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Since June 2024
Instructor since June 2024
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Master Python: From Introduction to Advanced Projects
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From 21 C$ /h
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This introductory Python course is specially designed for beginners looking to gain a solid understanding of programming fundamentals. You'll start with the essential foundations of the Python language, including syntax, control structures, and functions.

Through hands-on examples and guided exercises, you'll learn how to solve simple problems using Python, manipulate data, create scripts, and automate common tasks. We will also cover the principles of object-oriented programming and the use of basic libraries such as NumPy and Matplotlib for data analysis and visualization.

This course is ideal for those who want to get started with programming with Python, whether for academic, professional applications or simply for the pleasure of learning a new language.
Extra information
This course does not require any specialized equipment. All you need is a computer with a stable internet connection and a prior installation of Python, which you can download for free from the official Python website (https://www.python.org/downloads/).

For the best experience, make sure you have an integrated development environment (IDE) such as PyCharm, VS Code, or Jupyter Notebook installed on your system. These tools will help you follow the lessons, practice the exercises, and develop your Python projects smoothly.
Location
location type icon
Online from France
About Me
An engineer passionate about IT and technology, I have solid experience in programming with languages ​​such as C, Java and Python. At the same time, I developed advanced skills in web development with HTML, CSS and JavaScript, as well as expertise in the use of specialized software.

In addition to my technical skills, I am multilingual, mastering Arabic, Tariffit and Darija as my mother tongue, as well as a good level in French, the language in which I followed my university studies. My teaching approach aims to combine a deep understanding of computing concepts with their practical application, creating an interactive and stimulating learning environment.

My academic background includes a DEUST in Mathematics-Computer Science-Physics, a License in Mathematics-Computer Science and an engineering diploma in Geoinformation, enriched by university projects such as the development of mobile applications and GIS solutions. As a future engineer, I am motivated to pass on my knowledge and inspire my students to excel in both computer science and languages, while cultivating their curiosity and ability to innovate.
Education
DEUST in Mathematics-Computer Science-Physics
Bachelor's degree in Mathematics-Computer Science
Student in geoinformation engineering

My academic background includes a DEUST in Mathematics-Computer Science-Physics, a License in Mathematics-Computer Science and an engineering diploma in Geoinformation,
Experience / Qualifications
My professional and academic career reflects my passion for computing and technology. As a future engineer specializing in Geoinformation, I have developed expertise in programming, particularly with C, Java and Python languages. My skills also extend to advanced web development with HTML, CSS and JavaScript, as well as the professional use of specialist software such as AutoCAD, ArcGIS.

In addition to my technical skills, I am multilingual, mastering Arabic, Tarifit and Darija as mother tongues, and have a good level of French, which has been my main language of study.
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
60 minutes
The class is taught in
French
Arabic
English
Reviews
Availability of a typical week
(GMT -05:00)
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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The sessions will also include simple recitations and explanations of the verses of the Quran adapted to their level of understanding. Our educational approach encourages a positive and engaging learning environment, aimed at developing children's spiritual and linguistic connection with the Arabic language and the sacred text of the Quran.

This course is ideal for beginner children or those who want to strengthen their basic knowledge of Arabic and enrich their understanding of the Quran in an accessible and inspiring way.
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As a math teacher, I offer tutoring and extra hours tailored to children, middle school, and high school students. My goal is to help each student strengthen their foundation, progress at their own pace, and regain confidence in math.

✔️ Interactive and personalized methodology
✔️ Clear explanations adapted to the student's level
✔️ Practical exercises and concrete applications
✔️ Preparation for assessments and exams

Whether it is to overcome difficulties, deepen knowledge or prepare for an exam, each session is adapted to the specific needs of the student.

📍 In-person or online courses according to your preference

Do not hesitate to contact me for more information or to book a class! 😊📚
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1- PYTHON FOUNDATIONS
• Variables, data types, operators, conditional structures, loops, functions, modules, files, exceptions, and object-oriented programming
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• 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
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• 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

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• TensorFlow, Keras, or PyTorch depending on the learner’s project and working environment

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• Reliability, hallucinations, bias, privacy, responsible use, and appropriate human validation

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• 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
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-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
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✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
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✓ Collaborate and share: work with other kids, get feedback, improve their work
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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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Learn to code with method and logic
Whether it's to succeed in the NSI (Digital Sciences and Technology) specialization in high school, design personal projects, or prepare for higher scientific studies, mastering code relies on solid algorithmic thinking. I help students understand the structure of programming languages and the logic of data.

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Data Management: Analysis and SQL queries / databases.

Basic Web Development: HTML & CSS for creating structured pages.

The goal is to take the student from simply writing code to true autonomy in development.
verified badge
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Who this is for:
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- Researchers who need to process and present data properly

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Are you looking for personalized academic support to succeed in mathematics, physics or computer science? Do you want to understand your courses in depth, fill in your gaps or simply boost your performance? You've come to the right place!

💡 Why Choose this Program?
This program offers much more than traditional courses. You will benefit from tailor-made support for:

🔍 Understand theoretical concepts in depth.
🧠 Develop thinking and problem-solving methods.
📈 Progress at your own pace with exercises adapted to your level.
🎯 Prepare effectively for your exams (Brevet, Bac, competitive exams) by covering typical topics and revising key concepts.
💻 Acquire computer skills useful for studies, work or your personal projects.
👨‍🏫 Personalized and Pedagogical Teaching
Interactive online courses: Thanks to audio and screen sharing, enjoy comfortable learning from home, with complete peace of mind.
Clear and effective teaching: The explanations are adapted to your level to facilitate understanding.
Regular and motivating monitoring: Each progress is closely monitored to encourage and guide you throughout your journey.
Positive and caring method: Learn without stress and gain confidence thanks to caring support.
📘 Mathematics – Understand, Apply, Succeed
Mathematics can sometimes seem complicated, but with the right explanations, it becomes logical and accessible.
This module covers:

Middle School Level: Arithmetic, fractions, basic geometry, statistics.
High school level: Algebra, functions, equations, analytical geometry, probabilities.
Preparation for exams: Brevet, Bac, entrance exams for grandes écoles.
Advanced Mathematics: Differential and integral calculus, matrices, sequences and series for university level.
Practical and Corrected Exercises: To apply theoretical concepts and train effectively.
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Physics helps us understand the world around us, from gravity to electromagnetic phenomena.
This module covers:

Middle and high school level: Mechanics, electricity, optics, thermodynamics.
University Level: Analytical mechanics, advanced electromagnetism, quantum physics, statistical thermodynamics.
Scientific Methodology: Knowing how to analyze a problem, apply physical laws and interpret the results.
Practical Applications: Interactive simulations and corrected exercises to visualize and apply theoretical concepts.
💻 Computer Science – Learn to Code and Innovate
Mastering IT means developing essential skills in a constantly evolving digital world.
This module adapts to your level:

Introduction to Computers: Understand how a computer works, master office software.
Programming Beginner: Learn to code in Python, JavaScript or C/C++ with clear explanations and practical exercises.
Advanced Programming: Complex algorithms, advanced data structures, object-oriented programming.
Project Development: Creation of web applications, automated scripts, simple video games.
Preparation for NSI Exams: Complete support to pass the Digital and Computer Science tests.
🎯 Interactive and Motivating Teaching
Dynamic Online Course: Learn from home with an interactive format using audio and screen sharing.
Method Adapted to Your Pace: Each course is designed according to your level and your objectives.
Practical Exercises and Concrete Projects: To apply theoretical concepts and learn while having fun.
Personalized Monitoring: Regular support to monitor your progress and adapt the program to your needs.
Encouragement and Motivation: A positive approach to building your confidence in your abilities.
🔔 For Who?
This program is aimed at:

Middle school and high school students wishing to strengthen their foundations or aim for excellence.
University students in science or computer science looking to deepen their knowledge.
Candidates for exams and competitions preparing for the Brevet, the Bac, or entrance exams to the grandes écoles.
Passionate self-taught people who want to learn to program or better understand the scientific world.
Adults in professional retraining wishing to acquire IT skills.
🚀 Ready to Succeed?
Join the "🎯 Tailor-made Success – 📘 Private Lessons in Maths, 🔬 Physics & 💻 Computer Science!" and benefit from personalized support to achieve your goals. Whether you want to improve your grades, pass your exams or develop programming skills, this program will give you knowledge, confidence and motivation.

Register today and take the first step towards success!
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I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.
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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.
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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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Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty.

1: Demystifying AI (What exactly is it?)
AI is not a movie robot: Difference between fiction and reality.

How it works (simply): The image of the "giant library": AI has read billions of books and uses them to predict the continuation of a sentence or create an image.

Where is it already present? Spell checkers, Netflix/YouTube suggestions, GPS, and voice assistants (Siri/Alexa).

2: Using AI to make life easier
Conversing with AI (ChatGPT, Claude, Gemini):

Ask him to write an administrative email or a complex letter.

Summarize a long newspaper article or document.

Plan a travel itinerary or find recipe ideas with what's left in the fridge.

AI for creativity and memory:

Generate images to illustrate a birthday card (Midjourney, DALL-E).

Using AI to restore or colorize old family photos.

3: Learning to "talk" to AI (The Art of the Prompt)
The context method: Why "Give me a cake recipe" is less effective than "I am allergic to gluten and I am hosting 4 people, give me a simple chocolate cake recipe".

The expert's role: Learning to tell AI "Act like a travel guide" or "Act like an expert gardener".

4: Precautions and Critical Thinking (The Survival Guide)
"Hallucinations": Understand that AI can make false claims with complete certainty (never take medical or legal advice from AI without verification).

Privacy protection:

Never give sensitive data (social security number, passwords, bank details) to an AI.

Knowing that everything we write to the AI is potentially used to train it.

Spotting "Deepfakes":

How to recognize a doctored image or video (details on the hands, strange reflections, slightly metallic voice).

Verify the information: the golden rule of cross-referencing sources.

5: Ethics and Impacts (To go further)
Copyright: Who owns an image created by AI?

The environmental impact: The water and energy consumption of AI servers.

The future: Will AI replace us or assist us?
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I teach coding to beginners and intermediate students.
Lessons focus on logic, basic programming, and practical exercises.
Classes are adapted to the student’s pace.
Students can choose between website or mobile app development.Hands on dev
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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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Primary School Teacher. I offer personalized guidance in developing lesson plans and learning activities adapted to current educational regulations. During our sessions, you will learn to structure and write a complete lesson plan, including specific competencies, assessment criteria, core knowledge, methodology, addressing diversity, evaluation, and learning situations. My goal is to help you understand each section so you can independently develop a coherent, rigorous, and high-quality lesson plan.

You will learn to design practical, creative proposals, developing the necessary skills to apply them in the classroom or in competitive examination processes.
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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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📊Microsoft Office: To establish your office skills, manage data via Excel, write professional reports with Word, and prepare impressive presentations with PowerPoint.

📐 AutoCAD: To learn engineering drawing and design two-dimensional and three-dimensional plans with high accuracy and speed.

🛣️ Civil 3D: To learn road design, network design, surveying, and quantity surveying in a scientific and practical way
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Java is one of the most widely used languages in the world, both in business and in higher education. But learning Java is not just about writing code that "works": it's about writing code that is readable, reliable, and easy to maintain.

As a master's student in computer science, specializing in software quality, I offer a practical course that teaches you the language while giving you the good habits of professional developers from the start.
Good-fit Instructor Guarantee
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