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Since April 2023
Instructor since April 2023
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Discover the infinite possibilities of programming with the interactive and challenging Python course for all ages!
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From 35 € /h
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Do you also want to learn how to program and discover the world of technology? Then you've come to the right place! I offer an interactive and challenging Python course for all ages. Whether you are a beginner or more experienced, I will make sure that you are challenged and guided at your level. During the lessons we will work on practical assignments and projects, so that you not only learn the basics of Python, but can also apply it directly in practice. In short, with me you not only learn programming, but also creative and solution-oriented thinking. Contact me for my Python course and discover the infinite possibilities of this programming language!
Extra information
All that is required: a laptop or computer with a good internet connection.
Location
location type icon
Online from Netherlands
About Me
Hello, my name is Jaskirat and I am a 19 year old college student. I am passionate about helping students and I love sharing my knowledge and skills with others. My goal is to help teens reach their maximum potential and guide them to achieve success.

With my high performance in secondary education and my communication skills, I am able to teach in a way that is fun and engaging for students. It is important to me to provide a supportive learning environment, where students feel comfortable and can ask their questions.

I have experience helping fellow students and other teens with their school work and I have helped them achieve great achievements. I also offer flexible lesson times, so that students can come to me for tutoring during the weekend and online tutoring is also possible. I look forward to working with you and supporting your success!

Not only do I have experience with tutoring or helping students at school, but also with sports. I have been actively involved in sports for over four years and I have also managed to guide people in this in the beginning. Over time I have built up knowledge about sports that I can easily and simply transfer to someone else.
Education
I did NT in secondary education, with challenging subjects such as mathematics D. I am currently studying technical business administration and I am learning to analyze and improve business processes.
Experience / Qualifications
As a fellow student, I have gained a lot of experience in tutoring subjects such as mathematics and chemistry. I have managed to achieve great results for my fellow students and I would also like to help you to get the best out of yourself! In addition, I have been guiding a small group of young people in my area for over two years and I am happy to share my knowledge with you to grow and develop together.
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
Dutch
Hindi
English
Urdu
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
Welcome to my math lesson for teenagers at HAVO level! As a young student with a passion for math and outstanding achievements in this area, I understand the challenges you face as a teenager and how I can help you achieve success.

With my experience in math B and math D, I can guide you in understanding even the most complex concepts and formulas. I will convey my passion for math in a way that will inspire and motivate you to be the best you can be.

But what really makes my class unique is my understanding of the situation of teenage students. I know that balancing school, social activities, and personal obligations isn't always easy. Therefore, I will provide a supportive and inclusive learning environment, where you feel comfortable and can be yourself.

In short, my math class is designed to help you succeed in school and in life. With my expertise and personal approach, you will enjoy the math lesson and be motivated to learn and grow.
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Control or manage your own hardware?

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

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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.

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Beginner: basics of the language (variables, loops, conditions, functions).

Intermediate: data manipulation (Pandas, NumPy), file management, object-oriented programming.

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A- TOPICS YOU CAN EXPLORE AND MASTER:
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• 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

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• 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

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• 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.

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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I work as a data consultant and hold a master's degree in Data Science and Statistics from UCLouvain. I use Python and data manipulation and analysis tools daily in a professional context.

I offer Python and data analysis courses for students, beginners and people wishing to develop practical skills in programming and data.

The lessons are tailored to your level and your goal. We can work on, among other things:

* the basics of Python and programming logic;
* variables, conditions, loops and functions;
* Data manipulation with Python and pandas;
* data cleaning and transformation;
* data exploration and visualization;
* applied statistics;
* solving practical exercises and projects;
* Understanding and debugging your code.

I prefer a practical approach: we start with a concrete problem or dataset, gradually build the solution, and analyze the errors encountered together.

The goal is to understand what you are doing rather than simply reproducing code, in order to gradually become self-reliant.

I can also support a project or student work by explaining the approach, the code and the methods used, without doing the work for you.
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Python is one of the easiest and most in-demand programming languages in today's job market, used in artificial intelligence, data analysis, web development, and game development. As an IT teacher with experience in school teaching, I designed these lessons to be practical and interactive:

Programming basics (variables, conditions, loops)
Solve realistic exercises and small projects
A simplified approach perfectly suited for beginners with no prior experience.
Suitable for students who want support with their school curriculum (IGCSE/British/American) or anyone who wants to start programming from scratch
Good-fit Instructor Guarantee
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