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I adopt a personalized and clear approach for each student. I simplify complex concepts through diagrams and summaries, facilitating understanding and assimilation. Each course is structured around the explanation of concepts, followed by practical exercises to reinforce learning. I also make sure to monitor the student's progress and adapt my methods according to their specific needs. My courses are aimed at high school students studying general economics and statistics, as well as undergraduate and graduate students in economics and related disciplines.

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My approach is to explain concepts using simple explanations with daily life examples. I love discussion-based teaching. I have taught Game Theory to Students as a tutor at University College Dublin. Also, I am taking personal tuitions for many years in India. I have worked in Evelyn Learning Pvt Limited, India as a Statistics Solver. I used to provide solutions to statistical problems and exercise. I have a pretty well experience of teaching.

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[FR/ENGL] Are you preparing for math assessments or exams? I'm here to help! I offer private lessons in math, statistics, and data science, designed to maximize your chances of success. My approach is based on personalized teaching, clear explanations, and concrete exercises tailored to your needs. During our sessions, we can review theoretical concepts, work on specific exercises or prepare for an exam in a targeted manner. Together, we will put all the chances on your side! Are you preparing for math assessments or exams? I'm here to help you succeed! I offer one-to-one tuition in mathematics, statistics and data science, designed to maximize your chances of success. My approach is based on personalized teaching, clear explanations and concrete exercises adapted to your needs. During our sessions, we can review theoretical concepts, work on specific exercises or prepare for an exam in a targeted way. Together, we'll put all the chances on your side!

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I offer personal tutoring and study guidance in a wide variety of subjects, tailored to your level and learning style. Together, we'll create a clear plan so you can stay organized, learn more efficiently, and achieve better results. In addition to content-based tutoring, I'll focus on learning strategies, study planning, and self-confidence—so you'll not only improve your grades but also enjoy learning. The lessons are entirely online, but I ensure a personal and interactive approach. Using an iPad and the option to share PDFs, I create an atmosphere similar to private lessons at your home. Everyone learns in their own way and has unique goals; therefore, I tailor my approach to your needs. We tailor the program together to your goals.

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Throughout my teaching career, I have consistently strived to make mathematics accessible and enjoyable for learners of all levels, from elementary to advanced. I believe that mathematics is not just a subject but a tool for problem-solving and critical thinking, and I am committed to instilling this mindset in my students. My approach to teaching emphasizes clear explanations, hands-on activities, and a supportive atmosphere where every student can thrive. I have a proven track record of helping students grasp complex mathematical concepts, and I take great pride in their academic achievements. I am passionate about inspiring a love for math and helping students build the skills and confidence needed to excel in their academic pursuits. I look forward to the opportunity to contribute my expertise, dedication, and enthusiasm to your educational institution, helping students of all levels achieve their full potential in mathematics.

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MATLAB is a programming and numeric computing platform used by millions of engineers and scientists to analyze data, develop algorithms, and create models. I professionally program in MatLab since 2005 and propose classes for all levels and requirements.

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Do you need to complete the statistical modeling part in your dissertation or pfe? Do you find it difficult to analyze and interpret the results found? Do you need help using statistical analysis software (SPSS, R, Eviews, etc.)? ****************** DO NOT PANIC ... ****************** Support sessions are at your disposal to help you carry out your modeling parts via statistical analysis tools (methodologies and software) and according to the correct rules for interpreting the results (analysis of data tables, statistical tests, linear regression, logit/probit models, time series, etc.)

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Sat math test includes 3 main part. Problem Solving and Data Analysis is about being quantitatively literate. It includes using ratios, percentages, and proportional reasoning to solve problems in science, social science, and career contexts. The Heart of Algebra focuses on the mastery of linear equations and systems, which helps students develop key powers of abstraction. Passport to Advanced Math focuses on more complex equations and the manipulation they require.

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I specialize in teaching Hands on Machine learning with Python. I can teach with real case studies and in layman's language. This class is for the candidates aspiring to learn data science or having problem with their projects or any other work.

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My name is Christelle, I recently graduated from a research masters in Genetics and Psychology and I am now working as a PhD student in the genetics of Obsessive Compulsive Disorder. I completed both my Bachelor in Psychology, and Master’s at the Vrije Universiteit Amsterdam. I have experience with teaching statistics / methodology courses to Psychology and Political Science students. I can offer help in statistics, methodology, biological psychology, and statistical programming in R. Other tasks I can offer my help for: feedback on written assignments, help in designing scientific figures or presentations.

