Machine Learning or Python Programming courses (all levels) - Longueuil

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Machine Learning or Python Programming courses (all levels)

From 37 € /h

Machine Learning and Data Science are very advanced fields and, as such, in fashion. They are major tools for any new technology and the school is lagging behind in teaching these skills.

In addition, these skills are theoretical as well as practical skills, and the multiple online courses focus on practice, forgetting that companies are not only looking for performers, but also experts in the intelligent use of these tools.

Having advanced theoretical training in this field, along with more than 2 years of field experience in information programming associated with machine learning, I propose to teach you this subject, both theory and practice, at the option of courses combining the two aspects of the thing.

Extra information

No training, theoretical or practical, is required. But I will adapt to the knowledge of the student and, if he / she does not know anything in applied mathematics or programming, the amount of time to plan will be important.

Location

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At student's location :

Around Longueuil, 10, Canada

About Me

- I am a young Frenchman of 25, in Montreal for work and enthusiastic about the idea of discovering Quebec and the people of Quebec!
- Coming from French fields of excellence in theoretical and applied mathematics, I pushed the love of mathematics to the point of teaching, during private lessons and preparatory classes, mathematics at the highest level
- I have trained many students in oral mathematics competitions, with an emphasis not on magical methods but on pedagogy, to help students form reasoning, understand demonstrations and apply them. My students have always recommended me for my patience and my pedagogy.

Education

Preparatory classes at the Lycée Saint Louis (Paris)
Master Grande Ecole, HEC Paris
Master in Data Science / Advanced Statistics, ENSAE Paris
2 years of experience in Data Science applied to insurance and finance

Experience / Qualifications

Private lessons for 4 years, at a rate of 3 students per year, 2 hours per week
Oral high-level mathematics exams, for 3 years

Age

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

60 minutes

90 minutes

120 minutes

The class is taught in

French

English

Skills

Statistics

Computer programming

Availability of a typical week

(GMT -04:00)

New York

At student's home

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Mathematics courses for all levels, theory and practice

37 € /h

A former student of HEC Paris and ENSAE Paris (School of Applied Mathematics and Statistics of the Institut Polytechnique Paris), I did high-level mathematics and now work as a data scientist and statistician in the service of financial institutions.

My course in France is one of the most demanding in mathematics and I was an oral interrogator for preparatory classes in France, preparing students for oral mathematics for the competition. In France, I gave hundreds of hours of private lessons but also, therefore, in preparatory classes. I teach all levels, up to the most advanced. My students generally recommend me for my pedagogy and my ability to explain complex reasoning graphically, and therefore clearly.

I prefer teaching in the presence, even if it is possible to teach by webcam.

Florian

4.67

(3)

Developer since 10 years, I work on the development of new 3D engine for different industries. My experience ranges from raytracer to standard OpenGL rendering. The languages covered will be C / C ++, OpenGL and OpenCL.

This course is for anyone wanting an introduction to this type of programming or wanting to learn and discuss developments and new methods in this area. The focus is mainly on the use of graphic resources and understanding how to use the material.

For beginners in programming, the course will focus on learning the technical terms, methodologies and concepts namely to program effectively in general.

Ahmed

4.67

(3)

Mathematics, Physics, and Computer Science Tutor | Montreal | French & English
Private tutoring in mathematics, physics and chemistry, life and earth sciences, and computer science for high school, CEGEP, and university students in M

French curriculum: middle school, high school, preparation for the Baccalaureate (Mathematics, Physics-Chemistry, Life and Earth Sciences) — Stanislas, Marie de France
Quebec Program (Secondary & CEGEP), (NYA, NYB, NYC), university

Mathematics: Secondary 1 to 5 (including SN and CST components).
Science: Secondary 5 Physics and Chemistry.
CEGEP: Integral and Differential Calculus (NYA, NYB), Linear Algebra (NYC), and Physics.

