Artificial Intelligence and Data Science Courses

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From 18 € /h

These courses offer a comprehensive and progressive path, ranging from the fundamentals of artificial intelligence and data science to advanced mastery of concepts, tools and applications.
The approach adopted combines theory and practice through real projects, challenges and competitions, as well as personalized support to guide each participant in their development.

Each module is designed to:

Build a solid understanding of the principles of AI, machine learning, and deep learning.

Explore data processing, modeling and predictive analysis techniques.

Develop practical skills through concrete and collaborative projects.

Prepare for a career in AI and Data Science through monitoring, mentoring and continuous monitoring of trends and innovations in the field.

It is not simply a series of courses, but a real training and career guidance program, designed to transform curiosity into expertise and learning into a career opportunity.

Location

Online from Morocco

About Me

I obtained my DEUST in mathematics, computer science and physics at the Faculty of Science and Technology. Through this, I gained a solid knowledge base in mathematics and physics, as well as basic computer skills.

By continuing my studies in computer science, I was able to deepen my knowledge in this field, particularly with regard to the logic of algorithms and the use of the Python language for data processing and analysis. I worked on many complex projects which allowed me to master the Python language and its different libraries and frameworks such as Pandas, NumPy, Matplotlib, and Flask.

Currently, I am a first year master's student in Artificial Intelligence at the École Normale Supérieure de l'Enseignement Technique de Mohammedia. This training offers me a solid foundation in this constantly evolving field.

In these courses, my main goal is to provide students with a solid foundation that will allow them to effectively learn and master Python algorithms and language. In addition to theory, we will work on concrete mini-projects to allow students to apply the concepts they have learned. This will enable them to develop practical skills and strengthen their understanding of the subjects, preparing them to take on more complex challenges in these areas.

Education

University degree in Mathematics, Computer Science and Physics.
Bachelor's degree in Computer Science, Networks and Multimedia at the Faculty of Science and Technology.
First year of master's degree in Distributed Systems and Artificial Intelligence at the École Normale Supérieure de l'Enseignement Technique de Mohammedia.

Experience / Qualifications

Provide programming support courses (Python, Algorithms, etc.)
Provide programming support courses (HTML, CSS, etc.)

Age

Preschool children (4-6 years old)

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Student level

Beginner

Intermediate

Advanced

Duration

45 minutes

60 minutes

90 minutes

120 minutes

The class is taught in

French

Arabic

English

Skills

Information technology

Computer programming

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

Computer Science and Programming Course: Algorithms, Python

12 € /h

This comprehensive program offers a deep dive into the world of computer science and programming, covering two essential areas: algorithms and Python. It is designed for beginners, as well as those looking to strengthen their skills in these areas.

Part 1: Fundamentals of Algorithms
In this first section, we'll explore the fundamental concepts of algorithms, including data structures, sorting techniques, searching, algorithmic complexity, and more. You will develop the ability to design, analyze and optimize algorithms to solve a variety of problems.

Part 2: Programming in Python
The second part of the course focuses on programming in Python, a language prized for its simplicity and versatility. You'll learn the basics of Python, including commonly used variables, loops, functions, and libraries. You will put your knowledge into practice by automating tasks, developing web applications, and performing data analysis.

This comprehensive course is ideal for those who want to gain a solid foundation in computer science, from theory to practice. Whether you're an absolute beginner or looking to expand your programming skills, this program will help you achieve your goals

In-depth lessons in mathematics are offered to primary, middle and high school students, as well as private lessons

14 € /h

My courses mainly focus on in-depth understanding of problems in mathematics. They are designed to help students learn how to solve these problems effectively by guiding them through each step of the process. My approach aims to strengthen students' problem-solving skills by providing them with clear and structured methods and techniques.

In addition to detailed explanations, I also provide additional materials to help students with their learning. These materials may include additional exercises, additional examples, and additional resources to deepen their understanding. Additionally, I provide solution documentation for each problem covered, allowing students to check their answers and understand the underlying concepts in more depth.

In summary, my courses aim to provide students with an enriching and interactive learning experience, helping them master math skills while developing their confidence in their ability to solve problems independently.

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Matías

4.85

(13)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Enrique

4.85

(13)

Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.

Gaëlle

4.85

(13)

While adults are still debating whether kids should use AI, they are already using it.
The question isn't "should they?" it's "how do we do it intelligently?"

In this course, your child will discover:
✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't
✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it
✓ What LLMs are (Large Language Models): in language they understand, not tech jargon
✓ Create with AI: custom avatars, interactive stories, real projects using real tools
✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do?
✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life

Why this is different:
Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI.
Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits.
And, more importantly: that they can control how they use it.

What they take home:
Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace

For curious kids asking "How does ChatGPT actually know things?"

Ayoub

4.85

(13)

It is important to me to teach my students while adopting an active teaching method. I put all my experience acquired as a head teacher and also that of my academic career to the service of their success.

- Mathematics
- Chemical Physics,
- Technology.

My courses are aimed at students in the French system from 6th to 12th grade (Speciality: Mathematics, PC).

Giuliano

4.85

(13)

Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

Do you want to create your own software?
Work with data or images?
Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!

Salah

4.85

(13)

Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Pingla

4.85

(13)

Are you looking to bridge learning gaps, boost confidence, or push for top-tier grades? Whether your child is struggling with a specific concept or preparing for crucial exams, this comprehensive tutoring service provides the individualized support needed to succeed.

As a qualified educator with a Bachelor of Accounting Science, a Postgraduate Certificate in Education (PGCE), and a 120-hour TEFL certification, I offer a unique, multi-disciplinary approach to learning. I understand that every student learns differently, and my goal is to simplify complex topics, improve study habits, and foster a genuine understanding of the curriculum.

What this class offers:

Comprehensive Subject Coverage: Assistance across a wide range of school subjects, from foundational literacy and numeracy to advanced mathematics, accounting, and language studies.

Targeted Exam Preparation: Specialized strategies for test-taking, managing time effectively during exams, and tackling high-pressure assessments.

Personalized Learning Plans: Each session is tailored to the student’s current pace and specific curriculum requirements, ensuring they don't just "pass" but truly master the material.

Confidence Building: A supportive, patient, and focused environment where students feel comfortable asking questions and exploring new ideas.

With my background in both formal education and corporate business, I bring a structured, result-oriented focus to tutoring, helping students develop the discipline and analytical skills they will need long after they leave the classroom.

Ready to help your student reach their full potential?
Consistency is key to academic success. Book a session today so we can evaluate your student's current needs, set clear academic goals, and create a customized tutoring schedule that fits your family's routine.

Baia

4.85

(13)

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.

Dr.Ibrahim

4.85

(13)

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.

Meriem

4.85

(13)

Python is today one of the most widely used programming languages in the world, both in Data Science, Artificial Intelligence, Web Development and for task automation.
In this course, I will guide you step by step according to your level:

Beginner: basics of the language (variables, loops, conditions, functions).

Intermediate: data manipulation (Pandas, NumPy), file management, object-oriented programming.

Advanced: practical projects (data analysis, machine learning, automation, API, web scraping).

My goal is to make learning clear, practical, and motivating. You'll not only learn how to code in Python, but also how to structure your projects and apply your knowledge to real-life scenarios.

Laroussi

4.85

(13)

*Goal: To understand artificial intelligence without fear, use it to simplify life, and uncover digital traps.*

### **1: Demystifying Artificial Intelligence (What Exactly Is It?)**

* **Artificial intelligence is not a "movie robot":** The fundamental difference between science fiction and practical reality.
* **How it works (simply):** Imagine a "giant library"; AI has read billions of books and uses them to predict the completion of a sentence or create a new image.
* **Where do we use it now?** The spell checker, Netflix and YouTube suggestions, GPS navigation, and voice assistants such as Siri and Alexa.

---

### **2: Using artificial intelligence to make your life easier**

* **Interacting with artificial intelligence (ChatGPT, Cloud, Gemini):**
* Writing formal emails or complex letters.
* Summarizing long articles or huge documents.
* Plan travel itineraries or create food recipes from ingredients available in the refrigerator.

* **Creativity and Memory:**
* Create creative images for greeting cards (via Midjourney or DALL-E).
Restoring and coloring old family photos.

