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Since October 2018
Instructor since October 2018
Translated by GoogleSee original
Algorithms Course - Desktop/Web Application Programming - SQL
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From 24 € /h
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This course is accessible for all skill levels, from those who want to learn programming to those who are already familiar with it.

Therefore, the purpose of the course will depend primarily on your knowledge and what you wish to learn.

Obviously, if you are a complete beginner, you will be given an algorithm course to familiarize yourself with programming methods.
These algorithm courses will be complemented by exercises in Pascal, Python or Java (or other programming language according to your preference) where other concepts will appear as we go along (procedures, object-oriented, ...).
SQL courses will also be offered for intermediate and/or advanced level students.

The idea of this course is to help you understand concepts either through theory, through kata, or both.

The most advanced courses will focus on frameworks such as Vaadin, JavaFX, ...

In short, feel free to contact me for further information and/or to provide me with the information that will allow me to offer you a tailor-made course that meets your needs.
I remain available for an initial contact to assess your level or knowledge if you need it.
Extra information
Having your own machine (on which you can install software).
Location
location type icon
Online from Belgium
About Me
I am a dynamic person, eager for knowledge but also to share my knowledge.

In this regard, I think Apprentus will teach us both a lot.

I generally try to help people by guiding them towards a solution. My goal is not to provide the answers, but rather to lead you there.
Education
- I am currently pursuing a bachelor's degree in Management Information Systems to obtain the diploma that goes hand in hand with my role and am currently in my final year.
- Playground Training (Video Games) in 2013
- Java training in 2012
- Training in mathematics and programming in 2012
Experience / Qualifications
Developer within an R&D unit since 2015.
My goal is to develop web applications focused on real-time event processing. Primarily in Java, but also in other web languages and/or frameworks.
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Advanced
Duration
60 minutes
120 minutes
The class is taught in
French
English
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
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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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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

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• 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

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• Clustering using k-means, hierarchical clustering, and density-based methods
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• 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.
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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
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This cohort is designed for young people who want to learn in an affordable, flexible, and enjoyable way without having to dedicate a huge amount of time each week or even just extra support.

This beginner-friendly course introduces students to the world of computers and computer science through simple explanation.

Students will learn how computers work, including hardware, software, memory, storage, data, and how a computer processes information. They will then explore how applications are used to create and organize information, with practical experience using tools such as Microsoft Word, PowerPoint, and Excel.

As the course progresses, students will be introduced to important computer science concepts including binary numbers, algorithms, programming, databases, networks, the Internet, and cybersecurity.

By the end of the course, students will have a good foundation in computer science and improved digital skills.
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Data runs the world, and SQL is how you talk to it. Learn to query, design, and manage databases with confidence.

I've worked with SQL and databases for 3 years, building queries, analyzing data, and securing databases behind real applications for government, financial, and telecom organizations. I'll teach you the practical skills used on the job, not just textbook theory. No boring lectures, just live, hands-on practice.

You'll learn:

How databases work: tables, rows, keys, and relationships
Writing queries with SELECT, WHERE, ORDER BY, GROUP BY, and JOIN
Inserting, updating, and deleting data safely
Database design basics: normalization and schemas
Subqueries, aggregate functions, and useful real-world query patterns
Performance basics such as indexes, plus how to keep your data secure and avoid SQL injection

Perfect for: beginners, students, career changers, developers, analysts, and anyone preparing for a data or IT role.

You'll walk away with the ability to write your own queries, understand how data is stored, and a strong foundation for data analysis, development, or backend work.

No experience needed, just curiosity and a computer. Book your first session and let's get querying!
Good-fit Instructor Guarantee
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