Learn how to build easily machine learning models.

From 41 C$ /h

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves

Extra information

have your own laptop

Location

Online from United Kingdom

Age

Children (7-12 years old)

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

Greek

Skills

Python

Statistics

Computer science

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Robert

4.74

(27)

As a Franco-Belgian management teacher, I give Excel lessons with passion!
Whether remotely or face-to-face, I offer many examples and exercises to accompany you.
I travel without problem throughout the region of Brussels and its surroundings, for lessons of at least 2 hours. For France, courses are only given remotely.

Here are some key words that will be covered in my classes:
Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking

Do not hesitate to contact me to organize your lessons according to your needs and availability. Together, we will develop your Excel skills in an efficient and personalized way.

Adam

4.74

(27)

Demystifying probabilities and data processing
Statistics and probability occupy an increasing place in the secondary school curriculum and directly prepare students for the requirements of higher education (economics, medicine, engineering, humanities).

The sessions will include:

Descriptive statistics (means, standard deviations, graphical representations).

Conditional probabilities, probability laws and combinatorics.

Analysis, interpretation of datasets and sampling logic.

Targeted training based on typical exercises and exam problems.

Leila

4.74

(27)

I am an IB-certified Mathematics educator with formal certification in IB Math HL and IB MYP Mathematics, and I have served as an IB Mathematics Examiner within the IB Examiner Network. I also have extensive experience teaching Cambridge and British curriculum mathematics, including IGCSE, AS-Level, A-Level, Edexcel, GCSE, and O-Level.
I specialize in supporting students across leading international curricula, helping them build strong mathematical foundations while mastering the specific assessment criteria, exam techniques, and problem-solving styles required by each system.
Curriculum coverage includes:
IB MYP Mathematics
IB Diploma Programme: Math AA (HL / SL), Math AI (HL / SL), Internal Assessments (IA)
Cambridge & British Curriculum: IGCSE, AS-Level, A-Level, Edexcel, GCSE, O-Level
My teaching approach is analytical, structured, and results-oriented. I help students:
understand how marks are awarded in IB and Cambridge exams
choose efficient and correct solution methods
communicate mathematics clearly and precisely
avoid common examiner-level mistakes
prepare confidently for internal assessments and final exams
As an IB Examiner, I bring insider insight into how student work is evaluated, which allows me to guide students strategically—not only toward correct answers, but toward high-scoring solutions.
With over 12 years of international teaching experience, including work in international schools and at the university level, I support both high-achieving students and those who need to rebuild structure and confidence. Sessions are calm, focused, and personalized to each student’s academic goals.

Sincerely,
Leila

Amin

4.74

(27)

Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Salah

4.74

(27)

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 an inadequate explanation by the teacher. With me, you will discover a real interest in the material!

We strive together to achieve academic excellence, overcoming the shortcomings and difficulties encountered by your child. Studies will become a pleasant experience for him. In addition to the courses, I can also help with school orientation, 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 create a personalized plan to address these gaps, including the number of hours of work needed, specific areas to focus on, and appropriate training and development exercises.

3️⃣ We stay in constant contact with the student's class teacher, to keep up to date with the latest requirements and ensure a consistent approach.

4️⃣ Subsequently, I provide exams similar to those that are likely to be asked in class, to prepare the student effectively.

5️⃣ Upon request, I write a regular report, usually monthly, to keep parents informed of their child's progress throughout their course.

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 crash courses for students preparing for the start of the school year, allowing them to start the year well prepared, with a solid lead on the school curriculum.

If you have any questions, do not hesitate to contact me. I will be happy to help you.

Reza

4.74

(27)

You will learn Systematic Reasoning & Logical Thinking which is a requirement for entering Computer Science program in many universities.
The book “Delftse Foundations of Computation” especially its second chapter will be the main source of our lesson, but other more in-depth books will be also covered if you want to improve even further on logical thinking.
The topics in our lesson include:
• Propositional Logic: Logical operators; Precedence rules; Logical equivalence; Implications in English; Exclusive or; Universal operators; Classifying propositions
• Boolean Algebra: Substitution laws
• Logic Circuits: Logic gates; Combining gates to create circuits; From circuits to propositions; Disjunctive Normal Form; Binary addition.
• Predicate Logic: Predicates; Quantifiers; Tarski’s world and formal structures;
• Deduction: Valid arguments and proofs; Proofs in predicate logic

If you have any additional questions before starting a class, please feel free to ask me. I am here to assist! :)

Baia

4.74

(27)

I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.

Vincent

4.74

(27)

With over seven years of experience in teaching Computer Science & Information Technology (ICT), I have developed a strong expertise in delivering high-quality education across multiple internationally recognized curricula, including Cambridge IGCSE, GCSE, A-Levels, O-Levels, and Checkpoint. My passion lies in equipping students with coding, cybersecurity, and digital literacy skills, ensuring they are well-prepared for the evolving demands of the digital world.