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Greetings! I am a geospatial analyst at Transport for London and I specialise in running statistical analysis in R and Python, as well as analysing large sets of data and building and running Geographic Information Systems (GIS) through different technologies. As part of my specialisation, I teach and assist early and mid-career individuals with data science and statistics, including the programming languages Python and R. I would be more than happy to help with specific projects the students have in mind, if applicable. Otherwise, I have student-focused study programmes that provide the foundations as well as more advanced knowledge and skills. Feel free to contact me for a chat!

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PhD student in Applied Mathematics offers mathematics, statistics courses for high school students, bachelor's and master 1 & 2 as well as college I have experience for 6 years

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As a teaching professional, I have always enjoyed sharing my knowledge. My goal is to provide quality education. I am aware that some topics may seem complex, but often this is simply the result of insufficient explanation on the part of the teacher. With me, you will discover a real interest in the subject! We work together to achieve academic excellence, overcoming the shortcomings and difficulties encountered by your child. Studying will become a pleasant experience for him. In addition to lessons, I can also help with academic guidance, identifying their preferences and highlighting the advantages and benefits of a fulfilling educational ambition. The sessions generally take place according to the following stages: 1️⃣ The first sessions are devoted to the assessment of the student's level in order to detect existing gaps. 2️⃣ Next, we establish a personalized plan to fill these gaps, including the number of work hours needed, specific areas to target, and appropriate training and development exercises. 3️⃣ We remain in constant contact with the student's class teacher, to stay informed of the latest requirements and ensure a consistent approach. 4️⃣ Subsequently, I provide exams similar to those likely to be taken in class, to effectively prepare the student. 5️⃣ Upon request, I write a regular report, usually monthly, to keep parents informed of their child's progress throughout their journey. I adapt my methodology according to the specific needs of each student, thus offering them a personalized and adapted work approach. In addition, I offer intensive internships to students preparing for the start of the school year, allowing them to start the year well prepared, with a solid lead on the school program. If you have any questions, do not hesitate to contact me. I will be happy to help you.

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I'm graduated in quantitative Finance and I have a master degree in Financial Mathematics. I'm currently working as a quant in a top Tier bank. This module covers: - Basic statistics (expected value, variance, mean, ...); - Random variable theory; - Regression analysis; - Stochastic processes (AR, MA, ARMA, ARIMA, white noise); - Calibration of models on real data;

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I hold an academic bachelor's degree in Mathematics with distinction and a master's degree in Data Science & Biostatistics with great distinction from Hasselt University. I also have a degree in acting and am a former scout leader (so I have some experience with children). I also worked as a full-time 3rd-grade math teacher for some time. I am currently a PhD candidate in statistics at Hasselt University and teach statistics in various bachelor's programs. We'll explore the problems in a pleasant, relaxed manner, and I'll focus on guiding students through the material, rather than blindly applying it as quickly as possible. Thanks to my years of experience, I also have plenty of exercises and sample exams available.

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Analyst Statistician Analyst and Actuary gives mathematics and statistics courses for all levels. Help with the realization of the statistical and quantitative part during a Bachelor or Master project. Mastery of SPSS and R software Private individual lessons and / or small groups. Ps: Since I'm no longer in Lausanne, I give my classes largely by Skype but I also move to Zurich.

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This class covers statistics and statistical methods for data analysis which cuts across all industry and disciplines. Sample topics, Statistical calculations Statistical methods Statistical analysis Quantitative analysis Quantitative analysis techniques Non Quantitative data analysis Research methods Research methods paper section Mathematical analysis Statistical software and spreadsheets like Rsutdio, Excel, SPSS, and many others. and any statistical topic requests by students

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This lesson provides a simplified and practical introduction to the principles of statistical analysis and is suitable for students and researchers who wish to understand the basics of data analysis in a clear and organized way. We start with the basics, then gradually move on to data analysis, hypothesis testing, and understanding the relationships between variables, with a focus on how to choose the appropriate statistical method and read and interpret the results. Lesson topics: 1. Introduction to Statistical Analysis * The concept of statistics and statistical analysis. * Data types and variables. Levels of measurement. * The difference between descriptive and inferential statistics. 2. Descriptive Statistics Frequencies and percentages. * Arithmetic mean. * Median and mode. * Range and standard deviation. * Reading and interpreting statistical tables and results. 3. Fundamentals of Hypothesis Testing * The concept of the null hypothesis and the alternative hypothesis. * Level of statistical significance (Sig. / p-value). * Understanding the concept of statistical significance. * How to make decisions regarding hypotheses. * Getting acquainted with basic statistical tests and choosing the appropriate test in a simplified manner. 4. Correlation analysis * The concept of the relationship between variables. * Correlation coefficient and interpretation of the direction and strength of the relationship. * Understanding the statistical significance of correlation. 5. Regression analysis * The concept of regression and its importance. Simple and multiple linear regression. * Understanding the relationship between the independent variable and the dependent variable. * Interpretation of the coefficient of determination (R2). * Reading the main results of the regression analysis. 6. Practical application using SPSS * Data entry and organization. * Conducting basic statistical analyses. * Reading SPSS output. * Interpreting the results in a simplified and academic manner. The aim of the lesson: By the end of the lesson, the student will be able to understand the main fundamentals of statistical analysis, work better with data, choose the appropriate analysis initially, and read and interpret basic statistical results using SPSS. This lesson is particularly suitable for students of "Business Administration, Economics, Administrative Sciences, and researchers" who need a strong foundation in statistical analysis.