English-language program: secondary school, CEGEP, university level
Computer science: Java, C++, Linux, algorithms
formations

Baccalaureate with a specialization in Mathematics
B.Sc. Computer Science, Finance and Mathematics — McGill
M.Sc. Applied Computer Science — Concordia

I have been giving private lessons in mathematics, physics-chemistry and computer science for over 10 years in Montreal. I support high school, CEGEP and university students, in Quebec, French and English programs.
In mathematics and physics, I teach from secondary school to university level, including CEGEP courses at NYA, NYB, and NYC. For students at French schools in Montreal such as Stanislas or Marie de France, I cover the French curriculum from middle school through the Baccalaureate with a specialization in Mathematics, including mathematics, physics and chemistry, and life and earth sciences.
In computer science, I teach programming courses in Java, C++ and Linux, as well as algorithm courses for college and university levels.
My method is based on understanding before memorization. Each session is adapted to the student's level and objectives, whether it is to fill gaps in knowledge, prepare for an exam or deepen understanding of a concept.
My background is rooted in both systems: I graduated with a French Baccalaureate specializing in Mathematics, hold a B.Sc. in Computer Science-Finance-Mathematics from McGill University, and an M.Sc. in Applied Computer Science from Concordia University. I have over 10 years of experience tutoring students of all levels in mathematics, physics, and computer science in Montreal.

4.67

(3)

Hello, I am a doctoral student in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (Electronics, automatics, electrical engineering, automation, programming).

Digital electronics
Analog electronic
electromagnetism (propagation of high frequency waves)
Automatic (continuous, sampled)
electrical engineering (transformers, electrical machines, switching power supply)
C / c ++ programming, Assembler, ARM, STM32
renewable energy (wind, PV)
engineering Sciences
RDM
Python,VHDL
PIC Microprocessor and Microcontroller
Signal processing and data acquisition
Engineering Sciences

These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes.

COURSE OBJECTIVES AND PEDAGOGICAL APPROACH

Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

Respond to individual issues and questions

Exercise training in order to achieve real mastery of the content.

Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

This educational approach is effective since it has often led me to interesting results with my students.

Associate professor provides support courses in electrical engineering

Sébastien

4.67

(3)

Hello,

I am a trainee engineer at MBA and I have 19 years of experience in the field. I teach web and mobile programming courses (Spring, Java, Hibernate, Angular, HTML5, CSS3, etc.)

I am available on Saturdays.

thank you,

Manoosh

4.67

(3)

I have a bachelor's degree in Electrical Engineering- Telecommunications from SBU university in Iran. SBU is one of the top 5 universities in Iran. I was always among the top three students during my undergrad. I am specifically good at Math, Programming, and Electrical Circuits analysis. During my undergrad, I was a TA for AVR micro-controllers programming and probability & statistics courses, during which I gained lots of teaching experience. During my bachelor's thesis, I implemented Behavioral Cloning (end-to-end) approach for self-driving by programming Artificial Neural networks in python with Keras and Tensorflow frameworks. I am currently a master student in the ECE department of McGill University working in the field of Computer Vision at Visual Motor Research Lab and am a member of Center for Intelligent Machines (CIM) at McGIll.

I believe that learning is only effective when you have a question in mind. Thus, I always try to first stimulate student's curiosity on the subject and talk about its application, before teaching that subject to them. Also, I teach the subjects very slowly and step by step to allow students to think deeply about everything I teach to them. Also, my courses' syllabus is flexible and I usually consult them with students on the first session.

Adam

4.67

(3)

Demystifying probabilities and data processing
Statistics and probability occupy an increasing place in the secondary school curriculum and directly prepare students for the requirements of higher education (economics, medicine, engineering, humanities).

The sessions will include:

Descriptive statistics (means, standard deviations, graphical representations).

Conditional probabilities, probability laws and combinatorics.

Analysis, interpretation of datasets and sampling logic.

Targeted training based on typical exercises and exam problems.

Mohamed

4.67

(3)

The aim of this course is to learn programming in general and to discover the different programming applications such as machine learning, deep learning or even video game programming via Unity.
There is also the possibility of doing lessons at a more advanced level according to the student's need and to concentrate on one point or another.

