelance Programmer, Computer Science Expert, Crypto Mining Rigs Expert, Python specialist, C++ specialist, Java specialist, Tutoring Expert, Students Favorite, Teaching Expert, Programming Expert, Competitive Coder
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
30 minutes
45 minutes
60 minutes
90 minutes
120 minutes
The class is taught in
English
Urdu
Hindi
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Ace Competitive Programming: I specialize in helping students master the art of competitive coding. Whether you're preparing for coding competitions like Codeforces, LeetCode, Hackerrank, or university-level contests, I guide you through the problem-solving techniques and strategies used by top coders.

Structured Problem Solving: My tutoring sessions focus on breaking down complex problems into manageable steps. You’ll learn how to approach coding challenges with a clear and logical mindset, enabling you to solve problems efficiently under time constraints.

Algorithm Optimization: Understand and implement key algorithms such as greedy algorithms, dynamic programming, backtracking, and divide-and-conquer. We’ll focus on optimizing your solutions for speed and efficiency, ensuring your code runs within time limits during competitions.

Data Structure Expertise: Gain a deep understanding of how to effectively use arrays, linked lists, stacks, queues, trees, graphs, and other advanced data structures to solve challenging problems. You’ll learn when and how to choose the right data structure to improve performance.

Hands-On Practice: Every session includes real-time problem-solving, where we’ll tackle actual coding problems from popular competitive platforms. I provide immediate feedback on your code and guide you through debugging and refining your solutions.

Improve Speed & Accuracy: Competitive coding is all about solving problems quickly and accurately. I help students develop strategies to think on their feet and avoid common coding pitfalls, while also sharpening their typing and coding speed.

Prepare for Coding Interviews: In addition to competitions, the skills you’ll learn are invaluable for technical interviews at top companies. I provide specific coaching for coding interview prep, ensuring you’re ready to tackle both standard and advanced problems with confidence.

Stay Motivated & Confident: Competitive coding can be tough, but I keep students motivated with challenging yet achievable goals. You’ll develop resilience and confidence in your coding skills, ready to take on any challenge.
Read more
GCSE Computer Science, Mathematics, and Physics Tutoring

I specialize in tutoring Computer Science, Mathematics, and Physics for GCSE students. I aim to provide clear, engaging lessons that help students master key concepts while building confidence in their problem-solving abilities.

In Computer Science, students will learn programming fundamentals, algorithms, loops, logic gates, conditions, computational thinking, and exam techniques to excel in theory and practical assessments. Whether you're new to coding or refining your skills, I guide students through real-world applications of computing, using languages like Python to bring lessons to life.

In Mathematics, I focus on helping students understand the core principles of algebra, geometry, and statistics. Lessons are designed to reinforce schoolwork, address challenging topics, and prepare students for GCSE exams with practice problems, test-taking strategies, and personalized feedback.

For Physics, I make complex concepts like mechanics, electromagnetism, and energy systems accessible and interesting. Students will engage in hands-on activities and thought experiments that deepen their understanding of the physical world, preparing them for exams and future STEM studies.

I assign targeted homework after each session and provide periodic progress reports to ensure students stay on track and continuously improve. My approach is to challenge students without overwhelming them, fostering a positive learning environment where they can excel academically.
Read more
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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.
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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.
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In this training, we will try to describe what is object-oriented programming (often abbreviated as OOP) and model this approach with these different concepts. My goal is to advance the student to reach his goal without overloading it.
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Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
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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.
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Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.
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🐍 Python Course – Learn to code and create your projects!

This course is for anyone who wants to:

✅ Learn Python from the beginning
✅ Strengthen their programming skills

📚 On the program:

Variables

Loops

Functions

Data structures

Practical projects for implementation

💡 How does the course work?

Clear explanations to understand the programming logic

Targeted exercises adapted to your level

Concrete projects to create your own applications

🎯 My goal:

Helping you understand the logic behind the code

Progress at your own pace

Create your own projects in Python and gain independence
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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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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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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

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pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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Learn Python with a structured, hands-on approach! Whether you are a absolute beginner looking to start coding, a student needing help with coursework, or a professional aiming to automate tasks, these lessons are tailored for you.What we will cover:
Core Fundamentals: Variables, loops, functions, and data structures.Object-Oriented Programming: Building reusable and clean code.Real-World Projects: Creating scripts, data analysis, or web scraping based on your goals.

Problem Solving: Learning how to debug and think like a programmer. Lessons are highly interactive. We will write code together from day one, and you will receive practical exercises after every session to build your confidence.
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Do you want to learn Python, discover programming, or strengthen your basic skills?
As a computer science teacher with a Master's degree in Computer Science, specializing in Data Science, I offer courses tailored to your level and objectives.
We can work specifically on the basics of Python, variables and data types, conditions, loops, functions, data structures, files, as well as problem-solving and first projects in Python.
My approach is primarily practical: I explain concepts gradually, with simple examples, and then we apply them through exercises. The content and pace are tailored to each learner's difficulties and objectives.
The courses are aimed at beginners, students or adults wishing to learn Python or consolidate their programming knowledge.
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I offer personalized lessons adapted to each student’s level, objectives, and learning pace. Whether you want to strengthen your fundamentals, prepare for an exam, improve your academic performance, or develop practical skills, I provide clear explanations and hands-on exercises.

📐 Mathematics: algebra, functions, equations, calculus, probability, and applied mathematics.

💰 Finance: financial analysis, corporate finance, investments, financial markets, portfolio management, risk management, and quantitative finance.

📊 Statistics: descriptive statistics, probability, hypothesis testing, correlation, regression, data analysis, and interpretation of results.

