Introduction to Programming – Python for Beginners

From 22 C$ /h

This course introduces programming concepts from the very beginning using Python (programming language).

Students will learn coding and programming fundamentals starting from basic concepts and progressing step-by-step until they understand functions and structured programming.

The course is designed for complete beginners and focuses on building strong programming foundations through explanation and practical exercises.

Topics covered include:

• Basic programming concepts and problem-solving logic
• Variables and data types
• Input and output operations
• Conditional statements (if, else)
• Loops and iteration structures
• Lists and basic data structures
• String manipulation
• Functions and modular programming
• Writing simple programs from scratch
• Introduction to coding logic and algorithmic thinking

The teaching method combines theoretical explanation with hands-on coding practice to help students gain confidence in programming.

Extra information

💻 Students need a laptop for coding practice.
✨ This course is perfect for students who want to start learning programming from zero.

Location

Online from Lebanon

About Me

With experience delivering more than 2500 coding and technology online training sessions across the UK, USA, Egypt, and Gulf countries, I have worked with students from different backgrounds and skill levels, helping them improve their technical knowledge and practical skills.

I am a university instructor specializing in computer science and information technology education. I have experience teaching and explaining complex technical concepts in a clear, structured, and practical manner.

I offer tutoring and training in programming languages including C++, Java, Python, and C#, as well as web development. I also teach computer networking, data communication, cybersecurity fundamentals, artificial intelligence (machine learning), robotics and introductory IoT concepts.

My teaching approach focuses on understanding core principles, solving practical problems, and applying knowledge through examples and exercises. I adapt my lessons according to the student’s level, whether beginner or advanced.

I am committed to helping students build strong technical foundations, improve their problem-solving skills, and gain confidence in working with technology.

All sessions are delivered in a supportive learning environment where questions and discussion are encouraged.

Education

• Bachelor’s Degree in Computer Science – GPA: 3.81
• Master’s Degree in Computer Science – GPA: 3.90
• Certified in Machine Learning Fundamentals and Engineering from IBM.
• Certified in Computer Fundamentals from ICDL program.

Experience / Qualifications

• University instructor with extensive experience in teaching computer science and information technology subjects.
• Delivered more than 2500 coding and technology training sessions to students across the UK, USA, and Gulf countries.
• Experienced in teaching programming languages including C++, Java, Python, and C#.
• Knowledgeable in computer networking, data communication, cybersecurity fundamentals, artificial intelligence basics, IoT, and robotics concepts.
• Skilled in explaining complex technical topics in a simple, structured, and practical manner.
• Focused on helping students develop problem-solving skills and strong technical foundations.

Age

Preschool children (4-6 years old)

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

English

Skills

Computer programming

Computer science

Python

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Advanced Programming with Python – OOP, Data & Algorithms

22 C$ /h

This advanced course builds on programming fundamentals using Python (programming language) and is designed for students who want to deepen their programming knowledge.

The course continues from functions and introduces advanced programming concepts including object-oriented programming principles such as polymorphism, inheritance, abstraction, and encapsulation.

Students will also learn data handling techniques, working with Python libraries, and developing structured programs using complex loops and data collections.

The course covers practical implementation of nested loops, nested lists, tuples, and dictionaries, as well as an introduction to data structures and algorithmic thinking.

Additional topics include graphical user interface development using libraries such as Tkinter, along with introductory concepts in data science and machine learning using Python.

Teaching combines theoretical explanation with real coding exercises to help students develop strong practical programming skills.

• Review of programming fundamentals and functions
• Object-Oriented Programming (OOP) concepts
• Polymorphism, inheritance, abstraction, and encapsulation
• Data structures basics
• Nested loops and complex data handling
• Lists, tuples, and dictionaries
• Introduction to algorithms
• Working with Python libraries
• GUI development using Tkinter
• Introduction to data science and machine learning concepts

Computer Basics & Productivity Skills – Fundamentals, OS, and Office Applications

19 C$ /h

This course is designed for complete beginners who want to build strong basic computer skills and understand essential computing concepts.

Students will learn computer fundamentals including hardware components, input, processing, and output concepts, as well as basic operating system operations such as file management and system handling.

The course also introduces practical productivity skills using Microsoft Word, Microsoft Excel, Microsoft PowerPoint, Microsoft Outlook, and Microsoft OneDrive.

The teaching approach combines explanation and practical exercises to help students confidently use computers for academic and everyday tasks.

This course is ideal for beginners who want to start learning computer science concepts and improve their computer productivity skills.

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Adam

4.85

(13)

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

Enrique

4.85

(13)

Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.

