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Since February 2024
Instructor since February 2024
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Master the Fundamentals of Data Science and Artificial Intelligence
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From 54 C$ /h
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Welcome to the Data Science course where you will discover the art and science of transforming data into actionable insights.
In this captivating journey, we'll explore the fundamentals of Data Science, diving into the key concepts and essential techniques for analyzing and interpreting data. You will learn the basics of data cleaning and preparation, data exploration and visualization, and advanced machine learning and predictive modeling techniques.

Whether you are a curious beginner or a professional looking to hone your skills, this course offers a practical, in-depth approach to help you become a Data Science expert. Join me to explore the vast possibilities offered by the world of data together and become a master in the art of data manipulation and analysis.
Get ready to unleash the power of data and transform your understanding of the world around you!
Extra information
There are no specific prerequisites for this course other than the availability of a personal computer, a good internet connection and a quiet environment for an optimal learning experience.
Location
location type icon
Online from Canada
About Me
I am an AI Engineer with a Master’s degree in Software Engineering, specialized in artificial intelligence and machine learning. My background combines strong academic training with real-world experience designing and building intelligent systems. I am passionate about making complex technical concepts accessible and practical. As a teacher, I focus on clarity, structure, and deep understanding rather than memorization. I believe every student can master technical subjects when explanations are adapted to their level and learning style. My teaching approach is patient, structured, and example-driven, with a strong emphasis on applying theory to real projects. I enjoy working with motivated students who are curious and ambitious, whether they are beginners starting programming or advanced learners working on AI, research, or professional development. My goal is not only to help students succeed academically, but also to help them build confidence and real technical skills they can use in their careers.
Education
I hold a Master’s degree in Applied Software Engineering with a specialization in Artificial Intelligence and Machine Learning. During my studies, I developed strong foundations in algorithms, data structures, software architecture, and advanced AI systems, including machine learning, deep learning, and natural language processing. I also completed an engineering diploma in computer science, which provided me with rigorous technical training and hands-on experience in building complex software systems. My academic path has always combined theoretical depth with practical implementation, allowing me to understand both the mathematical foundations and the engineering aspects of intelligent systems.
Experience / Qualifications
I currently work as an AI Engineer, where I design and implement intelligent systems, machine learning models, and AI-driven automation solutions. I have extensive experience in Python programming and have worked on projects involving data science, large language models, multi-agent systems, and advanced software engineering workflows. My background includes research experience in AI for software engineering, where I focused on improving the reliability and performance of intelligent systems. In addition to my professional work, I have experience mentoring and guiding students in programming, machine learning, and research projects. I am comfortable supporting learners at different levels, from foundational programming concepts to advanced AI implementation and technical interview preparation. My strength lies in combining academic rigor with industry experience to provide practical, high-quality instruction.
Age
Preschool children (4-6 years old)
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
French
English
Arabic
Reviews
Availability of a typical week
(GMT -04:00)
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
Hello everyone !
As a student of software engineering and deep learning, I am passionate about mathematics and its application in the fields of artificial intelligence and machine learning.

With a patient approach, I strive to make complex mathematical concepts accessible to everyone. My methodology is both clear and interactive, promoting in-depth and stimulating learning. I'm here to support you every step of the learning process, encouraging you to explore and master the essential foundations of mathematics.

Join me on a dynamic journey to mathematical excellence, where we will work together to expand your understanding and strengthen your skills
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Do you want to learn how to build websites from scratch?

With this online course, you will learn HTML & CSS by building beautiful, modern and responsive websites! You will have a strong foundation in web development that will enable you to start creating any website you can imagine.

By the end of this course, you will be competent in HTML & CSS and be able to create your own professional-grade website from scratch – no prior experience required! You will also have the skillset necessary to continue learning about web development and advancing your career.

What is HTML & CSS?
HTML and CSS are the two most important languages for a new web developer to learn. They are also the easiest. If you’ve always wanted to build webpages, but were intimidated by the code, I will help you through my course to learn your first two languages quickly and easily.

Taking a step-by-step approach, this course will have you learning by doing, building several mini-websites from scratch.

Every webpage that you see on the internet is built using code. There are many different programming languages that can make your website do various things, but the two most important to learn are HTML and CSS. In fact, even people who plan on allowing someone else to build their website should have a basic grasp of both languages. This way you can tweak things behind the scenes, or change some of your formatting without having to always rely on others.

This course of lectures and presentations gives you a basic, yet thorough understanding of both HTML and CSS. The course focuses on having you begin writing code right away so you can learn through doing, and build your own completely functional HTML and CSS webpage at the end.

