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Private lessonsNumerical AnalysisNumerical Analysis in Riyadh

1 numerical analysis teacher in Riyadh

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1 numerical analysis teacher in Riyadh

Abdou - Riyadh$32
$32Statistics, data visualization and machine learning for beginners – course in French
📊 Introduction to Data Science with Python Full Title: Statistics, Data Visualization, and Machine Learning for Beginners (100% online course – for students, professionals in retraining, or curious data enthusiasts) Data science is now at the heart of the most innovative professions and strategic decisions in all sectors. However, when you're just starting out, you can quickly feel overwhelmed by technical jargon, Python libraries, or statistical models. With this course, my goal is to make this exciting discipline understandable and accessible to everyone, even without advanced mathematical training or computer science background. I offer step-by-step support based on practical experience, concrete projects, and a supportive teaching approach. You'll learn how to manipulate data, extract information from it, and create your first machine learning models with ease. 🎯 Course objectives Discover the basic tools of Data Science with Python Understand and apply the fundamental concepts of exploratory statistics Know how to manipulate, clean, visualize and interpret real data sets Carry out initial predictive modeling (linear regression, classification) 📚 Course content ✔ Fundamental libraries in Data Science – pandas: reading, cleaning and transforming data – numpy: mathematical operations and array manipulation – matplotlib & seaborn: clear and aesthetic data visualization – Getting Started with Scikit-Learn for Machine Learning ✔ Data cleaning and analysis – CSV file import and data mining – Management of missing values and duplicates – Creation of variables, filtering, groupings – Visualization: histograms, curves, heatmaps, boxplots... ✔ Introduction to Machine Learning – Understand how linear and logistic regression work – First classification models (KNN, simple decision trees) – Data separation (training/test set), single cross-validation – Interpretation of results and improvement of the model 🧭 How the sessions work 1️⃣ Assessment of the student's objectives: discovery, professional project, preparation for training, etc. 2️⃣ Personalized progression plan, adapted to the starting level. 3️⃣ Alternation of visual theory and intensive practice on real data sets (health, sports, finance, etc.). 4️⃣ Practical mini-projects at each stage: analyzing survey results, predicting simple results, automating analyses. 5️⃣ Explanation of errors encountered, individualized educational monitoring. 6️⃣ Regular assessment, with reinforcement of key points as needed. 🌐 100% online courses – accessible teaching methods Classes via Zoom, Google Meet, or the tool of your choice Live screen sharing, work on interactive notebook (Jupyter or Google Colab) PDF supports + commented code provided after each session Possibility of intensive coaching for training or an interview Flexible hours, adapted to the time zone of the Gulf countries and your availability 👨‍🎓 For whom? Complete beginners in Data Science and Python Students wishing to enrich their profile with practical skills Professionals retraining for data professions Anyone curious about understanding the world through data! This course has been designed so that each participant can progress at their own pace, develop their analytical logic and discover the pleasure of "making the data speak". Feel free to contact me to discuss your goals and build a customized program together. I would be delighted to accompany you on this wonderful adventure that is data science.
Statistics · Math · Numerical analysis
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Amine - Paris, FranceRecently active$51
$51PhD Candidate & Experienced Professor - Data Analysis & Advanced Statistics | 300+ people coached | SPSS, R-Studio, Jamovi, JASP
Trusted teacher: ◾ 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
Statistics · Numerical analysis · Computer programming
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Soufiane - Cergy-Pontoise, FranceRecently active$28
$28Post-Baccalaureate Mathematics Courses – Algebra, Analysis, Probability, Statistics, Optimization, Modeling...
Trusted teacher: Hello to post-baccalaureate students (L1/L2/L3 maths/computer science, BUT, preparatory classes, engineering schools, career change)! My name is Soufiane, I have a master's degree in Data Science & AI. I offer 100% practical courses in university mathematics: - Linear algebra (vectors, matrices, eigenvalues, diagonalization) - Analysis (sequences, continuity, differentiation, integrals, series) - Probability (random variables, distributions, expected value, limit theorems) - Statistics (hypothesis testing, regressions, ANOVA, confidence intervals) - Differential and integral calculus (differential equations, functions of several variables) - Optimization (linear, convex, Lagrange, gradient) - Discrete mathematics (graphs, combinatorics, logic) - Mathematical modeling (dynamic systems, simulations) - Applied projects (Python/Matlab/R to validate concepts) Levels: L1/L2/L3 maths, computer science, economics and management BUT, MP/PC/PSI preparatory classes, ATS, Engineering schools (INSA, Centrale, ENSIIE, etc.), Career change / continuing education Why me ? Diagnostic to target gaps & objectives. 100% interactive courses: demonstrations, solved exercises, multiple-choice questions, digital practicals. Professional resources: theorem sheets, summaries, exam-style exercises, PDF answer keys. Flexible hours: evenings, weekends, holidays. At home (Cergy, Pontoise, Sarcelles – free within 15 km) or Zoom + virtual whiteboard Invoices issued. Limited places available (max 8 students). Respond quickly! See you soon to master math and ace your exams!
Math · Statistics · Numerical analysis
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