Course on Digital Circuits: FPGA, VHDL, SYSTEMVERILOG, UVM.

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From 15 £ /h

If you're seeking to gain a competitive edge in the VLSI field, you have found the ideal resource. As a seasoned Hardware Design Verification Engineer, I offer my tutoring services to individuals interested in delving into Digital Electronics, as well as FPGA/ASIC/SoC Circuits. Whether you require assistance in Design (VHDL, VERILOG, SYSTEMVERILOG) or Verification (Simulation Synopsys), I am well-equipped to provide the support you need. Please feel free to reach out to me without hesitation.

Location

Online from Morocco

About Me

I am a hardware design verification engineer and a PhD student in deep learning and embedded systems, if you are looking for courses on:
digital electronics, design and verification processes, artificial intelligence, machine learning and deep learning, then you are in the right place.

Skills:
• Artificial intelligence, machine learning and deep learning
• Verification methodologies: UVM, C-driven, formal (SVA), OOP, constrained random verification, metric-driven verification, UVM and C based testbenches, code coverage.
• Languages: System Verilog, C, C++, Tcl, Verilog, VHDL, Makefile, Python, XML.
• Simulation: VCS/Synopsys.
• Data management, tracking: SVN, JIRA.
• Flow: verification plan, schedules, VIP, test benches, sequences and test cases, integration tests, coverage, checkers and assertions, regressions.

Education

Doctoral student: Development/optimization of embedded systems and image processing algorithms for the detection of traffic offenses in real time.
Engineer in embedded electronic systems.

Experience / Qualifications

2+ years as a verification engineer.
1 year+ as an automotive software engineer.
Skills:
• Artificial intelligence, machine learning and deep learning
• Verification methodologies: UVM, C-driven, formal (SVA), OOP, constrained random verification, metric-driven verification, UVM and C based testbenches, code coverage.
• Languages: System Verilog, C, C++, Tcl, Verilog, VHDL, Makefile, Python, XML.
• Simulation: VCS/Synopsys.
• Data management, tracking: SVN, JIRA.
• Flow: verification plan, schedules, VIP, test benches, sequences and test cases, integration tests, coverage, checkers and assertions, regressions.

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

Duration

60 minutes

The class is taught in

English

French

Arabic

Skills

Electronic circuits

Computer programming

Engineering

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

Course on Machine Learning with Python from key concepts to applications

15 £ /h

The aim of this program is to provide you with the necessary skills and experience to begin your journey and get a head-start in Machine Learning.
Covering the primary types of machine learning, the program offers a comprehensive theoretical understanding of Machine Learning with opportunities to practice using algorithms, methods,
and best practices associated with Machine Learning. You will also have the chance to develop your own projects using relevant open-source frameworks and
libraries and apply your learnings in various courses to a final project.

Whether you are already proficient in Python programming, statistics, and linear algebra, or have a general interest and are willing to learn,
this beginner/intermediate oriented series is suitable for you.

Gaëlle

5.0

(3)

Most kids think coding is for "smart kids" or "future programmers."
It's not. Coding is how real people solve real problems.
In this class, we skip the theory. Your child creates real things.

What they'll do:
✓ Build real projects in Scratch: a working game, an interactive animation, a story they coded
✓ Program virtual robots: solve real-world challenges (navigate a maze, automate a task, build a system)
✓ Create in Minecraft Education: design worlds, automate constructions, solve logic problems
✓ Experiment with different languages: not just learn "the right way," but understand that there are many ways to think about a problem
✓ Collaborate and share: work with other kids, get feedback, improve their work
✓ Develop logical thinking: not just for coding, but for anything: solving math problems, science challenges, real-world situations

Why this is different:
We don't teach syntax. We teach how programmers think.
Most children's coding courses say "here's the code, copy it." We teach "what problem are we trying to solve? How could we break it into steps? What options do we have?"
When your child learns to think like a programmer, they can learn any language afterward.

What they take home:
A portfolio of 3–4 completed, working projects. The ability to say "I built this." And the deep understanding that code is a tool to make real things happen.

Format: Online or Barcelona | 60–90 min sessions | Flexible pace, no prior experience needed
For curious 8-12 year olds who want to build.

Matías

5.0

(3)

Do you want to master the most used design software and bring your ideas to life in 3D? Do not search anymore ! I offer specialized courses to guide you through the exciting worlds of CATIA V5/V6, Inventor, Fusion 360, FreeCAD and 3D printing.

