Introduction to programming applications in VBA (Excel) - Namur

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Introduction to programming applications in VBA (Excel)

From 40 $ /h

Microsoft Office applications contain a development environment which allows the operation of these applications to be adapted to the concrete needs of its users.
I offer you an introduction to programming in Visual Basic for Applications, in order to allow you to get started with macros and the interaction that you can bring to your Excel files.
On the menu :
* Editor interface
* Macro recording
* Analysis of the code generated by the macro recorder
* Programming basics: types of variables, execution flow control instructions and common functions
* Preview of the Excel object model

Extra information

You must have an official version of Microsoft Excel software (minimum version 2016)

Location

Online from Belgium

About Me

Computer scientist (more precisely: analyst-programmer) since the last century (it's been old, I know), I turned to teaching a few years ago now.

I am now an office automation trainer (Word, Excel, Access, Outlook, Powerpoint, VBA) and a programming teacher (all languages: it is the substantive core that is taken from it)

Education

Graduate in IT management - Business School of Namur
Certificate of Educational Aptitudes - Technical Institute of Namur (Social Promotion)

Experience / Qualifications

Computer scientist (analyst-programmer) since 1998:
* Family Allowance Fund (application management + XML exchanges with social security)
* UCM Social Secretariat: management of exchanges with the ONSS; Business Intelligence with SAS
Teacher since September 2020:
* ITN Promotion Sociale (technopedagogue - office automation)
* Business Administration School - SPW (office automation - programming)
* IEPSCF - Namur Cadets (office automation teacher)

Age

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Duration

60 minutes

The class is taught in

French

English

Dutch

Skills

Visual basic

Computer programming

Microsoft excel

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

Personalized support for Microsoft Word software

33 $ /h

Starting from your needs (school work such as TFE, dissertations or institutional to hand in), I will accompany you, step by step, to allow you to take in hand and improve your use of the Microsoft Word software:
* Layout, character and paragraph formatting;
* Insertion of tables, images, SmartArt or other objects;
* Management of layouts, sections and table of contents;
* Management of styles, advanced editing elements;
* Direct mail;
* Creation of macros, text blocks, forms;
(non-exhaustive list)

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I hold a PhD in Mathematical Physics (Theoretical Physics), and I specialize in providing educational support lessons in physics and mathematics. I provide my services to high school and university students, and I have the ability to teach in French, Arabic, and English.

Thanks to my eight years of experience in providing private lessons, I have developed a flexible teaching methodology that adapts to the needs of each individual student. With my experience of more than six years as a professor within the French Mission Program, I have mastered the requirements of this educational system and its special methods. My experience in the field of entrance examinations for graduate schools constitutes an additional advantage for students wishing to continue their studies in prestigious educational institutions.

My passion for physics and mathematics and my strong academic background enable me to explain complex concepts in a clear and understandable way. My goal is to develop students' understanding academically and build their self-confidence, helping them reach their full potential.

I am committed to providing high-quality education, tailored to each student's pace and learning styles, and I strongly believe that every student can excel with the right guidance and support.

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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?"

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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!

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Do you aspire to maximum efficiency, limitless creativity and unparalleled productivity in the Gulf region? Let us guide you to excellence with Microsoft Office.

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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.

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Unlock Your Microsoft Office Potential! Private online classes available in Microsoft Word, Excel, and PowerPoint. Struggling with Microsoft Office? Get personalized help with private online classes in Word, Excel, and PowerPoint. Boost your productivity, create professional documents, analyze data effectively, and design engaging presentations. Learn from the comfort of your home! Inquire today.

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Stuck in Excel? Want to finally understand how those formulas really work? Do you need to create a pie chart of your expense report for work or school, but feel completely lost? Don’t worry! I’m here to help... at your pace, with no jargon or complicated explanations.

Whether you:
- are starting completely from scratch,
- already have some basic knowledge,
- or want to solve a specific problem,
we’ll tailor the session to your needs. No one-size-fits-all course, just practical help that actually works for you.

👨‍🏫 About me
I’ve been using Excel since I was a teenager — for personal use (like budgeting tools or calorie trackers) and professionally as part of my work and studies in data analysis. Thanks to my experience and structured approach, I explain Excel in a clear and understandable way. I know how frustrating it can be when something technical doesn’t work... and how satisfying it feels when it finally clicks.

🎯 Topics we can cover
- Smart formulas (IF, VLOOKUP, INDEX, MATCH, etc.)
- Creating charts, pivot tables, and dashboards
- Using Excel for budgeting, planning, or managing projects
- Data analysis and basic programming in Excel
- Preparing for Excel tests or improving job-related Excel skills

💻 Practical info
- Having your own laptop/PC is helpful, but not required
- Online or in-person sessions possible
- Have specific questions or files you’d like to work on? Let me know! I also have my own practice materials.

Feel free to send me a message with your question or goal. I’ll gladly look at how I can help you out!

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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.

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Online Private Classes: Microsoft Word, Excel & PowerPoint
Unlock your productivity potential with personalized one-on-one training!

📘 Microsoft Word: Master document formatting, reports, and professional layouts.

📊 Microsoft Excel: Learn formulas, charts, and data analysis with ease.

🎤 Microsoft PowerPoint: Create impactful presentations that impress every audience.

👩‍🏫 Private & Flexible: Classes tailored to your level, schedule, and goals. 🌍 Online Access: Learn from anywhere, at your own pace. 🎯 Practical Skills: Focus on real-world applications for work, study, or personal projects.

👉 Start today and gain the confidence to use Microsoft Office like a pro!

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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

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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.

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Learn Python by building something you’ll actually use

Ever wanted to code but had no idea where to begin? You’re in the right place. In these relaxed, one-on-one lessons, you’ll go from zero to writing real programs, with no experience required.

Together, we’ll choose a project that fits your interests. Maybe it’s a video game you want to build or a quiz to challenge your friends, a chart built from your own spreadsheet, or a script that takes over a boring, repetitive task. Along the way, you’ll pick up the essentials (variables, loops, functions) and learn to read error messages without panic, so you can change your code with confidence.

Where you can go next

AI-assisted coding: Use tools like ChatGPT to brainstorm, decode errors, and improve your code, while learning to test its suggestions and explain how the final result works.
Machine learning: Train a simple model on a real dataset and see how well it predicts.
Your own project: Bring an idea from school, work, or a hobby, and we’ll break it into steps you can build at your own pace.

Your instructor

I’m an engineer with a master’s degree from Nagoya University and research experience in applied AI and computer vision. I explain every concept in plain language, then give you time to try it yourself with live feedback, so you’re never stuck alone.

Ready to start?

Send me a quick message and let's do your first coding project together.

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Is your code not doing what you want it to? Are you learning Python but just copying and pasting without really understanding?

Loops, functions, algorithms, data structures... Behind these intimidating concepts lie simple, visual ideas. My goal: to help you understand them, not just apply them.

These tools may seem difficult at first, but they make perfect sense once you visualize them in practice: seeing a loop run, a variable change, a list fill up. That’s the level I’d like to help you reach, using diagrams, analogies, and programs we’ll build together, line by line.

I offer computer science lessons (Python and other languages), from middle school through college, to help you:
- overcome obstacles and regain confidence,
- prepare for your exams (Brevet, Baccalaureate, midterms, entrance exams, NSI),
- make progress on your projects: lab assignments, scripts, games, digital projects...

Each lesson is tailored to your needs: we’ll go over the tricky parts, code together, and I’ll teach you methods to become self-sufficient.

Message me to schedule your first lesson: let’s make the abstract clear!