Computer Science, Artificial Intelligence and Data Science

From 27 £ /h

I have a 10 years of teaching and tutoring experience in Computer Science (Computer Networks, Operation Research, Statistics, Human Computer Interaction), Computer Programming (Python, MATLAB, R Studio), and Data Science (Artificial Intelligence, Machine Learning, and Neural Network). I also have an experience of online teaching sessions, for which I use Pen Tablet based class. I also help students in their assignments, projects, Master thesis and PhD thesis. The student will learn all the above mention subjects or closely related subjects. I also prefer to give small tasks after each session to help students for their understanding (if student requires).

Extra information

Bring your laptop. Pen Tablet will also be beneficiary for online sessions (but not compulsory).

Location

Online from United Kingdom

Age

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

30 minutes

45 minutes

60 minutes

90 minutes

120 minutes

The class is taught in

English

Skills

Computer science

Computer programming

Statistics

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Salah

4.96

(28)

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.

Robert

4.96

(28)

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.

Khalil

4.96

(28)

If you’ve ever felt that science and math are difficult, it’s probably because no one showed you how to think like a problem solver.
In my classes, you’ll learn not just formulas or code but how to truly understand concepts, apply them, and build strong logical intuition.

I teach:
• 🔢 Mathematics: From algebra and calculus to applied problem-solving for real-world use.
• 💻 Computer Science: Coding fundamentals (Python, C++), algorithms, and logical thinking for beginners and intermediate learners.
• ⚛️ Physics: Mechanics, thermodynamics, and practical examples that make abstract ideas simple and visual.

As a Software Engineer and Master’s student in Engineering at Nagoya University, I bring both academic knowledge and hands-on experience from real projects. My teaching approach is interactive, visual, and deeply focused on understanding over memorization.

Let’s turn complex problems into clear, step-by-step insights — and make learning something you genuinely enjoy.

Madara

4.96

(28)

I am a Doctor of Psychology (PhD) and researcher with extensive experience in teaching and mentoring. Since October 2016, I have successfully tutored undergraduate, postgraduate, and Ph.D. students, as well as professionals, in areas including Psychology (AS, A-level (AQA or other exam boards), and degree level), Statistics, Data Analysis, SPSS, Jamovi, JASP, R/RStudio, Research Methods, and in support of research projects, theses, and dissertations.

I specialise in Clinical Psychology, particularly reading disabilities and dyslexia, though I also have strong knowledge across other areas of psychology, research methodology, and data analysis, with expertise in SPSS.

I offer individual, live, one-to-one online sessions via Zoom, tailored to your learning goals. I can also recommend relevant literature and provide resources from my own curated database to support your studies and research.

Reza

4.96

(28)

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! :)

Vincent

4.96

(28)

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.

Dr.Ibrahim

4.96

(28)

This course introduces students to the fundamentals of Information and Communication Technology (ICT) and its role in modern society. Topics include computer hardware and software, digital communication tools, internet technologies, data management, cybersecurity, and emerging trends. Students will gain practical skills in using productivity software, conducting online research, and understanding the ethical and responsible use of digital resources. The course emphasizes both technical proficiency and digital literacy, preparing learners to confidently navigate and contribute to a technology-driven world.

Kevin

4.96

(28)

► 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

4.96

(28)

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

4.96

(28)

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

4.96

(28)

The first year of secondary school prepares students for the prestigious high school diploma! The mathematics program in the final year (whether in Classical or General education) is demanding and requires a solid foundation.

This support from the beginning of the year is specifically designed for students in the Luxembourg system who are moving from 2nd to 1st year of secondary school. The objective is to start now to consolidate what they have learned and fill in any gaps.

📚 Sample program (Adaptable according to the student's section - B, C, D, G, etc.):

Module 1: Consolidation of Foundations (Basic Algebra and Analysis)

Perfect mastery of algebraic calculation, fractions and powers.

Solving complex equations and inequalities.

In-depth review of derivatives and the study of functions (variation tables, asymptotes).

Module 2: Introduction to the key concepts of the 1st

Introduction to logarithmic and exponential functions (ln and exp).

Introduction to integral calculus (calculating areas).

Depending on the section: Complex numbers, analytic geometry in space, or probability/statistics.

Farouk

4.96

(28)

These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework

Fisnik

4.96

(28)

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.

Baia

4.96

(28)

I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects

Atharva

4.96

(28)

About me:

- Quantum Machine Learning Researcher
- Upcoming Intern at the Indian Space Research Organisation
- Fluent in ML + DL + RL + Agentic AI + GANs

Want to learn Data Science and Machine Learning but don't know where to start?

My classes are designed for students, beginners, and aspiring developers who want to understand how Machine Learning works and how to implement it using Python.

I focus on building strong fundamentals, explaining concepts intuitively, and connecting theoretical knowledge with practical applications.

Topics covered:

- Python for Data Science
- NumPy and Pandas
- Data cleaning and preprocessing
- Exploratory Data Analysis (EDA)
- Statistics and fundamentals of Data Science
- Supervised Learning: Linear Regression, Logistic Regression and Classification
- Decision Trees and Random Forests
- Model training, evaluation and performance metrics
- Overfitting, underfitting and model optimisation
- Introduction to Unsupervised Learning and Clustering

Whether you're a college student exploring Machine Learning, a beginner interested in AI, or someone looking to strengthen their Data Science foundations, these classes will help you develop a structured understanding of the subject.

**No prior Machine Learning experience is required. Basic Python knowledge is helpful but not mandatory.**