Amin

4.85

(13)

Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Harry

4.85

(13)

Hello,

I am 26 years experienced Online Tutor and Assignment Helper for Computer Science. I teach PHP, MySQL, Python, Machine Learning, Programming in C, C++, Java, ASP, C#.NET, Visual Basic, Oracle, HTML, VBScript, JavaScript, Data Structures, JQuery, Bootstrap , MS Office. I have teaching experience of teaching IT Professionals , students from different grades, graduate and post graduate classes for more than 22 years.

Presently I am teaching students online, providing homework assignment help, provide help in online tests for the students from USA ,UK, Canada, New Zealand, Germany, Australia, Malaysia, Austria, Malta, Saudi Arab etc. Also, I am in Software Development and Web Designing. I have helped more than 1200 students from different countries in last 26 years.

Regarding my teaching methodology, I always start teaching the concepts right from the scratch so that the students can learn concepts easily. I would like to describe you how do I teach through Internet . There is 100 % interaction between me and my students using Internet.

For starting the lessons with me all that you need is PC with Internet Connection and Headphone and Mic. Rest I will guide you about everything when you start learning with me. My lessons are also customized, planned and prepared according to the needs of individual student. I can also provide old student references if the student needs that.

If you join the course with me, I assure you that it will be value for your time and money.

Thanks
Harry

Salah

4.85

(13)

Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Hassane

4.85

(13)

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.

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.

Yomna

4.85

(13)

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.

Amr

4.85

(13)

In today's rapidly evolving technological landscape, **Python programming** has emerged as one of the most **critical skill sets** for professionals across industries. With applications spanning web development, data science, artificial intelligence, automation, and more, Python continues to dominate as the **language of choice** for developers and organizations worldwide. This proposal outlines a comprehensive Python course designed and delivered by **Amr**, a developer and instructor with over **20 years of experience** in the field. The course combines fundamental programming concepts with practical, real-world applications, ensuring students gain not just theoretical knowledge but **marketable skills** that align with current industry demands. By leveraging cutting-edge teaching methodologies and extensive professional experience, this course offers an unparalleled learning opportunity for aspiring programmers and experienced developers alike.

## 1 Introduction to Python Programming

Python has established itself as a **powerhouse programming language** across various domains, from web development and data analysis to artificial intelligence and automation. As of 2025, the demand for Python skills continues to soar, with industry giants like Cisco, IBM, and Google leveraging its capabilities for their projects . Python's dominance in the technology sector is undeniable – it remains the **most requested programming language** in job postings across multiple industries, including finance, healthcare, technology, and entertainment.

The language's popularity stems from several key factors: its **user-friendly syntax** that resembles natural English, making it exceptionally accessible for beginners; its **versatile nature** that supports multiple programming paradigms; and its **extensive ecosystem** of libraries and frameworks that simplify complex programming tasks. Python's cross-platform compatibility ensures code runs seamlessly on Windows, macOS, and Linux environments, while its open-source nature has fostered a massive community of contributors who continuously expand its capabilities . These attributes make Python not just a programming language but a **comprehensive toolset** for solving diverse computational problems.

For professionals looking to future-proof their careers, Python offers **exceptional value**. According to industry data, Python developers in the United States earn an average of **$116,028 per year**, reflecting the high market demand for these skills . Beyond financial rewards, Python proficiency opens doors to cutting-edge fields like machine learning, natural language processing, and data analytics – domains that are shaping the future of technology across industries.

## 2 Course Overview & Learning Objectives

### 2.1 Course Philosophy
This Python programming course is designed with a **practice-oriented approach** that emphasizes hands-on learning and real-world application. Unlike traditional programming courses that focus heavily on theory, this program balances conceptual understanding with **practical implementation**, ensuring students develop the skills needed to solve actual business problems. The curriculum is structured to build proficiency gradually, starting with fundamental concepts and progressing to advanced applications, with each module incorporating **project-based learning** components.

### 2.2 Key Learning Objectives
Upon successful completion of this course, students will be able to:

- **Demonstrate proficiency** in core Python programming concepts including data structures, control flow, functions, and file handling
- **Develop functional applications** using Python for various domains including web development, data analysis, and automation
- **Implement object-oriented programming** principles to create modular, maintainable code
- **Utilize popular Python libraries** such as Pandas, NumPy, and BeautifulSoup for specialized tasks
- **Integrate with databases** and web APIs to create full-stack applications
- **Apply debugging and testing** techniques to ensure code quality and reliability
- **Build portfolio-worthy projects** that demonstrate marketable skills to potential employers

## 3 Instructor Qualifications & Experience

### 3.1 Professional Background
**Amr** brings an exceptional **twenty-year track record** of development and instruction experience to this Python course. His extensive background encompasses both corporate training and software development, providing a unique blend of pedagogical expertise and practical knowledge. With credentials including a **Bachelor of Computer Science and Management Technology** from Modern Academy and a **Computer Science Diploma** from Arab Academy for Science and Technology, Amr possesses the academic foundation to complement his extensive professional experience.

