Teaching the Programming language(JAVA, Python, C, JavaScript)

From 20 € /h

### Course Description: Teaching the Programming Languages (JAVA, Python, C, JavaScript)

Welcome to the comprehensive course on Teaching the Programming Languages: JAVA, Python, C, and JavaScript. This course is designed for aspiring programmers and educators who aim to master the fundamentals and advanced concepts of four of the most popular programming languages in the industry.

#### Course Objectives:
- **Introduction to Programming Concepts:** Understand the core principles of programming, including variables, data types, control structures, functions, and algorithms.
- **Language-Specific Syntax and Features:** Gain proficiency in the syntax and unique features of JAVA, Python, C, and JavaScript.
- **Hands-On Coding Practice:** Apply your knowledge through numerous coding exercises, projects, and real-world scenarios.
- **Debugging and Problem-Solving:** Develop strong debugging and problem-solving skills to efficiently resolve coding issues.
- **Advanced Topics:** Explore advanced topics such as object-oriented programming, web development, data structures, and algorithms.
- **Teaching Methodologies:** Learn effective teaching strategies to impart programming knowledge to others, whether in a classroom setting or online.

#### Course Outline:
1. **Introduction to Programming:**
- Basics of programming and computational thinking
- Overview of the four languages: JAVA, Python, C, and JavaScript

2. **JAVA Programming:**
- Syntax and basic constructs
- Object-oriented programming concepts
- Exception handling and multithreading
- Building GUI applications

3. **Python Programming:**
- Syntax and basic constructs
- Data structures and libraries
- Functional programming and modules
- Web development with Flask/Django

4. **C Programming:**
- Syntax and basic constructs
- Memory management and pointers
- File handling and system programming
- Data structures and algorithm implementation

5. **JavaScript Programming:**
- Syntax and basic constructs
- DOM manipulation and event handling
- Asynchronous programming and AJAX
- Front-end frameworks (React, Angular, or Vue.js)

6. **Integrated Projects:**
- Cross-language projects to solidify understanding
- Real-world applications and problem-solving

7. **Teaching Strategies:**
- Curriculum development and lesson planning
- Interactive and engaging teaching methods
- Assessment and feedback techniques

#### Who Should Enroll:
- Aspiring programmers who want to learn multiple programming languages
- Educators and trainers looking to enhance their teaching skills
- Professionals seeking to expand their coding expertise for career advancement

#### Prerequisites:
- Basic understanding of computer operations
- No prior programming experience required, but familiarity with basic programming concepts is beneficial

#### Course Outcomes:
By the end of this course, you will be able to:
- Write, debug, and optimize code in JAVA, Python, C, and JavaScript
- Develop comprehensive projects using each language
- Effectively teach programming concepts to others
- Apply advanced programming techniques to solve complex problems

Join us in this journey to become proficient in four powerful programming languages and enhance your teaching abilities to inspire the next generation of coders.

Extra information

the laptop is necessary for assignment

Location

Online from Canada

About Me

Programming with several programming languages, such as C, JAVA, and Python.
Data scientist: extracting knowledge from structured, semi-structured, and unstructured data.
Teach programming languages and data science.
Five years of experience in teaching.

Education

Ph.D. in Artificial Intelligence Multi-modal from Sidi Mohamed Ben Abdellah University.
Master's degree in Big Data analytics and smart systems, from Sidi Mohamed Ben Abdellah University.
Bachelor's degree in Computer Science and Mathematics from Ibn Zohr University

Experience / Qualifications

Five years of experience in teaching.
Freelancer in several programming projects.

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

120 minutes

The class is taught in

English

Arabic

French

Skills

Java

C - c++

Python

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

AI and data science (the steps to handle a project)

26 € /h

Embark on a comprehensive journey through Artificial Intelligence and Data Science with our course, "AI and Data Science: The Steps to Handle a Project." This course is meticulously designed for individuals who aspire to become proficient in managing and executing AI and data science projects from inception to deployment.

