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Since July 2026
Instructor since July 2026
Python for beginer to start any new project (Usefull for my class Become OT/IT,SCADA DCS engineer)
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From 23 £ /h
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This hands-on training pathway is designed to help students kickstart any project, specifically tailored for OT labs and industrial applications. Starting from absolute scratch, students will build a strong foundation in Python programming through practical, industry-relevant concepts.

Curriculum Outline: |
01 - Python Environment Setup & Basics |
02 - Python Variables, Numbers, Bytes & Hex |
03 - Control Flow Logic Functions |
04 - Data Structures (Lists, Tuples, Dictionaries & Sets) |
05 - String Formatting, Comprehensions & Exception Handling |
06 - File IO, Pathlib & Context Managers |
07 - Object-Oriented Programming (Classes & OOP) |
08 - Standard Library, Modules & Networking Basics |

Assessment & Evaluation:
Students will take a mini-test after the completion of each module. Additionally, an Audit & Performance Evaluation report will be sent following the tests.
Duration:
5 days to 15 days (depending on the pace of the cohort)
Extra information
- Equipment: A laptop is required for hands-on exercises and practical work.
- Session Recording: Classes are recorded to create post-session summaries and key takeaways for easy revision.
- Feedback & Progress: Student reviews are gathered after each session to fine-tune the learning and objectives.
Location
location type icon
Online from Morocco
About Me
Results-driven Senior Solution Architect with over 10+ years of expertise in Operational Technology (OT), Industrial Control Systems (ICS), SCADA, and IIoT ecosystems. Proven track record of designing, modernizing, and governing complex OT architecture for industrial environments while bridging the gap between IT enterprise standards and plant-floor operational requirements. Recognized for developing reference architectures, design patterns, and strategic technology roadmaps using TOGAF and ISA/IEC frameworks. Adept at vendor integrations like (Areva, Schneider Electric, Siemens , Alstom , Abb ) and leading cross-functional teams toward successful digital transformations.
Education
Bachelor of Engineering / Computer Science : Oran University 1 Ahmed Ben Bela 2002
SNMP Protocol developper
Design a monitoring system for the compus
+ Monitoring of Servers
+ Monitoring of Sun Microsystem Workstation
+ Monitoring of Switch and router 3com and Cisco
+ Integration on IDS
Experience / Qualifications
- Network Administrator & Application Developer (1 year)
- Senior SCADA System Engineer (5 years)
- Senior DCS System Engineer (2 years)
- Senior Technical Sales & Proposals Engineer SCADA & DCS (4 years)
- Business Analyst Specialist - GIS (1 year)
- OT/IT Consultant
Age
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Duration
60 minutes
The class is taught in
English
French
Arabic
Availability of a typical week
(GMT -04:00)
New York
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
Master Industrial Control Systems (SCADA, DCS, IIoT) and automation through tailored, hands-on coaching based on real-world industrial projects! With over 10 years of international engineering, solution architecture, and technical business development experience working with major industry vendors

I offer practical courses designed for engineering students, university undergraduates, and professionals looking to upskill.

The pathway will be in 7 days to cover all basics in OT environnement :
Day 1 - Virtual Environment Preparation for OT projects
- Install Hypervisor on your workstation (A virtual machine).
- Create a Linux VM (Fedora Server).
- Configure 2 networks on the VM: one in NAT (internet access) and one in Host-Only Network (to isolate lab traffic).
- Install basic tools for OT
Day 2: Modbus PLC Simulation (Add 2 Server and test script client to connect)
- Implement Modbus PLC simulators and architecture overview
- Create PLC simulator scripts in src/plc-simulators/
- Add validation test script for Modbus connectivity
- Update Day 2 guide with detailed implementation steps and compatibility notes
Day 3: NGINX Load Balancer Configuration (Round Robin)
- Understand NGINX Stream Module
- Configure NGINX
- Verify and Load the Module
- Troubleshooting NGINX (Activate load balancing in layer 4 protocol, Set permission)
- Step-by-Step Load Balancer Validation
- Test Load Balancing (Round-Robin)
- Test Failover (Resilience)
Day 4 - Creation of the traffic generator (SCADA Client)
- TBD
Day 5 - Traffic capture and measurement with TShark
TBD
Day 6 - Advanced analysis and overload simulation
TBD
Day 7 - Grafana
-TBD
What we can cover together based on your goals:
Read more
- Modbus Protocol Introduction
- Modbus Frame Structure & Byte Analysis
- Modbus Exception Handling & Error Codes

Each module in this series is structured with core learning content followed by two mandatory practical components:
Challenge: A hands-on troubleshooting or design scenario to test your practical skills.
Audit: A checklist and verification quiz to ensure full mastery before moving to the next section.
Read more
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What they'll do:
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✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
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We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
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Electronics: Learn to create circuits, understand components, and carry out innovative electronics projects.

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Robotics: Explore the basics of robotics, create autonomous robots, and discover how to bring your ideas to life.

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• Aeronautical Engineering
• Mechanical Engineering
• Electrical Engineering
• other types of Engineering

Or need help with areas like control systems or data analysis, I’m here to guide you through any engineering challenge. My lessons are customized to fit your learning style and academic goals, ensuring you leave each session feeling confident and prepared.

Contact me now for availability, and let's schedule your first session soon. I look forward to working with you!
__________________________________________________________________________________

I'm actively supporting students from top universities worldwide, including:

UK:
• Imperial College London (+ Business School) (ICL)
• University College London (UCL)
• King’s College London (KCL)

The Netherlands:
• Delft University of Technology (TUDelft)
• University of Amsterdam (UvA)
• University of Groningen (RUG)

Switzerland:
• ETH Zurich - Swiss Federal Institute of Technology

Australia:
• Queensland University of Technology (QUT)
• University of Queensland (UQ)
• Griffith University
__________________________________________________________________________________

My name is Anh, and I was born and raised in the U.K. With over 10 years of international experience tutoring Maths, Sciences, and Engineering from Middle School to University Level, I’ve supported over 80 students worldwide in unlocking their full potential.