CATIA V5/V6: Discover the design software preferred by engineers for creating complex models and precise assemblies.

Inventor: Dive into the world of mechanical design and learn how to develop innovative products with this powerful software.

Fusion 360: Create organic models, run simulations, and hone your design and engineering skills.

FreeCAD: Explore the basics of parametric design and create 3D models ready for manufacturing.

️ 3D printing: Bring your designs to life! Learn how to use 3D printers, from modeling to concrete production.

Whether you're a beginner or looking to improve your skills, my classes are suitable for all levels. With interactive lessons, hands-on projects, and expert guidance, you'll progress quickly and with confidence.

Don't wait to explore the endless potential of 3D design and 3D printing. Join me on this exciting adventure and start creating your own 3D masterpieces today!

Don't miss this opportunity to develop in-demand skills in 3D design and printing. Join me for enriching and practical lessons you won't forget!

See you soon for our first class together!

5.0

(3)

Hello, I am a doctor in electrical engineering and associate professor in engineering sciences, experienced in the field of electrical engineering, I offer support courses in the subjects of engineering sciences (electronics, automation, electrical engineering, automation, programming).

Digital electronics
Analog electronic
electromagnetism (propagation of high frequency waves)
Automatic (continuous, sampled)
electrical engineering (transformers, electrical machines, switching power supply)
C / c ++ programming, Assembler, ARM, STM32
renewable energy (wind, PV)
engineering Sciences
RDM
Python,VHDL
PIC Microprocessor and Microcontroller
Signal processing and data acquisition
Engineering Sciences

These courses allow the student to get up to speed and regain confidence in all scientific subjects, just as they prepare him effectively for the Baccalaureate, the Preparatory Classes or various examinations of the engineering classes.

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 educational approach is effective since it has often led me to interesting results with my students.

Associate professor provides support courses in electrical engineering

Jeremy

5.0

(3)

Passionate & empathetic teacher. I have a Master's in Physics with honors from the University of Leicester (which was featured at the time as a top 5 Physics university in the UK by The Guardian) and a - french - European School diploma in which I achieved 90% in Physics and 85% in Maths.

Helping others understand difficult topics and skills is something that I am very passionate about as an empathetic person. I have 5 years of experience teaching Physics and Maths to kids from unprivileged backgrounds both in a homework schools as well as via private teaching. In private teaching, I have experience tutoring people with learning disabilities (ADHD, Dyslexia, Discalculia and more), younger kids of ages 7-12 and older students preparing for their final baccalaureate exams in advanced maths/physics curriculums.

In my classes, I aim to:

- help students achieve better grades in exams/tests in all branches of Physics & Maths
- clearly explain and break down topics
- give context and or example applications of topics (to improve understanding and memorization)
- help with ADHD & other learning disabilities
- give practical advice for university applications (eg. UCAS in the UK) and discuss the exciting Physics research/work and projects you can work on later in life.

Physics has a plethora of useful and fascinating applications, from the detection of Gravitational Waves and Gamma-Ray Bursts to the development of novel Medical Imaging techniques and Nano-technology (eg: smartphones). It is a subject that I am very passionate about and I hope to make use of my years of experience and extensive knowledge to help you understand and love the subject! My lessons will always be tailored to the individual needs of the student, so please do not hesitate to contact me if you have questions!

Enrique

5.0

(3)

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.

Samaa

5.0

(3)

With over 4 years of experience I teach math curriculums (GCSE, IGCSE, IB CNISE, SAT) to students from earlier stages, elementary to high school. I focus on all mathematical concepts, develop classroom materials, organize activities, assign homework, grade tests, and prepare students for exams. I prepare mathematics curriculum for my students, like college entrance exams.

I demonstrate excellent mathematics skills and analytical thinking alongside solid instruction. I instruct my students throughout the year and create lesson plans, assign homework, and manage online classrooms. I keep in touch with parents to be aware of the progress.
I hold a Master's degree in Engineering with teacher education courses and I've achieved the highest grades in my math courses throughout the years with straight A Grades.

My Responsibilities towards my students
-Create a great environment that is conducive to learning.
-Care for and effectively assist students with special concerns.
-Analyze data to determine student progress and achievement.
-Work with individual and small groups of students to support mathematics instruction.
-Encourage students who need extra help
-Plan and carry out instructions, activities and prepare learning materials.
-Maintain appropriate records and follow required procedures and practices.
-Work with students to develop and monitor academic goals for both short-term and long-term success.

My qualifications
-Master Degree in Engineering
-An experienced teacher for over 4 years
-Experience with calculus, geometry, statistics, and trigonometry.
-Dedication to instruction of critical thinking and problem-solving with confidence in a collaborative environment.
- Leadership skills and a positive attitude when assisting with decision making.
-Demonstrated professionalism and dedication to continuous improvement.
-Time management skills.

Giuliano

5.0

(3)

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!

Nicolas

5.0

(3)

As a current Master's student in Aerospace Engineering at TU Delft, I have successfully navigated the entire Bachelor's curriculum and the competitive selection procedure, so I am fully equipped to guide you through the study plan and specific admission requirements. I offer personalized tutoring sessions designed to ensure comprehensive preparation for the entrance exams. These classes include a detailed review of key concepts in Mathematics and Physics, intensive practice with relevant exercises, and specific strategies to tackle the test effectively. I also place a dedicated focus on mastering the First Year Material (FYM) section (often the most challenging and unfamiliar part for applicants) to help you build the confidence and skills necessary to succeed. Furthermore, I am happy to discuss the degree program itself and explore the opportunities available in Delft to help you prepare for your future student life.

Ayoub

5.0

(3)

This preparation session is dedicated to students aiming for preparatory classes for scientific Grandes Ecoles (CPGE), with a particular focus on the subjects of Physics and Engineering Sciences. The goal is to strengthen the foundations and deepen the knowledge to succeed.

1. Mechanics:
Kinematics: Study of rectilinear and circular movements, position vectors, speed and acceleration.
Dynamics: Newton's laws, work and energy, kinetic energy theorem.

2. Electromagnetism / Electrokinetics:
Electrostatics: Electric charges and fields, electric potential, capacitance.
Magnetostatics: Magnetic fields, Lorentz forces, electromagnetic induction.
Alternating Currents: RLC circuits, resonance, impedance.

3. Thermodynamics:
Principles of thermodynamics: Internal energy, heat, work, first and second principles.
Ideal and real gases: Equations of state, thermodynamic transformations.

4. Industrial sciences:
Automatic Linear, Kinematic, Static.

For more information and to register for the preparation session, please contact me.

Good preparation and success in your studies!

.

Roland

5.0

(3)

The TU Delft Aerospace Engineering Bachelor is one of the most prestigious bachelor programmes the Netherlands has to offer. As it is highly sought-after by students all around the globe, there is a highly competitive selection procedure which needs to be completed to get admitted to this popular degree. A major part of this admission procedure is the selection exam, consisting of three different tests: Mathematics, Physics and First-Year Material.

As a cum laude graduate Aerospace Engineer at TU Delft, who has also been tutoring since 2017, I have a lot of experience and knowledge of the program to help you out with the right preparation to get in. Over the last four years, I have helped tens of students secure a spot! Moreover, I offer a free personalised lesson plan for each student, which is fully based on the admission syllabus and past exams, to ensure an even higher chance of admission for each student.

With my calm and stepwise explanation, weaker topics will be addressed, and your solution procedures will become more effective and accurate. Each lesson will either be theory, exercise-based or an opportunity to talk about the admission, student life, the city of Delft, what to expect from the study and whether it is the right fit for you.

Ali

5.0

(3)

I offer one-to-one Electronics and Electrical Engineering tuition for university students, college students, and serious learners. Lessons are available online or in person around Birmingham.

What I cover:

Circuit analysis (DC and AC, Kirchhoff's laws, Thevenin / Norton, op-amps)
Digital electronics and logic design
Signals and Systems, Digital Signal Processing (DSP)
Control systems (Laplace, transfer functions, stability, frequency response)
Embedded systems and microcontroller basics
Power electronics fundamentals
University coursework, lab reports, dissertation and project support
Exam preparation for engineering modules

How I teach:
I start by figuring out exactly which concepts are tripping you up — most students are stuck on one or two key ideas, and once those click, everything else falls into place. I use plenty of worked examples, real circuit diagrams, and clear explanations of the maths behind each topic. For project and dissertation work, I can help you plan, debug, and present your work properly.
If you're struggling with an engineering module, preparing for exams, or working on a final-year project, I can help you turn confusion into confidence.

Baia

5.0

(3)

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.

Farouk

5.0

(3)

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

5.0

(3)

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.

Abdelmalek

5.0

(3)

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: