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Since December 2021
Instructor since December 2021
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PhD Candidate & Experienced Professor - Data Analysis & Advanced Statistics | 300+ people coached | SPSS, R-Studio, Jamovi, JASP
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From 49.91 $ /h
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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.
Location
location type icon
Online from France
About Me
◾◾ À propos de moi – Expérience & accompagnement ◾◾

Avec 9 ans d’expérience en analyse de données et statistiques avancées, j’ai accompagné plus de 300 élèves et professionnels issus de parcours variés :

◾ étudiants de l’enseignement supérieur
◾ ingénieurs et chercheurs
◾ professionnels de différents secteurs

Mon accompagnement est concret et appliqué, allant de la structuration de la démarche analytique jusqu’à l’analyse et l’interprétation des résultats :

◾ organisation et structuration du travail
◾ choix des méthodes statistiques adaptées
◾ réalisation des analyses
◾ interprétation et mise en valeur des résultats
Education
◾ Doctorant en statistique et analyse de données
◾ Ingénieur data analyst
◾ Encadrement et supervision de projets de fin d’études, avec accompagnement méthodologique et analytique des étudiants dans leurs travaux de recherche.
Experience / Qualifications
◾ Outils

R Studio • SQL • SPSS • SAS • Jamovi • JASP

◾ Méthodes & tests statistiques

T de Student • ANOVA • MANOVA • ANCOVA • Régression (linéaire & logistique) • Corrélation • Khi-deux • Tests non paramétriques • ACP • AFC • Analyse factorielle exploratoire • Classification / Clustering • Médiation • Modération • Interprétation

◾ Analyse de données & aide à la décision

- Préparation, structuration et fiabilisation des données (data préparation) avec SAS, R et SQL
- Analyses statistiques descriptives, exploratoires et multivariées sur des données métiers
- Production d’indicateurs de performance et d’analyses exploitables pour l’aide à la décision

◾ Choix et mise en œuvre des méthodes

- Préparation et structuration des bases de données
- Tests d’hypothèses et analyses univariées, bivariées et multivariées (ANOVA / ANCOVA)
- Régressions linéaires et logistiques
- Analyses factorielles (ACP / AFC)
- Modèles de médiation et de modération
- Classification / clustering

1) Accompagnement académique

- Cours, TD, projets et travaux en statistique
- Aide à la compréhension et à l’interprétation des résultats
- Préparation aux examens et présentations académiques

2) Analyse statistique

- Statistiques descriptives (univariées et bivariées)
- Analyses multivariées
- Exploration des données et détection des valeurs aberrantes

3) Tests statistiques

- Corrélations (Pearson, Spearman, Kappa de Cohen)
- Tests t (un et deux échantillons, indépendants ou appariés)
- Khi-deux, tests binomiaux
- z-scores et indicateurs associés

4) Modélisation statistique

- Régressions linéaires (simple et multiple)
- Régression logistique
- Interprétation des coefficients, diagnostics et validation des modèles

5) ANOVA & ANCOVA

- ANOVA à un ou plusieurs facteurs
- ANOVA à mesures répétées
- Effets fixes et aléatoires
- Tests post-hoc et tailles d’effet

6) Analyses factorielles

- ACP / PCA (scree plot, scores factoriels, matrices)
- Analyse factorielle exploratoire
- Rotations factorielles
- Validation et interprétation des structures et des clusters

◾ Reporting & communication

- Reporting clair, structuré et synthétique des résultats
- Visualisations adaptées aux décideurs
- Aide à la prise de décision stratégique et opérationnelle
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
English
French
Arabic
Reviews
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
◾ 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
Read more
◾ 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
Read more
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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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Code Your Ideas Into Reality 💻🚀
Want to build your own website or start a tech career? This class is perfect for absolute beginners who want to learn Python and use it to build real, working web apps with Django. You'll go from writing your first line of code to deploying complete projects - step by step, clearly explained, and handsOn.

✨ No experience needed.
🧠 Learn by doing - real apps, real logic.
🌍 Build skills for school, work, or freelance life.

Let’s turn your curiosity into code. First session gets you started!
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Hello high school students! My name is Soufiane, Master's in Data Science & AI.

I offer 100% NSI (Digital Science and Technology) courses:
- Python (variables, functions, lists, dictionaries, OOP)
- Algorithms (sorting, searching, complexity, divide & conquer)
- Recursion (recursive functions, stacks, trees)
- Databases (SQL, relational models, queries)
- Architecture (systems, networks, protocols)
- Web (HTML/CSS/JS, Flask, client-server)
- Baccalaureate projects (subject 0, assessed mini-projects, clean code)
- Past papers & practice exams (2024/2025 step-by-step solutions) Objective: BAC NSI > 16/20 (written exam + project)
- Enhanced Parcoursup (specializations, engineering schools)
- Complete mastery of the program

Why me ?
100% interactive course: live coding, debugging...
Professional supports: algo sheets, Python/SQL templates, PDF reports
Flexible hours: evenings, weekends, holiday internships
At home (Cergy, Pontoise, Sarcelles – free within 15 km) or Zoom + screen sharing
Invoices issued

Limited places available (max 8 students). Contact me by message to schedule an appointment.
Respond quickly before the start of term! See you soon to ace your NSI exams!
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This course shows students how AI is the engine behind modern video games. It’s an engaging, project-based track ideal for advanced concepts in a fun, relatable environment.

Behavioral AI: Using simple visual programming environments (like Scratch or similar platforms) to program smarter Non-Player Characters (NPCs) that react realistically to the player's actions.

Generative Assets: Learning how game studios use generative AI tools to rapidly create textures, background stories, or simple game environments.

Interactive Storytelling: Exploring decision-tree logic and how AI can adapt game narratives based on player choices, making the game feel dynamic and intelligent.

SEN Alignment: The visual and immediate feedback loop of game design environments is highly effective for kinetic learners and helps maintain focus.
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FOR CODING LESSONS WE HAVE STRUCTURED PROGRAMS
CHILD - > MINECRAFT CODING-> SCRATCH -> APP INVENTOR -> ROBLOX -> PYTHON ( DEPEND ON CHILD AGE)
ADULT -> PYTHON -> ALGORITHMS - > C++ - > CERTAIN NICHE OF THEIR CHOOSING TO BECOME EXPERT (14+)
AND WE TEACH OLD AND YOUNG PEOPLE BASIC KNOWLEDGE ABT PCS AND SMARTPHONE
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I teach coding to beginners and intermediate students.
Lessons focus on logic, basic programming, and practical exercises.
Classes are adapted to the student’s pace.
Students can choose between website or mobile app development.Hands on dev
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This class is designed for beginners who want to start learning robotics in a simple and practical way.

Students will learn the basics of electronics, Arduino programming, sensors, motors, and how to build small real-world projects step by step. No advanced background is required.

The course focuses on hands-on learning: connecting components, writing Arduino code, understanding how robots work, and creating mini projects such as smart fans, automatic lights, and simple robots.

By the end of the class, students will understand how hardware and software work together and will be able to build their own basic robotic systems.

This class is suitable for students, hobbyists, and anyone interested in robotics and technology.
Good-fit Instructor Guarantee
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