Ludovic

4.67

(3)

I've been developing since I was 15, and coding has always been at the heart of my career. Initially, Java was my language of choice. Now I use Python and Nodejs. I developed a complete product which was sold to companies in order to offer Single Sign-On (SSO) to an Oracle product supporting OpenID, SAML and Kerberos. I developed in Node.js.

Amin

4.67

(3)

Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Aniket

4.67

(3)

Hello,
I'm doing a PhD in AI and ML using Python and am an Oracle-certified trainer with 350+ reviews and ratings [with proof attached], I will be able to teach you Python better than any of my competition.

Why choose me?
1. 300 + reviews and ratings
2. Certified tutor
3. More than 5 years of teaching experience
4. Worked as a Software engineer in companies like Virtusa Corp and DIGIDEZ DIGITAL SYSTEMS
5. Hold B.tech and M.tech in Computer Science

Featured Review :
Been trying to learn Java on my own for about 1 year and I couldn't get a grasp on it. Aniket make learning Java a fun experience and challenges you to think for yourself to reinforce the concepts you've learned. I am truly excited for our meetings and he makes time go by so fast that I'm upset when they end. Great teacher and he is genuinely passionate about your success. If I could give him more stars I would!!!

Thanks
Aniket

Etienne

4.67

(3)

Hello,
My name is Etienne and I am a final year student in a dual engineering school degree. I have already been a private tutor for 3 years, and I love passing on my knowledge! I am bilingual in English (985/990 on the TOEIC), and have a Master's level in Mathematics. I can also give science or computer science lessons. We can plan a face-to-face, distance or hybrid course.
I hope to see you again soon!

Nathanaël

4.67

(3)

Having graduated with a master's degree in industrial engineering, with a major in computer science at Polytechnique Montréal, I would like to give math and/or computer science courses to students in a university program, at CEGEP or at secondary school.
During my studies at Polytechnique Montréal, I gave classroom lessons, practical work (around 50 people), as well as mathematics reinforcement for all types of profiles (individual help).
I also have previous private tutoring experience.

It is always a real pleasure for me to witness the success of the students and to see their progress session after session.
I insist on stimulating students' thinking so that they are as effective as possible during their exams.

It would be a pleasure to have a first meeting!

Mathilde

4.67

(3)

For:
- Better understand your science courses (math, physics, chemistry, biology, computer science)
- Find effective working methods that suit you
- Regain confidence in your abilities
- Discover that science can become exciting

I offer personalized courses adapted to each profile which go beyond simple academic support:

✅ Learning to learn (organization, memorization, reasoning)
✅ Develop solid and sustainable methods
✅ Work at your own pace, with kindness

An engineer in medical imaging, neuroscience, and artificial intelligence, my rigorous scientific background and my passion for sharing my knowledge drive me to support students in their success. My goal is to give students a taste for science and the keys to becoming independent and confident. I adapt to the pace and needs of each individual, combining rigor and kindness to restore self-confidence and rediscover the joy of learning, essential for progress.

Ammar

4.67

(3)

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.

Julie

4.67

(3)

Do you want to learn the basics of computer science and programming, better understand your coursework, or get help with your homework and assignments? I can support you according to your level and goals!

I graduated with a bachelor's degree in software engineering from Polytechnique Montréal and have been tutoring for four years. I like to take the time to explain concepts simply and adapt to each student's difficulties.

I can help you with, among other things:
- The basics of computer science and software development
- Introduction to programming
- Python, Java, C#, JavaScript and other languages as needed
- Variables, conditions, loops, functions, arrays, objects, etc.
- Homework, practical work and programming exercises
- Understanding and reviewing concepts covered in class
- Debugging and understanding errors in your code
- Preparation for exams and assessments

Whether you're a complete beginner or already have some knowledge, we can adapt the sessions to your level. The goal is to truly understand the concepts and gradually become more independent, rather than simply finding the answer to an exercise.

The courses are suitable for high school students, college students, or anyone wishing to discover programming.