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Since July 2025
Instructor since July 2025
Learn Excel VBA from Scratch: Automate Excel Even with Zero Experience!
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From 13 £ /h
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This course is designed for complete beginners who want to learn Excel VBA programming from the ground up. Whether you're a student, professional, or freelancer, you’ll learn how to automate tasks, create intelligent macros, design simple forms, and manage data efficiently within Excel.

🔧 What You Will Learn:

The basics of programming: variables, loops, conditions, and procedures.

How to record and edit simple macros.

Automating tasks across cells, worksheets, workbooks, and named ranges.

Creating interactive forms (UserForms) for data entry and display.

Automating repetitive tasks like formatting, reporting, and even sending emails.

Exploring advanced tools: events, error handling, and integration with other applications.

🎯 Who Is This Course For?

Students, employees, or freelancers who work with Excel and want to save time.

Professionals looking to build custom tools tailored to their workflow.

No previous coding experience is required!

🛠️ Course Methodology:

Step-by-step, hands-on learning.

Clear explanations with real-life examples.

Tips on writing clean, understandable, and reusable code.
Extra information
📈 Final Goal:
Become independent in Excel VBA, capable of building your own professional tools and automations.
Location
location type icon
Online from Morocco
About Me
✅ What I teach:
• Programmation using MATLAB/excelVBA
• Mathematics (Middle school, High school, University level)
• MATLAB and Simulink (modeling, simulation, power systems)
• Renewable Energy (solar, wind, hybrid systems)
• Electrical Engineering (circuits, control systems, embedded systems)

🧠 My lessons are:
• Clear, interactive, and tailored to your level
• Focused on problem-solving and real-world applications
• Available in English, French, or Arabic

🌟 Whether you are a student, a researcher, or just passionate about tech, I will help you understand complex concepts with ease and confidence.

🔧 Tools I use: MATLAB, Simulink, STM32, Multisim, PSIM, Excel, Arduino...

🚀 Book the first lesson and let’s achieve your goals together!
Education
🎓 I hold an Engineering Degree in Electrical Engineering and Renewable Energies (5-year program, equivalent to a Master’s degree), I’ve worked as a technical trainer in electrical and renewable energy engineering.
Experience / Qualifications
🎓 I hold an Engineering Degree in Electrical Engineering and Renewable Energies (5-year program, equivalent to a Master’s degree), I’ve worked as a technical trainer in electrical and renewable energy engineering.
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
Arabic
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
Are you planning to travel, work, or live in Morocco? Or maybe you just want to understand and communicate with Moroccan people in their everyday language?
This course is designed to help you learn Moroccan Arabic (Darija) in a simple, practical, and enjoyable way.

🔹 What you will learn:

Essential vocabulary and expressions for daily life (greetings, shopping, transportation, food, work, etc.)

How to introduce yourself and hold basic conversations

Useful phrases for travel, business, and social situations

Pronunciation tips and cultural insights to sound more natural

Step-by-step lessons adapted to your level (beginner, intermediate, or advanced)

🔹 Teaching Method:

Interactive and conversational approach

Real-life dialogues and examples

Practice-oriented lessons with role-play and exercises

Personalized support to match your goals

🎯 Goal: By the end of this course, you will be able to communicate confidently in Darija, understand common conversations, and feel more comfortable in Moroccan culture.

Whether you are a complete beginner or want to improve your speaking skills, this course will help you speak Darija naturally and with confidence.
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Master Microsoft Office, the essential tools of the professional world!

Do you want to gain efficiency and confidence with Excel, Word, and PowerPoint? Whether you're a beginner or already familiar with the basics, my customized course will guide you step by step to become independent and efficient.

What you will learn:
Excel: from data entry and formatting to advanced formulas, pivot tables, etc.

Word: Professional document creation, styles, table of contents, mail merge, and advanced layout.

PowerPoint: Design impactful presentations, animations, and visual storytelling techniques.

Why choose this course?
✔️ Adapted progression: from total beginner to advanced user, everyone progresses at their own pace.
✔️ Practical and personalized approach: concrete exercises linked to your personal or professional projects.
✔️ Flexible: online courses, individual
✔️ Complete educational support: documents, tips and personalized follow-up between sessions.
✔️ Certified expertise: experienced trainer with an engineering background and several years of professional training
Read more
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🐍 Learn Python from Scratch — Think, Solve & Code!

Have you always wanted to learn Python programming but didn't know where to start?

Or maybe you've already started learning Python but some concepts still feel confusing?

Don't worry — you're in the right place! 😊

I'm Reza, a Computer Engineer, teacher, and technology enthusiast. I have a Master's degree in Computer Systems Architecture, I am currently studying Artificial Intelligence, and I have experience teaching programming and computer science to students with different backgrounds and skill levels.

🧠 Before Python: Learn How to Think Like a Programmer

For me, learning Python isn't just about learning commands and syntax. The most important part of programming is learning how to think when you face a problem.

Before jumping into code, we'll learn how to understand a problem, break it into smaller pieces, identify what information we have and what we need to find, and develop a step-by-step solution. Then we'll turn that solution into Python code.

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💻 What will you learn?

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Python fundamentals and programming concepts
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if statements and decision making
for and while loops
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Functions and reusable code
Working with files
Error handling and debugging
Problem-solving, reasoning, and programming logic
Algorithmic thinking and step-by-step solution design
Object-oriented programming
Practical Python exercises and projects
Introduction to Python for Artificial Intelligence and Machine Learning
🎯 My teaching style

I don't want you to simply memorize Python commands.

I want you to understand how programmers think.

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I believe that learning by doing is one of the best ways to learn programming.

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And don't worry if you're a complete beginner. You don't need any previous programming experience to start.

👨‍💻 Who are these Python lessons for?

My classes are suitable for:

Complete beginners who have never programmed before
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University and school students
People who want to improve their programming skills
Anyone who wants to learn Python for personal or professional development
Students interested in eventually moving toward Artificial Intelligence, Machine Learning, or Data Science

I'll adapt the lessons to your level, your goals, and your learning speed.

🚀 Let's learn Python together!

Learning to program can seem difficult at first, but it doesn't have to be.

With the right explanation, enough practice, and a little patience, you can go from writing your first print() statement to building your own Python programs.

My goal is simple:

Think Clearly. Solve Problems. Learn Python. Build Something.

If you're ready to start learning Python, book your first lesson and let's write some code together! 🐍💻
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Description:
This course is ideal for beginners or intermediate learners who want to learn programming using languages like C#, Java, or Python. With a step-by-step approach, you'll be guided from basic algorithms to object-oriented programming.

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Introduction to algorithms and their implementation.
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Video lessons: Clear explanations and practical exercises.
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Weeks 1–2. How an AI “learns”
With short projects, we observe data, patterns, and biases. The goal is not to memorize definitions, but for students to be able to explain, in their own words, why a tool is right or wrong.

Weeks 3–4. Create with discernment
Art, stories, or game ideas using generative tools. We work on prompts, what can be published, privacy, copyright, and when not to use AI (for example, to copy homework).

Week 5. Final Project
A mini-project of their own: a co-written story, a series of images, a simple classifier, a game idea... Something they can show at home and explain how they did it.

What does the family take with them?
• a 5-week overarching theme, not random, aimless classes
• Safe usage habits that are also useful at school
• Finally, a completed project and a brief note on how to proceed.

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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.

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🎯 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.
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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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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:
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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.
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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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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)
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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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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.
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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.
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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!
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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
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* 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.
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Become a Trading Pro with NinjaTrader!

Are you passionate about trading and want to master one of the most powerful trading platforms on the market? If so, this ad is for you!

As a seasoned NinjaTrader expert, I offer personalized courses to help you master this exceptional trading platform. Whether you want to learn how to trade manually or automate your strategies using C# and custom indicators, I'm here to guide you every step of the way.

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- In-depth training on using NinjaTrader, including navigating the interface, executing orders, and analyzing the markets.
- Detailed instructions on creating and optimizing automated trading strategies using C#.
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Whether you are looking to generate additional income through trading or make trading your full-time career, my courses will provide you with the knowledge and skills needed to succeed in the financial markets.

Don't miss this opportunity to become a true trading expert with NinjaTrader! Contact me today to reserve your spot and begin your journey to financial success.
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🐍 Learn Python from Scratch — Think, Solve & Code!

Have you always wanted to learn Python programming but didn't know where to start?

Or maybe you've already started learning Python but some concepts still feel confusing?

Don't worry — you're in the right place! 😊

I'm Reza, a Computer Engineer, teacher, and technology enthusiast. I have a Master's degree in Computer Systems Architecture, I am currently studying Artificial Intelligence, and I have experience teaching programming and computer science to students with different backgrounds and skill levels.

🧠 Before Python: Learn How to Think Like a Programmer

For me, learning Python isn't just about learning commands and syntax. The most important part of programming is learning how to think when you face a problem.

Before jumping into code, we'll learn how to understand a problem, break it into smaller pieces, identify what information we have and what we need to find, and develop a step-by-step solution. Then we'll turn that solution into Python code.

We'll practice logical thinking, reasoning, problem-solving, algorithmic thinking, and debugging along the way. My goal is to help you become someone who can look at a new problem and think, "Okay, how can I solve this?" — not someone who only remembers Python syntax.

💻 What will you learn?

In my Python classes, we can start from the very beginning and gradually build your programming skills. We'll combine programming fundamentals with problem-solving and practical coding, so you understand not only how to write Python, but also how to approach a programming problem.

Depending on your level and goals, we can cover topics such as:

Python fundamentals and programming concepts
Variables and data types
Numbers, strings, and text processing
if statements and decision making
for and while loops
Lists, tuples, dictionaries, and sets
Functions and reusable code
Working with files
Error handling and debugging
Problem-solving, reasoning, and programming logic
Algorithmic thinking and step-by-step solution design
Object-oriented programming
Practical Python exercises and projects
Introduction to Python for Artificial Intelligence and Machine Learning
🎯 My teaching style

I don't want you to simply memorize Python commands.

I want you to understand how programmers think.

During our lessons, I explain concepts in simple language and then we practice them together. You'll learn how to analyze a problem, think about possible solutions, write code, test it, find mistakes, and improve your solution. You'll make mistakes, ask questions, and gradually become more confident.

I believe that learning by doing is one of the best ways to learn programming.

So instead of spending the whole lesson listening to me, you'll actually write Python code and practice what you've learned.

And don't worry if you're a complete beginner. You don't need any previous programming experience to start.

👨‍💻 Who are these Python lessons for?

My classes are suitable for:

Complete beginners who have never programmed before
Students who want to learn Python from the basics
University and school students
People who want to improve their programming skills
Anyone who wants to learn Python for personal or professional development
Students interested in eventually moving toward Artificial Intelligence, Machine Learning, or Data Science

I'll adapt the lessons to your level, your goals, and your learning speed.

🚀 Let's learn Python together!

Learning to program can seem difficult at first, but it doesn't have to be.

With the right explanation, enough practice, and a little patience, you can go from writing your first print() statement to building your own Python programs.

My goal is simple:

Think Clearly. Solve Problems. Learn Python. Build Something.

If you're ready to start learning Python, book your first lesson and let's write some code together! 🐍💻
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Description:
This course is ideal for beginners or intermediate learners who want to learn programming using languages like C#, Java, or Python. With a step-by-step approach, you'll be guided from basic algorithms to object-oriented programming.

Goals :

Introduction to algorithms and their implementation.
Master the basics of C#, Java, and Python languages.
Understand the concepts of classes, objects, and error management.
Course methods and format:

Video lessons: Clear explanations and practical exercises.
Flexibility: Personalized support to meet your expectations.
For who ?
Students or professionals starting out in programming, or preparing for exams.
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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.
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A (60-minute) tour for children and teenagers who already use technology, ChatGPT, images, games, and for families who want that curiosity to have method, limits, and a visible result.

No prior assessment is necessary. The first class serves to get to know the student, adapt the pace (also if there are special educational needs) and choose the type of project.

What we do in weeks

Weeks 1–2. How an AI “learns”
With short projects, we observe data, patterns, and biases. The goal is not to memorize definitions, but for students to be able to explain, in their own words, why a tool is right or wrong.

Weeks 3–4. Create with discernment
Art, stories, or game ideas using generative tools. We work on prompts, what can be published, privacy, copyright, and when not to use AI (for example, to copy homework).

Week 5. Final Project
A mini-project of their own: a co-written story, a series of images, a simple classifier, a game idea... Something they can show at home and explain how they did it.

What does the family take with them?
• a 5-week overarching theme, not random, aimless classes
• Safe usage habits that are also useful at school
• Finally, a completed project and a brief note on how to proceed.

If the student has SEN (ADHD, dyslexia, organizational or rhythm difficulties), I break the work down into shorter steps, use visual aids, and measure progress in specific tasks, not speed.
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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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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.
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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

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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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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)
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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
Good-fit Instructor Guarantee
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