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This class is for people who already write some Python and now want to build machine learning and generative AI systems that work outside a notebook. I am a Lead Data and Machine Learning Engineer in Berlin with 9 years at Amazon, Delivery Hero, Goldman Sachs and Orion S.A., and I teach the same methods I use at work. WHO IT IS FOR Developers and analysts moving into machine learning or AI roles. Students who understand the theory but have never shipped a model. Founders and product people who want to build a real AI feature rather than a demo. Anyone preparing for machine learning or AI engineering interviews. WHAT WE COVER Framing a problem: what is predictable, what is not, and how to tell before you waste a month. Core machine learning: regression, classification, tree based models, feature engineering. Model evaluation done properly: leakage, class imbalance, baselines, and why your accuracy score is lying to you. Deep learning and natural language processing foundations. Large language models in practice: prompting, structured output, evaluation and cost control. Retrieval augmented generation end to end: chunking, embeddings, vector databases, reranking, and measuring whether the answers are actually correct. Agents and tool use with LangChain and LangGraph. Deployment: turning a model or an AI feature into a service, plus monitoring and drift. HOW IT WORKS We agree on a target project in the first lesson and build towards it. You write the code, I review it live and explain the reasoning. You leave with a working system in your own repository rather than a folder of tutorials. I will tell you honestly when an approach will not survive real traffic or real data. That is the main reason to learn this from someone who runs it in production. PRACTICAL DETAILS Lessons are in English, online via webcam, and I work comfortably across time zones. You need working Python basics for this class. If you are starting from zero, book my Python, SQL and Machine Learning class instead and we build up to this one.

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Hello, I help students understand and master statistics and probability, succeed in their modules, midterms and exams, and ensure the accuracy of the statistical section of their dissertations and projects. A PhD in mathematics and a public sector teacher, specializing in teaching statistics and probability at the university level, I draw on twenty-six years of experience. Many students don't get stuck on the calculations themselves, but on the meaning: which test to choose, how to interpret a result, what conclusion to draw. That's exactly what I clarify, using concrete examples rather than abstract formulas. WHAT I COVER • Descriptive statistics with one variable: measures of central tendency and dispersion, distributions. • Graphical representations: histograms, box plots, diagrams... • Bivariate descriptive statistics (with two variables): cross-tabulations, covariance, correlation. • Regression and adjustment. • Probabilities: counting, conditional probabilities, independence. • Random variables and distributions: mass function, density function, distribution function, marginal and conditional laws, expectation and variance. • Common distributions: discrete (Bernoulli, binomial, Poisson...) and continuous (normal, Student, Fisher, chi-square...). • Sampling methods: choice of sample size and types of sampling. • Estimation and confidence intervals. • Hypothesis testing: goodness-of-fit test, comparison of means (normal or Student's t-distribution), chi-square test (independence, goodness-of-fit), analysis of variance (Fisher/ANOVA)... • Getting started with the tools: Excel, SPSS, R. FOR WHOM • Students in economics, management, science and health (biostatistics). • Top business and finance schools. • Higher education institutions and undergraduate programs. • Methodological support for dissertations and theses: analysis plan, choice of tests, data processing and interpretation. MY METHOD • Understand before calculating: give meaning to each concept. • Exercises and real-world case studies tailored to your field of study. • Reading and interpreting the results, not just obtaining them. • Targeted preparation for exams and presentations. HOW ARE THE CLASSES CONDUCTED? At home or online (stylus and graphics tablet, for a clear and interactive whiteboard). Structured sessions, at your own pace, with availability between lessons via messaging. WHAT YOU CAN COUNT ON • A doctor who has mastered the subject matter and knows how to make it clear. • An applied, results-oriented and interpretation-driven approach. • Reliable support up to the exam or defense. • An initial session to identify your needs and set a goal. CONTACT For any questions or to arrange an initial exchange, contact me via Apprentus messaging.