Expertise & Teaching Areas:
✅ Programming & Software Development: Python, Java, C++
✅ Cybersecurity: Ethical hacking, data protection, network security
✅ Digital Literacy: ICT applications, online safety, cloud computing
✅ Data Science & AI: Data analysis, machine learning fundamentals
✅ Web Development: HTML, CSS, JavaScript

Curriculum & Pedagogical Experience:
🔹 Cambridge IGCSE & GCSE ICT & Computer Science – Teaching core and extended syllabi, focusing on programming logic, databases, and networking.
🔹 Cambridge A-Levels & O-Levels Computer Science – Preparing students for advanced computing concepts, problem-solving, and algorithm development.
🔹 Cambridge Checkpoint ICT – Building foundational skills in digital technology and computer applications.

Professional Impact:
📌 Mentored students to achieve top grades in Cambridge ICT & Computer Science exams.
📌 Developed interactive lesson plans integrating real-world applications of technology.
📌 Conducted coding boot camps and cybersecurity workshops to enhance practical learning.
📌 Guided students in project-based learning, including app development and website design.

With a strong commitment to student-centered learning and technological innovation, I am dedicated to shaping future tech leaders and empowering learners with skills relevant to careers in technology, data science, and software development.

Kevin

4.74

(27)

► EXPERT STATISTICS, DATA ANALYTICS, MACHINE LEARNING & AI TUTOR FROM SWITZERLAND
► UNIVERSITY, FOUNDATION, IB, A-LEVEL & INTERNATIONAL SCHOOL SUPPORT

I completed my Master’s degree in Business Information Systems at a Swiss University of Applied Sciences, where my academic background strongly combined mathematics, statistics, data analysis, analytical thinking and problem-solving. This technical and data-oriented foundation shaped the way I teach today: clearly, logically and with a strong focus on real understanding.

For many years, I have successfully supported students in Statistics, Data Analytics, Machine Learning and AI. My main focus is especially on Statistics — from basic descriptive statistics to advanced statistical methods, hypothesis testing, regression, probability distributions and interpretation of results.

I mainly use R for statistical analysis, data handling, visualisation and practical exercises. My goal is not only to help students calculate results, but to make sure they understand what the results mean and how to explain them correctly.

► STATISTICS, DATA ANALYTICS & AI SUPPORT

► STATISTICS & PROBABILITY
I help students understand descriptive statistics, probability, random variables, distributions, sampling, confidence intervals, hypothesis testing, p-values, correlation, regression and statistical interpretation. My lessons focus on explaining the logic behind each method, not just applying formulas.

► APPLIED STATISTICS WITH R
I support students in using R for statistical analysis, data cleaning, visualisation, hypothesis testing, regression models and interpretation of outputs. Students learn how to connect theory, calculation, code and real meaning step by step.

► QUANTITATIVE METHODS & RESEARCH STATISTICS
I help students with statistical methods used in business, economics, psychology, social sciences, science and university research. This includes choosing the correct test, understanding assumptions, interpreting results and presenting findings clearly.

► DATA ANALYTICS & DATA SCIENCE
I support students with data preparation, exploratory data analysis, visualisation, dashboards, summary statistics and practical interpretation. The focus is always on understanding the data and drawing meaningful conclusions.

► MACHINE LEARNING & AI FOUNDATIONS
For students working with modern data topics, I also provide support in the foundations of Machine Learning and AI, including regression, classification, clustering, model evaluation and practical applications. These topics are explained from a statistical point of view, so students understand the logic behind the models.

► UNIVERSITY, FOUNDATION & INTERNATIONAL COURSES
I support students in Statistics, Data Analytics, Business Analytics, Quantitative Methods, Econometrics, Research Methods and technical modules. I help with exam preparation, assignments, projects and practical data analysis tasks.

► HOW I TEACH

► I FOCUS ON REAL STATISTICAL UNDERSTANDING.
Statistics becomes much easier when students understand why a method is used, what the result means and how to interpret it correctly.

► I EXPLAIN FORMULAS STEP BY STEP.
Difficult formulas, tests and models are broken down into simple, logical parts so students can follow the reasoning clearly.

► I CONNECT THEORY WITH R PRACTICE.
Students learn not only the statistical theory, but also how to apply it in R, read the output and explain the result in proper academic language.

► I HELP STUDENTS CHOOSE THE RIGHT METHOD.
Many students struggle with deciding whether to use a t-test, chi-square test, ANOVA, regression or another method. I teach students how to recognise the correct approach from the question or dataset.

► I TRAIN INTERPRETATION AND EXAM TECHNIQUE.
Students learn how to structure statistical answers, write clear conclusions, explain p-values, interpret confidence intervals and present results professionally.

