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This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since June 2021
Instructor since June 2021
Computer Science Tutoring for beginners and professionals
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From 42.89 $ /h
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Lectures in Computer Science (Optimization, Graphs, Data Structures, Data Base, Data Mining, Computer Architecture, Image Processing, Numerical Simulation, Office, ..) and programing (C, C++, Java, R, Matlab, MIPS, ..) for beginners and professionals
Location
location type icon
Online from Lebanon
About Me
PhD in computer Science
10 years experience in teaching computer science at american french and lebanese universities like the American University of Beirut, the Lebanese American University and the Polytechnic school of the University of Tours in France
Education
PhD in operational research (modeling, optimization, graph theory, risk, programming).

Master in multimedia (classification, image processing, optimization, programing)
Experience / Qualifications
Associate professor
10 years experience in teaching computer science at american french and lebanese universities like the American University of Beirut, the Lebanese American University and the Polytechnic school of the University of Tours in France
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
The class is taught in
English
French
Arabic
Availability of a typical week
(GMT -05:00)
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
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Perform reliable statistical analyses with R, Stata, SPSS...
Interpret your results rigorously,
Present your work in the form of clear reports, graphics and publications.
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►I attach great importance to ensuring that my students truly understand statistical concepts, data analytics methods, machine learning, and AI models, rather than just applying them mechanically – this is how we achieve sustainable success in statistics, data analytics, and modern technologies.

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►I use practical, lively examples from statistics, data science and AI to clearly explain abstract concepts such as hypothesis testing, analysis of variance, linear and nonlinear models and to anchor them deeply in the memory.

►With patience and clarity, I break down complex statistical analyses, machine learning models, and data processes into their essential components so that no student is overwhelmed and can build a solid foundation in statistics, data analytics, and AI.

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►I offer intensive exam preparation and project support in statistics, data analytics, machine learning and AI, develop strategies to combat exam anxiety with my students and train them on real data sets and complex algorithms.

►As an experienced online tutor for statistics, data analytics, machine learning, and AI, I use modern tools such as interactive whiteboards and live coding sessions in R to make teaching as efficient and practice-oriented as possible.

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◾ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP

◾ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

◾ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL
- Descriptive, exploratory and multivariate statistical analyses on business data
- Production of performance indicators and actionable analyses to support decision-making

◾ Selection and implementation of methods

- Preparation and structuring of databases
- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)
- Linear and logistic regressions
- Factor analyses (PCA / MCA)
- Mediation and moderation models
- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics
- Help in understanding and interpreting the results
- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)
- Multivariate analyses
- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)
- t-tests (one and two samples, independent or paired)
- Chi-square, binomial tests
- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)
- Logistic regression
- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA
- Repeated measures ANOVA
- Fixed and random effects
- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)
- Exploratory factor analysis
- Factorial rotations
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◾ Reporting & communication

- Clear, structured and concise reporting of results
- Visualizations tailored to decision-makers
- Support for strategic and operational decision-making
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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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In this way, to build an application, I will teach you that the really important thing before sitting down to code (by attempt and error) in front of the computer, is the analysis and design of the algorithm (which constitutes 90% of the success of the program to be implemented. ), for this, with an example from the real world, the construction process will be explained: 1. Example with data from the real world, 2. Collection of information on requirements (input data, calculations, output data), 3. Hierarchy of operators (mathematical formulas versus computational formulas), 4. Desk test on a spreadsheet, 5. Constants, variables and data types to use, 6. Algorithm construction, 7. Flowchart, 8. Desk test on paper, 9. Implementation of the algorithm in the chosen programming language, if it is in console mode, it is implemented directly, if it is in form mode, the user interface is drawn on paper (UX) first.
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Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.
verified badge
While adults are still debating whether kids should use AI, they are already using it.
The question isn't "should they?" it's "how do we do it intelligently?"

In this course, your child will discover:
✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't
✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it
✓ What LLMs are (Large Language Models): in language they understand, not tech jargon
✓ Create with AI: custom avatars, interactive stories, real projects using real tools
✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do?
✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life

Why this is different:
Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI.
Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits.
And, more importantly: that they can control how they use it.

What they take home:
Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace

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❌ "My app works locally but crashes in production"
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Students: Fix your project before the deadline
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Live Debugging Session: We fix it together via screen share
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Simple bugs: 1-2 hours
Deployment issues: 2-3 hours
Complex debugging: 3-5 hours

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verified badge
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1- Install MongoDB
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3- Use of documents and collectibles
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5- Execute CRUD commands (create, read, update, delete) avec mongo shell
6- Type the register in a MongoDB database
7- Reset the base to remonter specific documents depuis mongo shell.
8- Lagrégation
9- Indexing
10- Amending institutions and transactions
verified badge
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Why choose this Course?

By opting for these courses, you will have the opportunity to consolidate your knowledge through practical exercises and concrete mini-projects which will strengthen your Python skills. Each session will be interactive, allowing you to ask questions and receive constructive feedback on your code.

You will be able to benefit from personalized support. Lessons are tailored to your level, whether you're looking to pursue a career in programming or just want to learn for fun. Sessions are tailored to your goals, and ongoing support is provided to overcome any challenges you may encounter.
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
Need professional support for your data analysis?
I offer you a personalized service, adapted to your academic or professional needs.

Whether you are a student, researcher, consultant or professional, I put my expertise at your disposal to help you:
Prepare and organize your databases,
Perform reliable statistical analyses with R, Stata, SPSS...
Interpret your results rigorously,
Present your work in the form of clear reports, graphics and publications.
Each project is handled with rigor, pedagogy, and confidentiality. You benefit from tailored support, whether for a professional assignment, a dissertation, a thesis, or a publication.

For those who wish to train in parallel, I have also designed a complete course to learn how to explore, manipulate and analyze your data independently.
verified badge
For many years, I have successfully supported Swiss students in the fields of statistics, data analytics, machine learning, and artificial intelligence. I have gained extensive experience using R as a statistical programming tool and know exactly what students in Switzerland are required to do. I have numerous sample projects, datasets, and exam questions at my disposal and have prepared many students for their assignments and exams in a targeted, sustainable, and highly successful manner. My focus is on explaining complex statistical procedures, algorithms, and data analyses in an understandable way, demonstrating them in a practical way, and building confidence in the secure handling of data. My goal is not only to improve grades, but also, in the long term, to develop a deep understanding of data-driven questions and modern technologies such as machine learning and AI, which are crucial in later professional life.

► How do I teach?

►I attach great importance to ensuring that my students truly understand statistical concepts, data analytics methods, machine learning, and AI models, rather than just applying them mechanically – this is how we achieve sustainable success in statistics, data analytics, and modern technologies.

►My success is based on my ability to flexibly adapt my teaching style to the individual needs of students in statistics, data analytics, machine learning and AI, including topics such as regression methods, logistic regression and other machine learning algorithms.

►I use practical, lively examples from statistics, data science and AI to clearly explain abstract concepts such as hypothesis testing, analysis of variance, linear and nonlinear models and to anchor them deeply in the memory.

►With patience and clarity, I break down complex statistical analyses, machine learning models, and data processes into their essential components so that no student is overwhelmed and can build a solid foundation in statistics, data analytics, and AI.

►I am convinced that trusting collaboration is crucial to reducing uncertainty in statistics or data science and creating a productive learning atmosphere.

►I offer intensive exam preparation and project support in statistics, data analytics, machine learning and AI, develop strategies to combat exam anxiety with my students and train them on real data sets and complex algorithms.

►As an experienced online tutor for statistics, data analytics, machine learning, and AI, I use modern tools such as interactive whiteboards and live coding sessions in R to make teaching as efficient and practice-oriented as possible.

►Locations: I teach statistics, data analytics, machine learning, and AI at your home, online, or by appointment – flexible, professional, and tailored precisely to your needs.
verified badge
As a Digital Transformation student, I know that programming is a fundamental building skill—whether you are a future engineer or a curious young learner. I designed this course as a practical guide to mastering essential tools and, above all, to developing the creative mindset of a programmer.

You will learn how to break down complex problems into logical steps, turn your ideas into functional code, and view errors (“bugs”) as stimulating challenges rather than obstacles.
verified badge
Learn Computer Science through hands-on lessons that cover both theory and programming.
I offer regular lessons to build your understanding of coding (Python/Java) and computer systems, plus exam-focused sessions for IGCSE (0478) and A Level (9618) students.

You’ll learn to:

Understand theory topics like algorithms, logic gates, and networks

Write, test, and debug programs step-by-step

Solve structured past paper questions confidently

Prepare effectively for both Paper 1 (Theory) and Paper 2 (Programming)

Lessons are interactive, practical, and tailored to your school progress and exam goals.
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◾ Tools

RStudio • SQL • SPSS • SAS • Jamovi • JASP

◾ Statistical Methods & Tests

Student's t-test • ANOVA • MANOVA • ANCOVA • Regression (linear & logistic) • Correlation • Chi-square • Nonparametric tests • PCA • MCA • Exploratory factor analysis • Classification / Clustering • Mediation • Moderation • Interpretation

◾ Data analysis & decision support

- Data preparation, structuring and validation using SAS, R and SQL
- Descriptive, exploratory and multivariate statistical analyses on business data
- Production of performance indicators and actionable analyses to support decision-making

◾ Selection and implementation of methods

- Preparation and structuring of databases
- Hypothesis testing and univariate, bivariate and multivariate analyses (ANOVA / ANCOVA)
- Linear and logistic regressions
- Factor analyses (PCA / MCA)
- Mediation and moderation models
- Classification / clustering

1) Academic support

- Lectures, tutorials, projects and assignments in statistics
- Help in understanding and interpreting the results
- Preparation for exams and academic presentations

2) Statistical analysis

- Descriptive statistics (univariate and bivariate)
- Multivariate analyses
- Data exploration and outlier detection

3) Statistical tests

- Correlations (Pearson, Spearman, Cohen's Kappa)
- t-tests (one and two samples, independent or paired)
- Chi-square, binomial tests
- z-scores and associated indicators

4) Statistical modeling

- Linear regressions (simple and multiple)
- Logistic regression
- Interpretation of coefficients, diagnostics and validation of models

5) ANOVA & ANCOVA

- One- or multi-factor ANOVA
- Repeated measures ANOVA
- Fixed and random effects
- Post-hoc tests and effect sizes

6) Factor analyses

- ACP / PCA (scree plot, factor scores, matrices)
- Exploratory factor analysis
- Factorial rotations
- Validation and interpretation of structures and clusters

◾ Reporting & communication

- Clear, structured and concise reporting of results
- Visualizations tailored to decision-makers
- Support for strategic and operational decision-making
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