His career demonstrates **progressive responsibility** and expertise across multiple programming languages and frameworks. Beginning as a technical instructor at renowned institutions including NewHorizons, Knowlogy, and Informatica, he quickly established himself as a developer at Microtech and ITS, where he worked on enterprise-level systems including **ERP and banking applications**. This combination of education and hands-on development experience creates an ideal foundation for teaching programming concepts with both theoretical rigor and practical relevance.

### 3.2 Industry Client Portfolio
Amr's exceptional teaching credentials are further enhanced by his impressive roster of **corporate clients**, which includes some of the world's most recognized brands:

- **Technology Leaders**: Microsoft, IBM, Siemens, Vodafone, and Telecom Egypt
- **Financial Institutions**: National Bank of Egypt, NSGB, CIB, and Central Bank of Egypt
- **Global Consumer Brands**: Pepsi, Coca-Cola, Nestlé, Cadbury, and Americana
- **Industrial Conglomerates**: Chrysler, Valeo, 3M, ABB, and BP (British Petroleum)
- **Government Entities**: Libya Government IT Department, Sudan Army Officers, Egyptian Airports Company

This diverse client experience has provided Amr with **unparalleled insight** into how Python is applied across different industries and organizational contexts. His exposure to various business domains allows him to teach Python not as an abstract academic exercise but as a **practical tool** for solving real business problems.

### 3.3 Teaching Methodology
Amr employs a **learner-centered approach** that emphasizes interactive engagement and practical application. His teaching philosophy is based on the principle that programming is best learned through doing, rather than passive listening. Each concept is introduced through **clear explanations** followed immediately by hands-on exercises that reinforce learning. He adapts his pace and approach based on student comprehension, ensuring no one is left behind while maintaining challenging content for advanced learners.

*Table: Instructor's Recent Training Engagements (2023-2025)*

| **Year** | **Corporate Clients** | **Training Centers** | **Technologies Covered** |
|----------|-----------------------|----------------------|--------------------------|
| **2023** | International Finance Corporation, Raya Integration | Raya Academy, IT-Egypt | VBA, Office Automation, Web Technologies, Software Fundamentals with C#, SQL Server Database Design and Querying, Introduction to .NET Core Framework, Building ASP.NET Core Web API, Front-End Development Basics (HTML, CSS, JavaScript, TypeScript), Advanced Front-End Development with Angular, Integration and Deployment |
| **2024** | 3M, Pepsi | NewHorizons, Radio & Television Institute, Informatics (Lebanon), Total-Tech (KSA), Global Business Star (USA) | SQL Query (20761), SQL Development (20762), SQL Admin (20764,20765), Tabular, MQL5, ASP.NET Core MVC Web Applications (20486), Programming in C# (20483), Programming in HTML5 with JavaScript and CSS3 (20480), LINQ, EF (Entity Framework) |
| **2025** | Siemens, Vodafone | YAT, Future University | Full Stack Development, Data Analysis |

## 4 Detailed Course Curriculum

### 4.1 Module Breakdown
The Python course is structured into **eight comprehensive modules** that systematically build programming proficiency from foundation to advanced application:

1. **Python Fundamentals** (10 hours): Syntax, variables, data types, operators, and basic input/output operations. Students will write their first programs and understand how Python interprets and executes code.

2. **Control Structures & Functions** (15 hours): Conditional statements (if/elif/else), loops (for/while), function definition, parameters, return values, and scope. Emphasis on writing clean, reusable code.

3. **Data Structures** (20 hours): Lists, tuples, dictionaries, sets, and their appropriate applications. Includes comprehensive exercises on data manipulation and storage.

4. **Object-Oriented Programming** (20 hours): Classes, objects, inheritance, polymorphism, and encapsulation. Students will learn to structure code using OOP principles for better maintainability.

5. **File Handling & Modules** (10 hours): Reading/writing files, exception handling, importing modules, and creating custom modules. Practical applications for data persistence.

6. **Web Development with Python** (25 hours): Introduction to Flask/Django frameworks, REST APIs, and basic front-end integration. Students will build a functional web application.

7. **Data Analysis & Visualization** (25 hours): Using Pandas for data manipulation, NumPy for numerical computing, and Matplotlib/Seaborn for visualization. Real-world datasets will be used for analysis.

8. **Introduction to Automation & Scripting** (15 hours): Applying Python to automate repetitive tasks, web scraping with BeautifulSoup, and working with APIs.