#### Course Objectives:
- **Foundational Knowledge:** Understand the core principles of AI and data science, including key concepts, methodologies, and tools.
- **Project Lifecycle Management:** Learn the systematic approach to handling AI and data science projects through each project lifecycle phase.
- **Hands-On Experience:** Gain practical experience through real-world projects and case studies.
- **Advanced Techniques:** Explore advanced techniques and algorithms in AI and data science.
- **Ethical and Responsible AI:** Understand the ethical implications and best practices for responsible AI development and deployment.

#### Course Outline:
1. **Introduction to AI and Data Science:**
- Overview of AI and data science
- Key concepts and terminologies
- Applications and industry use cases

2. **Project Scoping and Planning:**
- Defining the problem statement
- Identifying objectives and success metrics
- Project planning and timeline management

3. **Data Collection and Preprocessing:**
- Data collection methods and sources
- Data cleaning, transformation, and integration
- Exploratory data analysis and visualization

4. **Model Development:**
- Selection of appropriate algorithms and models
- Training, validation, and testing of models
- Hyperparameter tuning and optimization

5. **Model Evaluation and Validation:**
- Evaluation metrics and performance analysis
- Cross-validation techniques
- Model interpretability and explainability

6. **Deployment and Monitoring:**
- Model deployment strategies and tools
- Monitoring and maintaining model performance
- Continuous integration and continuous deployment (CI/CD)

7. **Project Documentation and Presentation:**
- Creating comprehensive project documentation
- Presenting findings and insights to stakeholders
- Effective communication of technical results

8. **Ethics and Best Practices:**
- Ethical considerations in AI and data science
- Ensuring fairness, accountability, and transparency
- Best practices for sustainable and responsible AI

#### Course Outcomes:
By the end of this course, you will be able to:
- Manage and execute AI and data science projects from start to finish
- Collect, preprocess, and analyze data effectively
- Develop, evaluate, and deploy robust AI models
- Communicate insights and results clearly to stakeholders
- Apply ethical and responsible practices in AI development

Join us to master the end-to-end process of handling AI and data science projects and become a proficient practitioner capable of delivering impactful solutions.

Machine Learning with Python and PyTorch: Practical Hands-on Training

24 € /h

Welcome to "Machine Learning with Python and PyTorch: Practical Hands-on Training," a beginner-friendly course designed to introduce you to the exciting world of machine learning using two of the most popular tools in the industry: Python and PyTorch. This course focuses on practical, hands-on learning, ensuring you gain the skills needed to start building your own machine learning models.

#### Course Objectives:
- **Introduction to Machine Learning:** Understand the basic concepts and principles of machine learning.
- **Python Programming for Machine Learning:** Learn Python programming essentials tailored for machine learning applications.
- **PyTorch Fundamentals:** Get acquainted with PyTorch, a powerful and flexible deep learning framework.
- **Practical Experience:** Gain hands-on experience by working on real-world projects and exercises.
- **Model Building and Evaluation:** Learn to build, train, and evaluate various machine learning models.

#### Course Outline:
1. **Introduction to Machine Learning:**
- What is machine learning?
- Types of machine learning: supervised, unsupervised, and reinforcement learning
- Applications of machine learning in different industries

2. **Python Programming Essentials:**
- Introduction to Python programming
- Data structures and libraries (NumPy, Pandas)
- Basic data manipulation and visualization (Matplotlib, Seaborn)

3. **Getting Started with PyTorch:**
- Introduction to PyTorch and its ecosystem
- Setting up your environment and installation
- Understanding tensors and basic tensor operations

4. **Building Your First Machine Learning Model:**
- Data preprocessing and preparation
- Splitting data into training and testing sets
- Building a simple linear regression model with PyTorch

5. **Training and Evaluating Models:**
- Understanding the training process
- Loss functions and optimization algorithms
- Evaluating model performance using metrics

6. **Advanced Models and Techniques:**
- Introduction to neural networks
- Building and training a neural network with PyTorch
- Exploring convolutional neural networks (CNNs) for image classification

7. **Practical Projects and Applications:**
- Hands-on projects to reinforce learning
- Real-world applications and case studies
- Tips and best practices for successful machine learning projects

8. **Next Steps in Your Machine Learning Journey:**
- Exploring further learning resources
- Joining machine learning communities and forums
- Preparing for advanced topics and courses

