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

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Machine Learning or Python Programming courses (all levels)

From 58 C$ /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

58 C$ /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.

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.

4.67

(3)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Amin

4.67

(3)

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.

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.

Lucas

4.67

(3)

This course aims to provide a solid foundation of programming concepts and techniques, using popular programming languages such as C, C++ or Python. This course is suitable for people who are new to programming or who already have some basic knowledge and want to improve their skills. Whether you want to become a software developer, get into data analysis, or simply learn to code, this course will provide you with the essential knowledge and practical skills needed to succeed.

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)

Tu souhaites apprendre les bases de l’informatique et de la programmation, mieux comprendre ton cours ou obtenir de l’aide pour tes devoirs et travaux ? Je peux t’accompagner selon ton niveau et tes objectifs !

Je suis diplômée d’un baccalauréat en génie logiciel de Polytechnique Montréal et je donne des cours particuliers depuis quatre ans. J’aime prendre le temps d’expliquer les notions de façon simple et de m’adapter aux difficultés de chaque élève.

Je peux notamment t’aider avec :
- Les bases de l’informatique et du développement logiciel
- L’initiation à la programmation
- Python, Java, C#, JavaScript et d’autres langages selon tes besoins
- Les variables, conditions, boucles, fonctions, tableaux, objets, etc.
- Les devoirs, travaux pratiques et exercices de programmation
- La compréhension et la révision de notions vues en classe
- Le débogage et la compréhension des erreurs dans ton code
- La préparation aux examens et aux évaluations

Que tu sois débutant complet ou que tu aies déjà quelques notions, nous pouvons adapter les séances à ton niveau. L’objectif est de comprendre réellement les concepts et de devenir progressivement plus autonome, plutôt que de simplement trouver la réponse à un exercice.

Les cours peuvent s’adresser aux élèves du secondaire, aux étudiants du cégep ou à toute personne souhaitant découvrir la programmation.