Learn Algorithms and Computer Programming

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From 60 € /h

The term computing is a neologism proposed in 1962 by Philippe Dreyfus to characterize the automatic processing of information. So, IT deals with two complementary aspects: the immaterial programs (software, software) which describe a processing to be carried out and the machines (hardware, hardware) which execute this processing.

The objective of this course is to teach you to design an ordered sequence of instructions which indicates the procedure to follow for
to solve a series of equivalent problems, as well as to characterize their validity, their robustness, their reusability, their complexity or their efficiency in a programming language understandable by the computer.

As Abelson et al. said, each computer program is a model, forged by the mind, of a real or imaginary process. These processes, which arise from human experience and thought, are innumerable and complex in their details. At any time, they can only be partially understood. They are rarely modeled in a satisfactory way in our computer programs. Although our programs are sets
symbols carefully carved, mosaics of intertwined functions, they never stop evolving. We modify them as our perception of the model deepens, expands and generalizes, until reaching a metastable equilibrium at the borders of another possible modeling of the problem. The joyful intoxication that accompanies computer programming comes from the continual back and forth between the human mind and the computer, the mechanisms expressed by programs and the explosion of new visions that they bring. If art translates our dreams, the computer realizes them in the form of programs.

Extra information

Have a computer and basic knowledge of information representation

Location

Online from France

About Me

I am a doctoral researcher at the University of Artois, EA 3926, F-62400 Bethune, France. Holder of a Master 2 Basic Computer Science, Computer Mathematics License, Baccalaureate Series C Mathematics and Physical Sciences.

My constructivism and socio-constructivist methodology consists in supporting the student towards knowledge, taking into account the situation of the student and his global environment which necessarily impacts on the approach and on the capacities of the learner. Personalized demonstration of the answer according to the difficulty identified in the student from the question asked.

Education

Master 2 Basic Computer Science in 2017, Bachelor's Degree in Computer Mathematics in 2013, Baccalaureate Series C Mathematics and Physical Sciences in 2010 at the University of Dschang

Experience / Qualifications

I am a Researcher, Temporary Teacher, Computer Monitor, Webmaster and Full-stack developer.

Programming languages: Android, Java, J2ee, JSP, Shell, C / C ++, C #, Windev, CTL, HTML, jQuery, JavaScript, Ajax, CMS (Joomla, Wordpress), PHP, CSS, VBS, ERP, VoIP, Python

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

French

English

Skills

Computer science

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

Gaëlle

5.0

(3)

Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations

Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.

5.0

(3)

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

Negar

5.0

(3)

Are you interested in learning programming, Artificial Intelligence, or Machine Learning but don't know where to start? I offer personalized lessons designed for beginners, students, and professionals who want to build strong practical skills in computer science and AI.

In this course, you will learn:

1. Programming & Algorithms
a) Programming fundamentals and problem-solving techniques
b) Algorithm design and data structures
c) Writing efficient and clean code

2. Python Programming (Beginner to Advanced)
a) Python basics, object-oriented programming, and advanced concepts
b) Using Python for real-world applications in:
I) Machine Learning
II) Computer Vision
III) Robotics
IV) Data Science
c) Scientific Python (NumPy, Pandas, Matplotlib)

3. Artificial Intelligence & Machine Learning
a) Core AI concepts and algorithms
b) Deep Learning fundamentals
c) Practical projects using modern AI tools and frameworks

Lessons are adapted to your background and goals, whether you are starting from zero, preparing for university courses, or looking to apply AI in your own projects.

Feel free to contact me if you have any questions. I look forward to helping you explore the world of AI!

Adam

5.0

(3)

doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

Zakaria

5.0

(3)

* This digital training aims to introduce you to the Scratch tool and through the game world, and gradually, to discover programming concepts such as loops, conditions or variables. It is aimed at anyone who is new to Scratch and who wants to create games and animations.

* Learning programming will allow students to develop their skills and will certainly allow them to meet the expectations of the future working world and emerging careers.

* In addition, learning programming allows the development of algebraic, algorithmic and computational thinking. Programming also helps to improve and develop students' sequencing ability, as well as their communication skills. Thus, there are several advantages to teaching programming, but the important thing is to remember that this learning teaches students that digital is not only for entertainment, but that it is possible to become creators. active and creative content.

Salah

5.0

(3)

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.

Hassane

5.0

(3)

Hello,

My name is Hassane, and I've been passionate about computers for over 20 years. With two decades of teaching experience, I've had the privilege of supporting learners of all ages and levels in developing their computer skills and achieving their professional and personal goals.

Computer science is an essential skill today, opening the door to countless opportunities. Whether you want to learn programming, website design, data analysis, or complex problem-solving, I'm here to guide you every step of the way.

What I propose:
In my classes, we explore a wide range of topics to meet the needs of both beginners and advanced learners:

Computer fundamentals: master the basics to get started, Hardware, Software, Binary, Operating system.
Programming: learn to code efficiently in different languages (C#, Python, VBA).
Web development: creating modern websites and applications.
Databases: understanding, managing and analyzing data, UML, MERISE.
Project management: Ms-Project, Agil, Scrum, Kanban

Teaching methods:
I adopt a dynamic and interactive approach to ensure a rich and enjoyable learning experience:

Interactive courses: clear explanations adapted to your pace.
Practical exercises: to immediately apply the concepts learned.
Collaborative projects: developing real solutions as a team.
Personalized monitoring: answer your questions and support your progress.
Why choose me?
20 years of experience in computer teaching.
Proven methods suitable for all levels.
Personalized support to help you achieve your goals.
A passion for passing on skills that make a difference.
Whether you are a student, a professional looking to retrain, or simply curious, my courses will provide you with the tools you need to succeed in this rapidly evolving field.

Join me today!
Please contact me to learn more or to discuss your specific needs. Together, let's build your digital future.

Hassane
Experienced computer teacher and trainer

Hayat

5.0

(3)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Yomna

5.0

(3)

This course is designed to introduce students aged 7 to 16 to the world of programming through two of the most widely used and industry-relevant languages: C++ and Python.

The class provides a structured, age-appropriate pathway into programming, whether the student is a complete beginner or already exploring coding through platforms like Scratch or Code.org. Emphasis is placed on understanding logic, building problem-solving skills, and writing real code in a supportive, project-based environment.

Taught by an engineering student with hands-on experience in both C++ and Python, this course empowers students to explore the power of code and build a strong foundation in computational thinking — essential for future studies in engineering, robotics, AI, or game development.

Mohamed

5.0

(3)

This fun and interactive course introduces kids and teens to the fundamentals of coding using Scratch, a visual programming language developed by MIT. Students will learn to create games, animations, and interactive stories while developing problem-solving, logical thinking, and creativity skills—all in a playful, drag-and-drop environment!
Who Should Join?
✔ Kids & teens curious about coding and game design
✔ Young learners who enjoy storytelling, art, or technology
✔ Future coders looking for a fun introduction to programming

5.0

(3)

For boys and girls who like games and want to understand and try out how AI moves characters, stories, and worlds.

You don't need to know how to program. You just need curiosity and a computer.

What do we do?
• Characters that don't stay still: in Scratch (or similar) we program an NPC that reacts to the player (follow, flee, change mood, choose a dialogue).
• Pieces of the world: how to sketch textures, backgrounds or a backstory with generative tools and what is okay to use or not (rights, copying style from a famous game, etc.).
• Branching story: a simple decision tree so the game changes depending on the player's choices.

Each session looks for something that can be taught at home: a character that reacts, a minimal map, a dialogue with two endings.

Rhythm
If it's engaging, a block of 6–8 sessions is enough for a mini-game or a playable scene. Sessions are 60 minutes long.

Recommended age: 10–16 years. If they are younger but already comfortable with Scratch, they may also be a good fit.

Ali

5.0

(3)

I offer one-to-one Programming tuition in Python, C, and C++, for GCSE Computer Science, A-Level Computing, and university students studying engineering, computer science, or related subjects. Lessons are available online or in person around Birmingham.

What I cover:

Python for beginners and intermediate learners
C and C++ programming
GCSE and A-Level Computer Science (all exam boards)
University coursework support, debugging help, and project guidance
Core concepts: variables, loops, functions, data structures, object-oriented programming, file handling, basic algorithms

How I teach:
I start by understanding exactly where you are — whether that's "I've never coded before" or "I'm stuck on a specific assignment." Then I build lessons around small, practical examples you can actually run and modify yourself. I'm patient with errors (everyone gets them), and I make sure you understand the why behind the code, not just how to copy it. For university students, I can also help with debugging, code reviews, and explaining tricky concepts in plain English.
If you or your child is preparing for exams, working on coursework, or just wants to finally feel comfortable with coding, I'd love to help.

Ammar

5.0

(3)

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

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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

5.0

(3)

This hands-on training pathway is designed to help students kickstart any project, specifically tailored for OT labs and industrial applications. Starting from absolute scratch, students will build a strong foundation in Python programming through practical, industry-relevant concepts.

Curriculum Outline: |
01 - Python Environment Setup & Basics |
02 - Python Variables, Numbers, Bytes & Hex |
03 - Control Flow Logic Functions |
04 - Data Structures (Lists, Tuples, Dictionaries & Sets) |
05 - String Formatting, Comprehensions & Exception Handling |
06 - File IO, Pathlib & Context Managers |
07 - Object-Oriented Programming (Classes & OOP) |
08 - Standard Library, Modules & Networking Basics |

Assessment & Evaluation:
Students will take a mini-test after the completion of each module. Additionally, an Audit & Performance Evaluation report will be sent following the tests.
Duration:
5 days to 15 days (depending on the pace of the cohort)

Baia

5.0

(3)

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