#### Who Should Enroll:
- Beginners with no prior experience in machine learning
- Individuals interested in learning Python programming
- Aspiring data scientists and machine learning enthusiasts

#### Prerequisites:
- Basic computer literacy and familiarity with high school-level mathematics
- No prior programming or machine learning experience required

#### Course Outcomes:
By the end of this course, you will be able to:
- Understand the fundamental concepts of machine learning
- Write and execute Python code for machine learning tasks
- Use PyTorch to build, train, and evaluate machine learning models
- Apply your knowledge to real-world problems and projects
- Take the next steps in advancing your machine learning skills

Join us in "Machine Learning with Python and PyTorch: Practical Hands-on Training" to embark on your journey into the fascinating world of machine learning. Gain the skills and confidence needed to build and deploy your own models, and start making an impact with machine learning today.

Matías

4.88

(85)

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.

Adam

4.88

(85)

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.

Subject areas and languages taught:

Algorithms & Logic: Designing data structures and solving problems.

Programming Languages: Python, C/C++, C# and Java.

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.

Amin

4.88

(85)

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.

Salah

4.88

(85)

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.

Roger

4.88

(85)

Are you looking to deepen your knowledge of physics or master advanced techniques in Python programming? This course is designed to help you achieve a level of academic and technical excellence, whether you are a high school student, university student or professional looking to develop your skills.

With an interactive and effective teaching approach, you will benefit from personalized support to overcome obstacles, grasp complex concepts and improve your performance. Whether it is to succeed in difficult exams, high-level competitions or to create powerful applications in Python, this course will provide you with all the tools necessary to achieve your goals.

🎯 Why Choose This Course?
Advanced and Expertise Level: In-depth content and effective methodology to master complex topics in physics and programming.
Personalized Courses: Sessions adapted to your needs, your pace and your level.
Interactive Online Learning: Dynamic online courses with screen sharing and audio interaction for enjoyable and engaging learning.
Concrete Projects and Practical Applications: Development of practical projects to implement theoretical concepts.
Intensive Preparation for Exams and Competitions: Rigorous training with complex exercises and exam simulations to guarantee your success.
Flexibility and Comfort: Learn from home, according to your schedule, without having to travel.

🔬 Advanced Physics – From High School to University
This module offers a complete and in-depth program to prepare you for demanding secondary school exams, preparatory classes and scientific university courses:

1. Secondary Physics (High School and Preparatory Classes)
⚙️ Classical Mechanics: Kinematics, dynamics, Newton's laws, energy and work, oscillations.
🌊 Waves and Vibrations: Wave propagation, interference, diffraction, acoustics.
⚡ Electricity and Magnetism: Electric circuits, electrostatics, magnetostatics, electromagnetic induction.
🔦 Optics: Geometric optics (lenses, mirrors), wave optics (interference, diffraction).
🌡️ Thermodynamics: Laws of thermodynamics, thermodynamic cycles, entropy, changes of state.

2. University and Advanced Physics
🔄 Analytical Mechanics: Lagrangian, Hamiltonian, and generalized coordinates.
🌐 Advanced Electromagnetism: Maxwell's equations and the propagation of electromagnetic waves.
🧪 Quantum Physics: The postulates of quantum mechanics, the wave function, and the Schrödinger equation.
☢️ Nuclear and Particle Physics: The structure of the nucleus, radioactivity, and fundamental interactions.
🌌 Special Relativity: Lorentz transformations, time dilation, and length contraction.

3. Intensive Preparation for Exams and Competitions
📘 Scientific methodology: Learn to analyze statements, structure responses and write clearly and precisely.
📝 Application exercises and past papers: Intensive training to master the concepts and pass your exams.
🔎 Solve complex problems with detailed explanations and effective strategies.
⏰ Time management: Practical tips to improve your time management during exams.

🐍 Advanced Python Programming – Focused on Efficiency
This module will teach you how to program efficiently and effectively in Python, with an emphasis on best practices and advanced techniques:

1. Mastering Advanced Concepts in Python
🔠 Advanced Syntax and Best Practices: Deepening of Python concepts.
📦 Object-Oriented Programming (OOP): Abstract classes, interfaces, and design patterns in Python.
🔄 Functional Programming: Using lambda, map, filter, reduce, generators and iterators.
⚡ Asynchronous Programming: Implementing asyncio for fast and responsive applications.
🧪 Unit Testing and Code Quality: Use of pytest, code coverage, and CI/CD.

2. Performance Optimization
🚀 Algorithm Optimization: Analysis of algorithmic complexity and use of efficient data structures.
⚙️ Profiling and Debugging: Performance evaluation with cProfile and code improvement.
🔒 Security and Robustness: Writing secure code and handling exceptions appropriately.
3. Practical Projects and Advanced Applications
🌐 Web Applications: Building high-performance web applications using Flask and FastAPI.
📊 Data Science and Machine Learning: Exploitation of Pandas, NumPy, Scikit-learn and TensorFlow.
🕸️ Advanced Web Scraping: Complex data extraction using BeautifulSoup and Selenium.
🤖 Automation and Efficient Scripts: Automation of tasks and development of efficient scripts.

🧑‍🏫 Methodology and Pedagogical Approach:
Learning by doing: Each theoretical concept is directly implemented through practical exercises.
Interactive Online Teaching: Using audio and screen sharing for seamless communication and dynamic learning.
Personalized monitoring: Regular support to assess your progress and answer all your questions.
Concrete projects: Development of complete projects to apply your programming skills.
Motivation and Confidence: A positive and encouraging approach to build your confidence in your abilities.

🎓 For whom?
This course is intended for:

- High school and preparatory class students who aspire to academic excellence.
- University students in science and computer science wishing to deepen their knowledge.
- Candidates for scientific competitions who are preparing for physics and programming tests.
- Developers looking to improve their advanced Python skills.
- Researchers and engineers who use Python for complex scientific applications.

🔔 Register now! Don't miss the opportunity to master advanced physics while developing skills in optimized and efficient Python. Join our program "🚀 Advanced Courses - 🔬 Physics from High School to University & 🐍 Advanced Python Programming Focused on Efficiency!" and progress at your own pace with confidence and motivation!

Baia

4.88

(85)

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.

Ali

4.88

(85)

I teach Python, C and C++ one to one, online or in person around Birmingham.

Most of my students fall into one of three groups. Some are at GCSE or A-Level and need to get comfortable with a language before an exam or a coursework deadline. Some are at university, usually on an engineering or computing degree, and have hit something specific that isn't clicking: pointers, memory, recursion, object orientation, or a project that won't compile. And some are adults starting from nothing, often because work has started asking them to automate things.

Lessons are built around code you can run. I'll ask what you're working on and where you got stuck, then we write something small together, break it on purpose, and work out what the error message is actually telling you. Reading error messages properly is half of programming and almost nobody teaches it.

Areas I cover regularly:

Python from the basics through functions, data structures, file handling, object orientation and libraries like NumPy and Pandas
C and C++, including the parts that cause most of the trouble: pointers, memory management, structs, classes and compilation
GCSE and A-Level Computer Science across all exam boards, including pseudocode, trace tables and written paper technique
A-Level NEA projects and university coursework, plus debugging sessions and code review
Embedded C for Arduino, ESP32 and microcontroller projects, which is the work I do professionally

After each lesson I send written notes covering what we did, worked through step by step, so you have something to revise from later rather than trying to remember what was on screen.

First session is free and lasts 30 minutes. We use it to work out what you need and whether I'm the right person for it. If I'm not, I'll say so and point you somewhere better.

Message me with what you're studying and what's giving you trouble, and I'll tell you honestly how I'd approach it.

Ammar

4.88

(85)

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.

Pallavi

4.88

(85)

Learn Python with a structured, hands-on approach! Whether you are a absolute beginner looking to start coding, a student needing help with coursework, or a professional aiming to automate tasks, these lessons are tailored for you.What we will cover:
Core Fundamentals: Variables, loops, functions, and data structures.Object-Oriented Programming: Building reusable and clean code.Real-World Projects: Creating scripts, data analysis, or web scraping based on your goals.

Problem Solving: Learning how to debug and think like a programmer. Lessons are highly interactive. We will write code together from day one, and you will receive practical exercises after every session to build your confidence.

Aditya

4.88

(85)

Python class from basics to the advance from the students perspective with proper deep understanding of concepts.
Topics to be covered:
Basic Python and Programming fundamentals
Memory Management
OOPs
Data Structure and Algorithms
Libraries
Data analysis (using libraries Pandas, Numpy, etc.)
AI (ML, DL, RL, LLMs, RAG, Langchain etc.)

Maths using visualization of geometry, algebra, calculus, etc.

Abel

4.88

(85)

I'm Abel, a Computer Science specialist based in Canterbury, Kent. I hold a BSc in Artificial Intelligence from the University of Kent and an MSc in Artificial Intelligence from City St George's, University of London, and I'm now a PhD researcher at the University of Kent, working on AI and reinforcement learning. I've tutored GCSE, IGCSE and A-level Computer Science since 2021.

Who I help: Year 9 to Year 13 students on AQA, OCR, Edexcel and Cambridge courses, including Cambridge IGCSE. Some are aiming for a 9 and keep dropping marks on the long questions. Others are stuck at a 4 or 5 and have lost confidence with programming. Both get a plan.

How lessons work: we meet one-to-one on Google Meet with a shared whiteboard and a live Python editor. Theory is taught through exam questions rather than slides, so every topic links to the marks it earns. For programming we work the way the exam does: plan it, write it on paper, then type it in and test it. Students learn to trace code by hand, spot their own bugs and structure the long-answer questions examiners reward.

What parents get: a diagnostic opening lesson with a plan for the term, and a short written update after every lesson covering what we did, what went well and the homework set. One recent Year 10 student went from 50% to 81% between one school test and the next.

I teach online across the UK, with weekday evening and weekend slots, and daytime lessons by arrangement. I'm happy to work alongside what school is doing, including mock preparation and A-level NEA support.

Zeyad

4.88

(85)

Computer Programming is essential for nearly every child and adult. Everyday we interact with computers and applications, but we never understood how they operate or how they were made.

In this class you will learn how to create your own programs and websites, that can be used in the future for a source of income, or providing an operating application for the public.

Abdul

4.88

(85)

Hello and welcome!
I am AbdulBasir Momand, a Software Engineer, Full-Stack Developer, and passionate educator with a strong background in computer science, software development, and modern web technologies.
I am passionate about sharing knowledge and helping students develop practical skills in programming, web development, database management, and software engineering. My goal is to make technology easy to understand by explaining complex concepts in a simple, structured, and practical way.
I offer online classes for beginners, intermediate learners, university students, and anyone interested in building a career in the technology industry.
What I Teach
1. Programming Languages
* Python Programming
* C++ Programming
* Programming Fundamentals
* Object-Oriented Programming (OOP)
* Data Structures and Algorithms
2. Web Design and Development
* HTML5 and CSS3
* JavaScript
* Responsive Web Design
* Front-End Development
* Back-End Development
* Full-Stack Web Development
3. Software Engineering
* Software Engineering Fundamentals
* Software Development Life Cycle (SDLC)
* Object-Oriented Design
* Software Architecture Fundamentals
* Project Development and Problem Solving
4. Database Management
* Database Fundamentals
* SQL
* Database Design
* Relational Database Management Systems
* Database Queries and Management
5. Pashto Language
* Pashto for Beginners
* Pashto Speaking and Conversation
* Pashto Reading and Writing
* Pashto Grammar
* Practical Everyday Pashto
My Teaching Approach
My teaching philosophy is based on simplicity, practical learning, and student engagement.
* Beginner-friendly explanations.
* Step-by-step lessons.
* Practical examples and coding exercises.
* Real-world projects and assignments.
* Individual attention and interactive sessions.
* Support with programming problems and academic concepts.
Whether you are learning your first programming language, developing your first website, improving your software engineering skills, or learning Pashto, I am here to guide you.
My Mission
My mission is to make quality education accessible to everyone and help students gain the knowledge, confidence, and practical skills they need to succeed.
Let’s learn, build, practice, and grow together!
Welcome to my classes!

Fer

4.88

(85)

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.

Khalil

4.88

(85)

Learn Python by building something you’ll actually use

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

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

Where you can go next

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

Your instructor

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

Ready to start?

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