### 4.2 Practical Projects
The curriculum includes **five portfolio projects** that allow students to apply their learning:

1. **Data Analysis Project**: Analyzing real business data to extract insights and create visualizations
2. **Web Application Project**: Building a fully functional web application with database integration
3. **Automation Script**: Creating a practical tool to automate a repetitive computer task
4. **API Integration Project**: Connecting to external services and processing returned data
5. **Final Capstone Project**: A comprehensive application that demonstrates mastery of course concepts

### 4.3 Python in Marketing Analytics
A special section of the course will focus on **Python applications in digital marketing**, covering how Python can be used for marketing automation, data analysis, and operations . Students will learn:

- **Working with APIs** to connect different software tools and automate marketing workflows
- **Web scraping** to gather data from web pages for content analysis and competitive intelligence
- **Text analysis** for sentiment analysis, content optimization, and customer feedback processing
- **Data analysis** for marketing analytics using Pandas and visualization libraries
- **Technical SEO** applications using Python libraries like advertools and EcommerceTools

This specialized content demonstrates Python's versatility beyond traditional programming roles, showing its value in business functions like marketing where data skills are increasingly crucial.

## 5 Training Methodology & Delivery

### 5.1 Interactive Learning Approach
This Python course employs a **multimodal teaching methodology** that accommodates diverse learning styles while ensuring practical skill development. Each session follows a structured pattern:

1. **Concept Introduction**: Clear explanation of programming concepts with real-world analogies
2. **Live Coding Demonstration**: Step-by-step coding examples that students can follow along
3. **Guided Practice**: Structured exercises with instructor support and immediate feedback
4. **Independent Challenge**: Problem-solving activities that require applying concepts creatively
5. **Code Review**: Collaborative analysis of solutions to identify best practices and improvements

This approach ensures that students not only understand theoretical concepts but develop the **problem-solving mindset** essential for effective programming. The emphasis is always on writing clean, efficient, and maintainable code following industry standards.

### 5.2 Hands-On Labs & Exercises
A distinctive feature of this course is the extensive **hands-on programming practice** integrated throughout the curriculum. Students will spend approximately **60% of course time** actively writing code rather than passively listening to lectures. Practical components include:

- **Coding exercises** for each new concept introduced
- **Mini-projects** that combine multiple concepts into functional applications
- **Debugging challenges** that develop problem-solving skills
- **Code optimization** activities focusing on efficiency and performance
- **Pair programming** sessions to foster collaboration and knowledge sharing

ِSend me if you have any questions,
Regars,
Amr

Ioannis

4.85

(13)

PhD Candidate in Informatics – Private Lessons & Pancyprian Exams

I am a PhD Candidate in Informatics and I offer private lessons in Informatics to High School students (Pancyprian Exams) as well as to University students, with an emphasis on correct understanding and methodical thinking.

Pancyprian Exams – Informatics

Systematic preparation with an emphasis on:
• understanding of the material
• correct algorithmic thinking
• methodology for solving problems
• analysis of old Pancyprian exam questions

We cover, for example: pseudocode, tables, repetitions, control structures and common exam errors.

Students & General Computing

Support in:
• Programming (C / C++ / Python)
• Operating Systems
• Computer Architecture
• Code Understanding & Debugging

In-person or online courses, with emphasis on understanding and proper study organization.

English text below

PhD Candidate in Computer Science – Private Tutoring & Pancyprian Exams

I am a PhD candidate in Computer Science offering private tutoring for high school students (Pancyprian Exams – Computer Science) and university students.

Pancyprian Exams – Computer Science

Structured exam preparation focusing on:
• understanding the syllabus
• correct algorithmic thinking
• exam-oriented problem-solving
• analysis of past Pancyprian exams

Topics include pseudocode, arrays, loops, control structures, and common exam mistakes.

University & General Computer Science

Support in:
Programming (C/C++/Python)
• Operating Systems
• Computer Architecture
• Code understanding and debugging

Lessons are available in person or online, with emphasis on understanding concepts rather than memorization.

Farouk

4.85

(13)

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

Ammar

4.85

(13)

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.

Yassine

4.85

(13)

Professeur agrégé de informatique, j’aide élèves et étudiants à réussir examens et concours. J’interviens aux classes préparatoires (MPSI, MP, PSI, ECS...) et jusqu’à l’université (Licence & Master en sciences ou économie). Ma méthode : comprendre le cours, pratiquer avec rigueur, structurer le raisonnement et ha des exercices et problèmes bien choisis. Chaque séance inclut exercices ciblés, conseils méthodologiques, et suivi personnalisé. Vous recevez un enregistrement vidéo plus un PDF annoté après chaque cours. Cours en ligne via Google Meet, 5 jours sur 7, avec flexibilité horaire. Je reste joignable entre les séances pour répondre aux questions. Contactez-moi pour un premier échange.