You’ll begin by learning what HTML and CSS are, so you can get an understanding of what it is that they do. During the course you’ll build several mini-websites that take what it is that you’ve learned and apply it to real world exercises to help cement the skills.

Everyone from aspiring web designers to bloggers, programmers to business owners, company employees and tech hobbyists can benefit from learning some HTML and CSS! Learn to build your own dynamic and beautiful websites or manage the website that you already have.

If you plan on becoming a web programmer or a web designer yourself, HTML and CSS are the first two languages you’ll need to succeed. In fact HTML is required for anyone that wants to get into web development from any angle. Learning it simultaneously with CSS allows you to hit the ground running with page design.
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While adults are still debating whether kids should use AI, they are already using it.
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✅ Cybersecurity: Ethical hacking, data protection, network security
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📌 Developed interactive lesson plans integrating real-world applications of technology.
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• Target audience: all levels, regardless of diploma, class or specific characteristics.
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The path and the method are in there; take a little bit of each.

Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online.

I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises.

Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam.

All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me.

My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress.

My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).
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I teach machine learning, AI and Python online to university students, postgraduates, career changers and serious beginners across the UK and Europe. Lessons are in English.

I hold an MSc in Electronics and Electrical Engineering with Distinction and I teach as a Visiting Lecturer on a Master's level module covering data analytics, machine learning and generative AI at a UK university. I also have two accepted international conference papers on deep learning for image classification. I set and mark postgraduate assignments myself, so I know where marks are won and lost on this kind of work.

Who this is for

Undergraduates and postgraduates on AI, ML, data science or computer science modules at any European university. Final year, Master's and thesis students working on a machine learning project. IB and A Level students moving into computing or engineering. Professionals retraining for data roles. Complete beginners who want to learn Python properly rather than copying it from videos.

I work with students on UK, IB and continental European programmes. I have tutored engineering students in Germany and international school students across several countries, so an unfamiliar syllabus or a module taught in a different structure is not a problem. Send me the material and I will work from it.

What we cover

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How lessons work

Send me your module handbook, assignment brief, thesis spec or the code that will not run, and I plan the session around it before we meet. Nothing generic.

In the lesson I explain the concept with a worked example, then you take the keyboard while I watch and correct, because you learn far more doing it than watching me do it. You finish with annotated notes and a clear next step, and you can message me between sessions with questions.

Practical details

Online over Google Meet or Zoom with screen sharing and a shared whiteboard. Sessions run 60 or 90 minutes. I am based in the UK and teach across GMT and Central European time, with evening and weekend slots that suit students anywhere in Europe.

Tell me your course, your deadline and exactly where you are stuck, and I will come back with a plan for the first session.
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This interdisciplinary program equips you with the fundamental skills of a modern engineer by combining applied mathematics, physics, and scientific computing. Designed as a coherent whole, this course shows you how these three disciplines work together to solve real-world engineering problems.

Mathematics Module: Numerical analysis, computational linear algebra, differential equations and optimization methods adapted to physical modeling.

Physics Module: Mechanics of systems, thermodynamics, electromagnetism and wave phenomena with rigorous mathematical equation formulation.

Computer Science Module: Scientific programming in Python, numerical simulation, algorithmic solving of physical and mathematical problems, data visualization.

Pedagogical approach: Each theoretical concept is immediately put into practice through integrated projects. For example, you will mathematically model a pendulum, establish the physical equations of its motion, and then develop a Python program to simulate and visualize its behavior.
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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.
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• 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

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verified badge
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Kinematics: Study of rectilinear and circular movements, position vectors, speed and acceleration.
Dynamics: Newton's laws, work and energy, kinetic energy theorem.

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Electrostatics: Electric charges and fields, electric potential, capacitance.
Magnetostatics: Magnetic fields, Lorentz forces, electromagnetic induction.
Alternating Currents: RLC circuits, resonance, impedance.

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Ideal and real gases: Equations of state, thermodynamic transformations.

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Automatic Linear, Kinematic, Static.

For more information and to register for the preparation session, please contact me.

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.
verified badge
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verified badge
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.
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This course provides a foundational understanding of Information Technology, data centers, covering architecture, power & cooling, networking, storage, virtualization, security and lots more. Learn best practices for efficiency, scalability, and reliability while exploring emerging data center solutions. Ideal for IT professionals, engineers, and facility managers involved in data center deployment or management.

This course offers a comprehensive exploration of Information Technology, data center infrastructure, guiding students through the entire lifecycle—from initial design and planning to day-to-day operations and long-term performance optimization. Students will learn the critical components of data center design, including site selection, power and cooling systems, space planning, networking, and physical security. The course also covers operational best practices, monitoring tools, energy efficiency strategies, disaster recovery planning, and emerging trends. By integrating technical, environmental, and management perspectives, students will gain the knowledge and skills required to build and maintain high-performance, cost-effective, and sustainable data center environments.
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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.
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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?
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Working part-time in the watch industry, I have been tutoring for several years in the context of refresher, occasional support or preparation of exams or competitions. Very experienced in relation to the difficulties encountered by students and pedagogue, I adapt to the needs of each to quickly regain the necessary confidence, the methodology of mathematical reasoning and allow a rapid improvement of results.
Experienced and pedagogue, I adapt to the needs of the student to help him consolidate his knowledge methodically, to regain confidence and improve as quickly as possible its results. I teach these courses in a radius of 30 km around Geneva.
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• Teaching methodology and techniques: I favour a personalized approach, adapting the courses according to the profile and academic background of each student.
• Typical course structure: tutoring in economics, econometrics, statistics and probability, financial mathematics, trading, investment, or political economy. Courses can take place at home, via videoconference, or at a pre-selected location, ideally quiet, free, and conducive to learning.
• Specifics as a teacher: I offer support throughout the school year, with free corrections of exercises outside of class, regular availability, and the guarantee of being accessible until the end of the year, subject to the general conditions of Superprof.
• Target audience: all levels, regardless of diploma, class or specific characteristics.
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The path and the method are in there; take a little bit of each.

Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online.

I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises.

Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam.

All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me.

My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress.

My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).
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I teach machine learning, AI and Python online to university students, postgraduates, career changers and serious beginners across the UK and Europe. Lessons are in English.

I hold an MSc in Electronics and Electrical Engineering with Distinction and I teach as a Visiting Lecturer on a Master's level module covering data analytics, machine learning and generative AI at a UK university. I also have two accepted international conference papers on deep learning for image classification. I set and mark postgraduate assignments myself, so I know where marks are won and lost on this kind of work.

Who this is for

Undergraduates and postgraduates on AI, ML, data science or computer science modules at any European university. Final year, Master's and thesis students working on a machine learning project. IB and A Level students moving into computing or engineering. Professionals retraining for data roles. Complete beginners who want to learn Python properly rather than copying it from videos.

I work with students on UK, IB and continental European programmes. I have tutored engineering students in Germany and international school students across several countries, so an unfamiliar syllabus or a module taught in a different structure is not a problem. Send me the material and I will work from it.

What we cover

Python for data science with NumPy, Pandas, Matplotlib and scikit-learn. Deep learning using TensorFlow and Keras. Core theory including regression, classification, clustering, decision trees, random forests, neural networks and CNNs, together with the linear algebra, calculus and statistics underneath them. Computer vision and image classification, which is my published research area. Model evaluation, overfitting and hyperparameter tuning. Writing machine learning work up to academic standard, covering methodology, results and critical evaluation.

How lessons work

Send me your module handbook, assignment brief, thesis spec or the code that will not run, and I plan the session around it before we meet. Nothing generic.

In the lesson I explain the concept with a worked example, then you take the keyboard while I watch and correct, because you learn far more doing it than watching me do it. You finish with annotated notes and a clear next step, and you can message me between sessions with questions.

Practical details

Online over Google Meet or Zoom with screen sharing and a shared whiteboard. Sessions run 60 or 90 minutes. I am based in the UK and teach across GMT and Central European time, with evening and weekend slots that suit students anywhere in Europe.

Tell me your course, your deadline and exactly where you are stuck, and I will come back with a plan for the first session.
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This interdisciplinary program equips you with the fundamental skills of a modern engineer by combining applied mathematics, physics, and scientific computing. Designed as a coherent whole, this course shows you how these three disciplines work together to solve real-world engineering problems.

Mathematics Module: Numerical analysis, computational linear algebra, differential equations and optimization methods adapted to physical modeling.

Physics Module: Mechanics of systems, thermodynamics, electromagnetism and wave phenomena with rigorous mathematical equation formulation.

Computer Science Module: Scientific programming in Python, numerical simulation, algorithmic solving of physical and mathematical problems, data visualization.

Pedagogical approach: Each theoretical concept is immediately put into practice through integrated projects. For example, you will mathematically model a pendulum, establish the physical equations of its motion, and then develop a Python program to simulate and visualize its behavior.
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