► I ADAPT EVERY LESSON TO THE STUDENT.
Some students need help with theory, others with R coding, assignments, research projects or exam preparation. I adjust every lesson to the student’s exact course, level and goals.

► YEARS OF EXPERIENCE WITH STATISTICS, DATA & UNIVERSITY STUDENTS

Over the years, I have successfully supported students from demanding academic programmes, helping them strengthen their statistical understanding, improve their analytical thinking and achieve excellent progress in Statistics, Data Analytics, Machine Learning and AI.

► ONLINE LESSONS

► Interactive whiteboard
► Clear digital notes
► Step-by-step statistical explanations
► R support for data analysis
► Exam preparation
► Assignment and project guidance
► Practical examples with real datasets
► Focused one-to-one support from Switzerland

► MY GOAL

My goal is not only to help students pass exams or complete assignments, but to help them truly understand Statistics. With the right guidance, statistical methods become logical, practical and much easier to apply.

► SUBJECTS: Statistics, Probability, Data Analytics, Data Science, Machine Learning, AI, Quantitative Methods, Research Methods, Econometrics
► MAIN TOOL: R
► LEVELS: International School, IB, A-Level, Foundation Courses, University Modules, Professional Training
► FORMAT: Online tutoring from Switzerland
► FOCUS: Statistical understanding, R practice, interpretation, exam preparation, assignments, projects and long-term analytical confidence.

Brent

4.74

(27)

Are you drowning in countless formulas? Is your head starting to explode with equations and graphs? Don't panic! Math doesn't have to be a stumbling block. With the right explanation and a calm approach, it often becomes much clearer. Together, we'll tackle it step by step, at your pace.

For whom?
- Students from primary and secondary education
- Children and young people preparing for exams or tests
- Anyone who wants to give mathematics a second chance, including adults

What can you expect?
- I explain the often complicated mathematical language in clear, human language
- Focus on insight, not just learning tricks and formulas by heart
- Exercises that we tackle together
- Space for questions, repetition and building self-confidence
I can also prepare exercises and even complete practice exams myself.

About me
I'm currently pursuing my Master's degree in Data Science/Analytics at the University of Antwerp. In high school, I had seven hours of math a week and always passed my exams with high marks. I've been happily tutoring students of various levels for several years now. I'm analytical, but also calm, patient, and good at sensing exactly where things are going wrong.

Practical:
- 1-on-1 lessons, online, at my place or at yours (if you don't live too far away)
- We will go through your material together or I will provide my own material
- Your own pace and approach, completely tailored to you

I have already successfully guided students with:
- Mathematics in secondary education: from the 1st to the 6th year, for various fields of study and schools, including Latin at Sint-Michielscollege Brasschaat, Economics-Mathematics at KA Schoten, and Humanities at Annuntia.
- Arithmetic in primary education: pupils in the 4th, 5th, and 6th grades, including mental arithmetic, written calculation, and other arithmetic skills.
- Mathematics in the Electromechanics program at AP University of Applied Sciences.

Feel free to send me a message with your questions or concerns, and we'll discuss how I can best support you.

Mariem

4.74

(27)

Understanding algorithms is essential for anyone pursuing computer science or programming. In this course, I provide a structured approach to learning algorithms—from fundamental concepts like sorting and searching to advanced techniques such as dynamic programming and graph theory. Whether you're preparing for exams, coding interviews, or aiming to improve your problem-solving skills, this course is designed to build strong algorithmic thinking. Through practical examples and step-by-step explanations, I help students master the logic and techniques needed to write efficient and elegant code.

Raouf

4.74

(27)

Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty.

1: Demystifying AI (What exactly is it?)
AI is not a movie robot: Difference between fiction and reality.

How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image.

Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa).

2: Using AI to make life easier
Conversing with AI (ChatGPT, Claude, Gemini):

Ask him to write an administrative email or a complex letter.

Summarize a long newspaper article or document.

Plan a travel itinerary or find recipe ideas with what's left in the fridge.

AI for creativity and memory:

Generate images to illustrate a birthday card (Midjourney, DALL-E).

Using AI to restore or colorize old family photos.

3: Learning to "talk" to AI (The Art of the Prompt)
The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe".

The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener".

4: Precautions and Critical Thinking (The Survival Guide)
"Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification).

Privacy protection:

Never give sensitive data (social security number, passwords, bank details) to an AI.

Knowing that everything we write to the AI is potentially used to train it.

Spotting "Deepfakes":

How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice).

Verify the information: the golden rule of cross-referencing sources.

5: Ethics and Impacts (To go further)
Copyright: Who owns an image created by AI?

The environmental impact: The water and energy consumption of AI servers.

The future: Will AI replace us or assist us?