💻 Microsoft Office: Excel, Word, and PowerPoint — from basic to advanced level, including formulas, data analysis, charts, professional documents, reports, and presentations.

As a Master’s student in Finance at the University of Neuchâtel, with a background in Finance and experience in quantitative analysis and credit-risk modelling, I focus on making complex concepts simple, practical, and easy to understand.

Courses available in French or English.
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This course is designed for students and adolescents who want to build a strong beginner-friendly foundation in Computer Science.
Whether you're completely new to Computer Science or need help with a specific programming subject, the course can be customized to match your needs.
Need help with C++ or programming? You can provide me with your syllabus, course outline, or the topics you're studying, and I'll tailor the lessons around what you need to learn.
Learning with friends? Group lessons are also available, allowing you to learn together while following the same customized course.
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Welcome! Whether you are a complete beginner or a university student aiming to strengthen your technical foundation, this course is tailored to help you master Python programming, database design, and SQL queries effectively.

In our sessions, we focus on hands-on practical learning rather than passive theory. Here is what we can cover:
• Python Programming fundamentals, data structures, and logic building.
• Relational Databases design, schemas, and ER diagrams.
• Writing clean, optimized SQL queries (SELECT, JOINs, aggregations, subqueries).
• Hands-on practice with real-world datasets and troubleshooting common errors.
• Assistance with university coursework, exam prep, and personal projects.

Lessons are tailored to your pace and goals, ensuring you build confidence in writing code independently. Feel free to reach out with any questions before booking!
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Similar classes
arrow icon previousarrow icon next
verified badge
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.
verified badge
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.
verified badge
In this training, we will try to describe what is object-oriented programming (often abbreviated as OOP) and model this approach with these different concepts. My goal is to advance the student to reach his goal without overloading it.
verified badge
Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
verified badge
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.
verified badge
Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.
verified badge
🐍 Python Course – Learn to code and create your projects!

This course is for anyone who wants to:

✅ Learn Python from the beginning
✅ Strengthen their programming skills

📚 On the program:

Variables

Loops

Functions

Data structures

Practical projects for implementation

💡 How does the course work?

Clear explanations to understand the programming logic

Targeted exercises adapted to your level

Concrete projects to create your own applications

🎯 My goal:

Helping you understand the logic behind the code

Progress at your own pace

Create your own projects in Python and gain independence
verified badge
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.
verified badge
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

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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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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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Learn Python with a structured, hands-on approach! Whether you are a absolute beginner looking to start coding, a student needing help with coursework, or a professional aiming to automate tasks, these lessons are tailored for you.What we will cover:
Core Fundamentals: Variables, loops, functions, and data structures.Object-Oriented Programming: Building reusable and clean code.Real-World Projects: Creating scripts, data analysis, or web scraping based on your goals.

Problem Solving: Learning how to debug and think like a programmer. Lessons are highly interactive. We will write code together from day one, and you will receive practical exercises after every session to build your confidence.
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Do you want to learn Python, discover programming, or strengthen your basic skills?
As a computer science teacher with a Master's degree in Computer Science, specializing in Data Science, I offer courses tailored to your level and objectives.
We can work specifically on the basics of Python, variables and data types, conditions, loops, functions, data structures, files, as well as problem-solving and first projects in Python.
My approach is primarily practical: I explain concepts gradually, with simple examples, and then we apply them through exercises. The content and pace are tailored to each learner's difficulties and objectives.
The courses are aimed at beginners, students or adults wishing to learn Python or consolidate their programming knowledge.
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I offer personalized lessons adapted to each student’s level, objectives, and learning pace. Whether you want to strengthen your fundamentals, prepare for an exam, improve your academic performance, or develop practical skills, I provide clear explanations and hands-on exercises.

📐 Mathematics: algebra, functions, equations, calculus, probability, and applied mathematics.

💰 Finance: financial analysis, corporate finance, investments, financial markets, portfolio management, risk management, and quantitative finance.

📊 Statistics: descriptive statistics, probability, hypothesis testing, correlation, regression, data analysis, and interpretation of results.

💻 Microsoft Office: Excel, Word, and PowerPoint — from basic to advanced level, including formulas, data analysis, charts, professional documents, reports, and presentations.

As a Master’s student in Finance at the University of Neuchâtel, with a background in Finance and experience in quantitative analysis and credit-risk modelling, I focus on making complex concepts simple, practical, and easy to understand.

Courses available in French or English.
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This course is designed for students and adolescents who want to build a strong beginner-friendly foundation in Computer Science.
Whether you're completely new to Computer Science or need help with a specific programming subject, the course can be customized to match your needs.
Need help with C++ or programming? You can provide me with your syllabus, course outline, or the topics you're studying, and I'll tailor the lessons around what you need to learn.
Learning with friends? Group lessons are also available, allowing you to learn together while following the same customized course.
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Welcome! Whether you are a complete beginner or a university student aiming to strengthen your technical foundation, this course is tailored to help you master Python programming, database design, and SQL queries effectively.

In our sessions, we focus on hands-on practical learning rather than passive theory. Here is what we can cover:
• Python Programming fundamentals, data structures, and logic building.
• Relational Databases design, schemas, and ER diagrams.
• Writing clean, optimized SQL queries (SELECT, JOINs, aggregations, subqueries).
• Hands-on practice with real-world datasets and troubleshooting common errors.
• Assistance with university coursework, exam prep, and personal projects.

Lessons are tailored to your pace and goals, ensuring you build confidence in writing code independently. Feel free to reach out with any questions before booking!
Good-fit Instructor Guarantee
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