I have a fun, ambitious, and outgoing personality, and I’m passionate about music, cooking, and trying new things. In my tutoring and mentoring, I am patient, adaptable, and committed to meeting the unique needs of each student.

I work as an Engineering Specialist/Consultant, holding:
• Master’s degree in Aeronautical Engineering from Imperial College London,
• AAA* A-Level in Further Maths and Physics,

Having been mentored and tutored myself, I understand the challenges students face. Through my own experiences of overcoming obstacles and achieving success, I’m passionate about helping others do the same. Let’s work together to ensure you reach your full potential, both academically and personally!
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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.

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.
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..................................... (satisfied or refunded)........ .......
Electrical engineering expert
PhD student in electrical engineering and renewable energies
engineer in electrical engineering and industrial computing
I offer home schooling courses to deal with the difficulties encountered by students during their schooling,
These courses allow the student to get back to level and regain confidence in all scientific subjects, as well as effectively preparing him for the Baccalaureate, Preparatory Classes or various exams.
===Automatic (Servo-control and automatism regulation (discrete, continuous)========
===Electrical engineering (electrical machines) and power electronics (inverter rectifier)=======
===Continuous and sampled signal processing=================
===VHDL programming, microcontroller and microprocessor (intel, ARM)============
===High frequency electronics (transistor, diode, AOP, noise)============
===Propagation of electromagnetic waves and antennas========
===Analog and digital electronics (filters, flip-flops, sysml,Grafcet,amplifier)=====
=== Realization of electrical projects
===MATLAB ARDUINO Proteus ISIS
=== Renewable energies

COURSE OBJECTIVES AND PEDAGOGICAL APPROACH

Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

Respond to individual issues and questions

Exercise training in order to achieve real mastery of the content.

Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

This pedagogical approach is effective since it has often led me to interesting results with my students.
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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.
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* This digital training aims to introduce you to the Scratch tool and through the game world, and gradually, to discover programming concepts such as loops, conditions or variables. It is aimed at anyone who is new to Scratch and who wants to create games and animations.

* Learning programming will allow students to develop their skills and will certainly allow them to meet the expectations of the future working world and emerging careers.

* In addition, learning programming allows the development of algebraic, algorithmic and computational thinking. Programming also helps to improve and develop students' sequencing ability, as well as their communication skills. Thus, there are several advantages to teaching programming, but the important thing is to remember that this learning teaches students that digital is not only for entertainment, but that it is possible to become creators. active and creative content.
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Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

Do you want to create your own software?
Work with data or images?
Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!
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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.
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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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As a teaching assistant in the College of Engineering (specializing in Mechatronics Systems Engineering), I provide specialized academic support to engineering students to help them understand complex material, pass exams with distinction, and complete academic projects professionally.
I offer explanations and assistance in the following courses:
• Fluid Mechanics & Hydraulic/Pneumatic Control.
• Rigid Body Dynamics.
• Sensors and Data Acquisition Systems.
• Digital control machines and computer-aided design/manufacturing (CAD/CAM & CNC).
• Electric Machines & Drives.
• Renewable Energies.
In addition to theoretical explanations and worksheet solutions, I offer practical guidance in using engineering software (such as MATLAB and ANSYS) and assistance with graduation projects and course projects (CAD modeling and CFD simulations). My goal is to simplify engineering concepts and connect them to practical applications.
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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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I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects
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Overview

Transitioning from learning data science theory to solving actual business problems is the hardest step for any aspiring data professional. [Insert Chosen Course Title] is an intensive, mentor-led program designed to simulate a real-world data team environment. Instead of working through synthetic, pre-cleaned textbook datasets, you will take on messy, complex industry scenarios and turn them into end-to-end data products.

What You’ll Experience

End-to-End Execution: Walk through the full data lifecycle—from problem scoping and data extraction to exploratory analysis, modeling, and executive stakeholder presentation.

Industry-Standard Workflows: Work with messy real-world datasets, practice Git-based version control, write production-ready code, and structure reports that business leaders actually care about.

1-on-1 & Group Mentorship: Receive continuous code reviews, architectural feedback, and project guidance mirroring the experience of working under a Senior Data Scientist or Analytics Lead.

Portfolio-Ready Deliverables: Graduate with 2–3 complete, polished projects that demonstrate actual business value to hiring managers—not just another churn prediction copy-pasted from Kaggle.

Who This Is For
Aspiring Data Analysts, Data Scientists, and recent graduates who know Python, but want the practical experience, confidence, and portfolio needed to land high-impact roles in the industry.
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Learn how to build modern websites and mobile applications from scratch and develop the practical skills needed for real-world projects.

In this Frontend & Mobile Development course, I’ll guide you step by step through the technologies and tools commonly used by developers, including HTML, CSS, JavaScript, Angular, Git, GitHub, VS Code, and mobile application development.

You’ll learn how to create responsive and interactive websites, build structured applications with Angular, manage your code using Git and GitHub, and use VS Code efficiently for development. We’ll also explore how frontend technologies can be used to create mobile applications.

The course is suitable for beginners and intermediate learners. Lessons are practical and project-based, so you’ll learn by actually building websites and applications rather than only studying theory.

My goal is to help you understand how and why the code works, improve your problem-solving skills, learn professional development practices, and gain the confidence to create your own projects independently.

Lessons can be adapted to your experience level, learning pace, and personal or career goals.
Good-fit Instructor Guarantee
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Contact Abdelmalek