Fisnik

4.74

(27)

Do you have a statistics or probability exam in BA1/BA2? I can help you review the material in a clear, structured and exam-oriented way.

I support higher education students (university and college), particularly in their first and second years of undergraduate studies, to understand important concepts, redo practical exercises, and practice with exam-style questions.

My goal is simple: to help you understand the logic behind formulas, know when to use them, recognize correct reasoning in a statement, and gain autonomy when facing exercises.

Subjects covered according to your program:

• Descriptive statistics:
mean, median, variance, standard deviation, quartiles, quantiles, coefficient of variation, box plots, histograms, graphs, interpretation of tables and data.

• Univariate and bivariate statistics:
analysis of one variable, analysis of two variables, scatter plots, covariance, correlation, regression line, coefficient of determination, interpretation of relationships between variables.

• Probabilities:
events, union, intersection, complement, conditional probabilities, independence, Bayes' theorem, probability trees, contingency tables.

• Combinatorial probabilities:
permutations, arrangements, combinations, draws with or without replacement, counting, classic exam situations.

• Random variables:
discrete and continuous variables, probability function, density function, distribution function, expectation, variance, standard deviation, variable transformation.

• Probability laws:
Bernoulli distribution, binomial distribution, normal distribution, standard normal distribution, Student's t-distribution, chi-square distribution, use of statistical tables according to your course.

• Statistical inference:
sampling, estimators, point estimation, confidence intervals, margin of error, degrees of freedom, confidence level.

• Hypothesis testing:
null hypothesis H0, alternative hypothesis H1, significance threshold, p-value, one-tailed or two-tailed test, test on a mean, test on a proportion, chi-square test, interpretation of results.

• Exam preparation:
reading statements, choosing the right method, identifying the formulas to use, typical exercises, past exams, guided corrections and problem-solving methods.

Method of working :

1. We quickly identify the chapters that are causing problems;
2. I re-explain the theory with simple examples;
3. We redo the important exercises together;
4. I will show you how to recognize good reasoning in the exam;
5. We construct a clear method that can be reused independently.

I don't just provide a correction: I explain the reasoning step by step so that you are able to redo the exercises without help.

For students retaking the exam, I also offer more intensive support: level assessment, priority identification, review of fundamentals, and practice with typical exercises and past exams. The goal is to get straight to the point and work efficiently within the time available before the exam.

I have been giving private lessons for over 7 years in mathematics, statistics, economics, and accounting. I have also tutored first and second-year Bachelor's students at Solvay/ULB in mathematics, statistics, and microeconomics as part of a university tutoring program.

My professional experience in finance and business controlling at Deloitte has also allowed me to develop a very structured approach to numbers, analysis and problem-solving.

Courses available in French or English, online or in person in Brussels or the surrounding area.

Daniel

4.74

(27)

Currently in Master 2 of Random Modeling at the University of Paris Cité, after a rigorous research Master focused on dynamic systems, I dedicate my expertise to Bachelor (L1, L2, L3) and Master (M1) students facing the demands of scientific and economic fields.

Objective: Zero obstacles. A targeted support system to help you pass your exams and entrance exams.

Pratiksha

4.74

(27)

Python Level 1Workshop

**Course Description**

Want to learn programming from scratch? This beginner-friendly Python course introduces students to coding through interactive lessons, practical exercises, and fun mini-projects.

Students will learn how to write Python programs, work with different types of data, take user input, make decisions using conditions, and repeat actions using loops. Each concept is explained step by step with real-life examples and hands-on coding activities.

**What You Will Learn**

* **Lesson 1: Your First Python Program** — Learn the `print()` function, display messages, and create simple programs.
* **Lesson 2: Variables and Data Types** — Store and work with text, numbers, and other basic data.
* **Lesson 3: User Input and Calculations** — Build interactive programs that accept user input and perform calculations.
* **Lesson 4: Conditional Statements** — Use `if`, `elif`, and `else` to make programs respond to different situations.
* **Lesson 5: Loops and Mini-Projects** — Use loops to repeat actions and apply your skills in practical coding challenges.

**Hands-On Projects**

Students will apply their learning by building beginner-friendly projects such as a calculator, a number-guessing game, and a Rock-Paper-Scissors game.

**Who Is This Course For?**

* Children and teenagers aged 8–16.
* Complete beginners with no prior programming experience.
* Students who want to develop logical thinking, problem-solving, and computational skills.
* Learners who want to explore programming through practical projects.

**My Teaching Approach**

I explain concepts step by step, use relatable examples, and encourage students to write their own code instead of simply copying solutions. Lessons are adapted to each student's pace, with coding exercises and challenges to strengthen understanding.

**No prior coding experience is required.** Students need a computer and an internet connection to participate.

By the end of Level 1, students will have a solid foundation in Python basics and the confidence to start creating their own simple programs.