3: The art of speaking to the machine (the Prompt skill)**

* **Context Style:** Why is the phrase "Give me a cake recipe" less effective than "I have a gluten allergy and I'm having 4 people, give me a simple chocolate cake recipe".
* **Role-taking:** Learn to ask the artificial intelligence to "speak like a tourism expert" or "answer me like a specialized agricultural engineer."

4: Precautions and Critical Thinking (A Survival Guide)**

Digital hallucinations:** Understand that artificial intelligence may confidently present false information (never rely on it for medical or legal advice without verification).
Privacy protection
Do not share sensitive data (ID numbers, passwords, bank details).
Be aware that everything you write may be used to train systems in the future.

Detecting deepfakes:**
How to identify fake photos or videos (examine hand details, strange reflections, or metallic sound).
* The golden rule: Verify by cross-referencing different sources.

5: Ethics and Impact (A Future Perspective)**

Copyright: Who owns the image created by artificial intelligence?
Environmental impact: Water and energy consumption in large data centers.
The future: Will artificial intelligence replace us or will it be an assistant to us?

Additional tip:** Since you are targeting the Gulf region, it is preferable to use terms such as "Digital Transformation" and "Innovation" at the beginning of your presentation, as they are very catchy words for decision-makers there.

Farouk

4.85

(13)

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

Ammar

4.85

(13)

A- TOPICS YOU CAN EXPLORE AND MASTER:
1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
• Lists, tuples, dictionaries, sets, comprehensions, debugging, and writing clear, reusable, well-structured code
• Jupyter Notebook, Anaconda, Visual Studio Code, virtual environments, and package management

2 — PROGRAMMING, ALGORITHMS, AND COMPUTER SCIENCE FOUNDATIONS
• Algorithmic thinking, problem decomposition, pseudocode, flowcharts, procedural programming, object-oriented programming, recursion, and modular program design
• Fundamental data structures including arrays, lists, stacks, queues, dictionaries/hash tables, sets, trees, graphs, and their appropriate use
• Searching, sorting, traversal, algorithm efficiency, computational complexity, Big-O notation, debugging, testing, code organization, and problem-solving strategies
• Practical programming exercises ranging from beginner problems to university-level algorithmic and computational challenges

3- DATA PREPARATION AND EXPLORATION
• NumPy and pandas for importing, cleaning, transforming, filtering, grouping, reshaping, and merging data
• Missing values, duplicates, outliers, inconsistent formats, data leakage, and data-quality validation
• Exploratory data analysis using descriptive statistics, Matplotlib, Seaborn, and graphical interpretation

4- MATHEMATICAL FOUNDATIONS
• Linear algebra, vectors, matrices, derivatives, optimization, probability, and statistics
• Loss functions, gradients, distance measures, regularization, likelihood, and model complexity
• Mathematical concepts are explained according to the learner’s level and the requirements of the selected algorithms

5- SUPERVISED MACHINE LEARNING
• Linear and polynomial regression, logistic regression, and regularized models
• k-nearest neighbours, decision trees, random forests, gradient boosting, support vector machines, and Naive Bayes classifiers
• Classification, regression, model assumptions, decision boundaries, feature importance, and interpretation of results

6- UNSUPERVISED LEARNING
• Clustering using k-means, hierarchical clustering, and density-based methods
• Principal component analysis, dimensionality reduction, anomaly detection, and pattern or structure discovery
• Method selection, evaluation of data structure, and interpretation of results without predefined labels

7- MODEL EVALUATION AND IMPROVEMENT
• Training, validation, and test sets; cross-validation; hyperparameter optimization
• Accuracy, precision, recall, specificity, F1 score, ROC–AUC, confusion matrices, MAE, MSE, RMSE, and R2
• Underfitting, overfitting, bias–variance trade-off, class imbalance, feature engineering, feature selection, scaling, and regularization

8- DEEP LEARNING
• Neural-network foundations, activation functions, forward propagation, backpropagation, and gradient descent
• Multilayer perceptrons, convolutional neural networks, recurrent neural networks, and Transformer foundations
• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

9- ARTIFICIAL INTELLIGENCE APPLICATIONS
• Natural language processing, text classification, embeddings, sentiment analysis, and foundations of language models
• Computer vision, image classification, fundamental principles of object detection, and image preprocessing
• Recommendation systems, forecasting, anomaly detection, intelligent automation, and decision-support applications

10- GENERATIVE AI AND LARGE LANGUAGE MODELS
• Transformer architecture, tokens, embeddings, attention mechanisms, prompt engineering, Retrieval-Augmented Generation (RAG), and model evaluation
• Use of artificial-intelligence APIs, vector databases, document-retrieval systems, and structured AI-enabled workflows when relevant
• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

11- TOOLS AND LIBRARIES
• Python, NumPy, pandas, Matplotlib, Seaborn, scikit-learn, SciPy, Statsmodels, TensorFlow, Keras, and PyTorch
• Jupyter Notebook, Anaconda, Visual Studio Code, Git, GitHub, SQL, Excel, and Power BI when useful to the project
• Additional libraries may be introduced depending on the selected specialization and dataset

12- PROJECTS, RESEARCH, AND INTERVIEW PREPARATION
• Complete projects covering data preparation, model development, evaluation, interpretation, and presentation of results
• University assignments, dissertations, theses, research projects, portfolio projects, technical interviews, and professional applications
• Code review, debugging, documentation, reproducibility, model comparison, and communication of results

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B- PERSONALIZED TUTORING: LEARNING HOW TO REASON
Machine learning and artificial intelligence become much more accessible when mathematics, algorithms, Python code, data, and real-world applications are clearly connected.

My lessons help you move beyond simply copying code or using models as “black boxes.” You will learn how to define the problem correctly, prepare the data, select an appropriate algorithm, understand how it works, train and evaluate the model, diagnose errors, improve performance, and interpret results rigorously and responsibly.

Each lesson is personalized according to your current level, mathematical background, programming experience, dataset, university work, research project, interview preparation, or professional objective. We begin by identifying your existing knowledge, software environment, expected outcomes, and main conceptual or technical difficulties. We then establish a structured learning plan.

The first lesson combines a discussion of your background, objectives, and tutoring needs; an initial assessment of your current knowledge; personalized planning and organization of future sessions; and a short trial lesson to determine the most effective learning approach.

A typical session may include conceptual explanation, development of mathematical intuition, live coding, guided implementation, model evaluation, technical problem solving, and a concise summary of the next steps.

You may work with your own dataset, university assignment, research project, or professional problem, provided that confidential information is handled appropriately. I can also provide structured examples and datasets suited to your level.

My goal is not simply to help you run an algorithm. It is to help you understand why it is appropriate, how it learns from data, how to evaluate it correctly, why it may fail, and how to build a reliable, interpretable, and scientifically rigorous solution.

Abdelmalek

4.85

(13)

Master Industrial Control Systems (SCADA, DCS, IIoT) and automation through tailored, hands-on coaching based on real-world industrial projects! With over 10 years of international engineering, solution architecture, and technical business development experience working with major industry vendors

I offer practical courses designed for engineering students, university undergraduates, and professionals looking to upskill.

The pathway will be in 7 days to cover all basics in OT environnement :
Day 1 - Virtual Environment Preparation for OT projects
- Install Hypervisor on your workstation (A virtual machine).
- Create a Linux VM (Fedora Server).
- Configure 2 networks on the VM: one in NAT (internet access) and one in Host-Only Network (to isolate lab traffic).
- Install basic tools for OT
Day 2: Modbus PLC Simulation (Add 2 Server and test script client to connect)
- Implement Modbus PLC simulators and architecture overview
- Create PLC simulator scripts in src/plc-simulators/
- Add validation test script for Modbus connectivity
- Update Day 2 guide with detailed implementation steps and compatibility notes
Day 3: NGINX Load Balancer Configuration (Round Robin)
- Understand NGINX Stream Module
- Configure NGINX
- Verify and Load the Module
- Troubleshooting NGINX (Activate load balancing in layer 4 protocol, Set permission)
- Step-by-Step Load Balancer Validation
- Test Load Balancing (Round-Robin)
- Test Failover (Resilience)
Day 4 - Creation of the traffic generator (SCADA Client)
- TBD
Day 5 - Traffic capture and measurement with TShark
TBD
Day 6 - Advanced analysis and overload simulation
TBD
Day 7 - Grafana
-TBD
What we can cover together based on your goals: