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Since September 2026
Instructor since September 2026
Bilingual CCNA Study Tutor: Networking Fundamentals and Exam Prep in English or Spanish
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From 32 € /h
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I studied the full CCNA curriculum in 45 days: NetAcad classes plus 150+ hours of theory and hands-on labs in Packet Tracer (OSPF, EIGRP, VLANs, STP, HSRP, ACLs, NAT). I score around 90% on full-length practice exams. I haven't taken the official exam yet (I'm preparing for it myself), so I'm not a certified instructor. What I offer is a recent, hands-on understanding of the material and of where learners get stuck, because I started from zero too.

I teach networking from first principles: why a protocol works, not just what to memorize. We cover IP addressing and subnetting, switching, routing, network services and basic security, with exam-style questions and Packet Tracer labs.

Sessions are in English or Spanish, which helps if you understand the concepts better in Spanish but need the English technical vocabulary the exam uses.

What we can do together:
- Understand topics you're stuck on (subnetting, VLANs, routing, STP)
- Practice exam-style questions and labs
- Build the English technical vocabulary for the exam
- Plan your study order and review weak areas

Online sessions via Zoom or Google Meet. Packet Tracer is free from Cisco NetAcad.
Extra information
Please let me know your current networking knowledge level and target exam date. If you have specific weak areas (subnetting, routing protocols, VLANs, etc.), mention them so I can customize our first session.

No special software required - we'll use free tools and simulators.

First lesson: $19 - we'll check your current level and plan your study.
Location
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Online from United States
About Me
Hi, I'm Adiel - a bilingual tutor specializing in English and networking/IT (CCNA preparation).

I graduated at 16 and have been helping people communicate clearly and understand technical concepts ever since. Whether you're learning English for work, travel, or personal growth, or preparing for your CCNA certification, I'll meet you where you are and help you get where you want to go.

What makes my approach different:
- I adapt to YOUR level and goals (not a one-size-fits-all method)
- I explain complex topics in simple terms (students say I make difficult things feel easy)
- I'm patient, clear, and genuinely enjoy teaching
- Fully bilingual (English/Spanish native fluency)

For English students:
I focus on practical communication - speaking confidently, understanding naturally, and using English in real situations (not just textbook exercises).

For CCNA students:
I've completed my CCNA coursework and am preparing for the certification exam. I can guide you through all exam topics - routing, switching, security, troubleshooting - with practical explanations that make complex networking concepts clear.

Let's start your learning journey. Book a trial lesson and see if we're a good fit!
Education
High School Diploma
Sharpstown High School
Graduated 2024 (Age 16)

CCNA Certification (Cisco Certified Network Associate)
Self-Study
July 2026 - Present

Completed comprehensive self-study covering routing, switching, network security, VLANs, subnetting, and troubleshooting. Currently preparing for certification exam.
Experience / Qualifications
Online Tutor (English & CCNA)
Apprentus, Superprof, Wyzant
September 2026 - Present
Remote

Teaching English language skills and CCNA/networking concepts to international students through online platforms. Providing personalized lessons adapted to each student's goals, level, and learning style.

Customer Service Representative
Cafe Express
Aug 2024 - Apr 2025
Houston

Provided exceptional customer service to 50+ customers daily in fast-paced retail environment. Communicated clearly with diverse customers, resolved inquiries efficiently, and maintained professionalism under pressure. Recognized by management and customers for outstanding communication skills.
Age
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Intermediate
Duration
60 minutes
90 minutes
The class is taught in
English
Spanish
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
Hi, I'm Adiel, a bilingual English/Spanish tutor educated in the U.S. I can explain things in either language when you get stuck, which helps if you think in Spanish first.

I passed Wyzant's subject exams in English, grammar, proofreading, reading and vocabulary, and I work daily in English with customers. I'm not a veteran teacher, so what I offer is clear explanations, real material and lessons built around your goals.

What we can work on:
- Everyday and work conversation
- Job interview practice and resume review
- Emails and professional writing
- Reading comprehension with real articles
- Vocabulary in context, including false friends between English and Spanish

How I teach: we use real content (articles, emails, interview questions) and I ask questions that make you reason in English instead of translating word by word. The tone is calm and focused, with no pressure.

First lesson: 12 for 60 minutes. We'll check your current level, set goals, and plan the next lessons together, so you can see whether my style fits you before committing.
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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.

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Additional materials + practice qs | Lesson plans + regular feedback | Recording + session notes available

A common theme running through our lessons will be to simplify - even topics like electromagnetic induction can be reduced to small bits :)

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As a Franco-Belgian management teacher, I give Excel lessons with passion!
Whether remotely or face-to-face, I offer many examples and exercises to accompany you.
I travel without problem throughout the region of Brussels and its surroundings, for lessons of at least 2 hours. For France, courses are only given remotely.

Here are some key words that will be covered in my classes:
Scenario analysis, Year, Rounding, Today, Bdnb, Bdnbval, Bdsum, Search, Column, Copy/paste in values, Copy/paste with transposition, Consolidation, Date, Datedif, Determat, Dollar, Right, Righterg, Equiv, Esterror, Estna, Frequency, Filter (simple and advanced), Format of cells, Left, Large.Value, Printing of documents, Index, Indirect, Inversemat, Day, Weekday, Line, Matrix, Max, Maxa, Max.Si, Min , Mina, Mina.If, Formatting of cells and ranges, Month, Average, Average.If, Nb, Nb.If, Nbval, Naming of cells and ranges, No, Small.value, Product, Productmat, Protection of cells, Lookup (Lookup), Lookupv (VLookup), Lookuph (HLookup), If (If), If.Not.Disp, If.Conditions, Iferror, Sum, Sumproduct, Sum.If, Sum.If.Set, Substitute , Pivot tables, Sorting, Cell locking

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verified badge
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I teach:
• 🔢 Mathematics: From algebra and calculus to applied problem-solving for real-world use.
• 💻 Computer Science: Coding fundamentals (Python, C++), algorithms, and logical thinking for beginners and intermediate learners.
• ⚛️ Physics: Mechanics, thermodynamics, and practical examples that make abstract ideas simple and visual.

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Senior professor of engineering sciences

SKILLS
IS engineering sciences
Embedded system (microcontrollers, z80 microprocessors, Motorola, ARM), Real-time system, network concept (OSI, TCP/IP), design of systems and electronic cards (analog, digital, power supply), signal processing, communication protocols ( SPI, I2C, CAN BUS, UART...), telecommunications.

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Languages: C / C ++, JAVA, VHDL / VERILOG, Python, Assembler.
Professional software:
MATLAB, SIS + PSIM + PSpice, QUARTUS, IDE68, Mikro C, Xilinix ISE, Labview, CoIDE.
Technologies:
Siemens PLC, Allen bradeley, STM32, FPGA, TIA Portal, STEP7, RSLogix

 Electrical engineering: Electric motors, Transformers
 Renewable energies: study of the solar pumping installation and the wind turbine installation.
 Electronics: analog, digital, power electronics, system electronics and instrumentation
biomedical.
 Networks and telecommunications.
 Industrial IT and programmable logic controllers.
 Automatic: modeling, identification and control of systems.
 Mechatronics.
 MATLAB
• Noise and vibration of asynchronous motors
• Speed variator
• Study and implementation of LV / MV standards
• Electrical accreditation: NF C18-510 standard
• NF C 15-100 electrical installations
• Management of electrical energy in networks (Continuous Power Flow)
verified badge
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Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

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- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
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Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
verified badge
Discover programming lessons suitable for children! With a fun and educational approach, my lessons allow young minds to dive into the fascinating world of programming. Provide your children with an enriching learning opportunity in a fun and stimulating environment.
verified badge
Experienced and patient teacher of logic for computer science.

I have taught logic, formal languages and automata theory to undergraduates for six years. My tutoring is adapted to the student's level and goals. Whether you need to learn logic for your studies, or you would simply like to know more about the subject, I will be more than happy to help you improve your understanding and skills.

Logic
The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

Formal languages and automata
A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
Regular grammar, context-sensitive grammar
Pumping lemmas for regular and context-free languages
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I teach Python specifically for finance and data applications - the kind used in economics, business analytics, and quantitative programs. This isn't a general "learn to code" course; it's built around real financial data, benchmarking, and the workflows you'll actually use in coursework or early career work.

Topics include:
Python fundamentals through a finance lens (data structures, functions, control flow).
Working with financial data and datasets.
Performance benchmarking and writing efficient code.
Applying concepts from Hilpisch's Python for Finance.
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🐍 Python Course – Learn to code and create your projects!

This course is for anyone who wants to:

✅ Learn Python from the beginning
✅ Strengthen their programming skills

📚 On the program:

Variables

Loops

Functions

Data structures

Practical projects for implementation

💡 How does the course work?

Clear explanations to understand the programming logic

Targeted exercises adapted to your level

Concrete projects to create your own applications

🎯 My goal:

Helping you understand the logic behind the code

Progress at your own pace

Create your own projects in Python and gain independence
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Objective: To understand AI without fear, to use it to simplify one's life, to know how to identify digital traps, and to use Word, Excel, etc. without difficulty.

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

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

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

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

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

Summarize a long newspaper article or document.

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

AI for creativity and memory:

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

Using AI to restore or colorize old family photos.

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

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

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

Privacy protection:

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

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

Spotting "Deepfakes":

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

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

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

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

The future: Will AI replace us or assist us?
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The terminal isn't scary, it's your superpower. Learn Linux the practical way and start working like a pro.

I work with Linux daily, running servers, analyzing logs, automating tasks with scripts, and securing systems for government, financial, and telecom organizations. I'll teach you the commands and habits that actually get used on the job. No boring theory dumps, just live, hands-on practice.

You'll learn:

Linux basics: the file system, users, and how everything fits together
Essential commands for navigating, creating, copying, searching, and editing files
Permissions and ownership: chmod, chown, sudo, and staying safe as root
Processes, services, and package management (apt, systemctl, and more)
Text processing and log analysis with grep, awk, sed, and pipes
Networking commands and remote access with SSH
Bash scripting basics to automate your everyday tasks

Perfect for: beginners, students, career changers, developers, IT staff, and anyone preparing to learn cybersecurity, DevOps, or system administration.

You'll walk away with the confidence to work in any Linux terminal, the ability to automate repetitive tasks, and a solid foundation for IT, cybersecurity, or development careers.

No experience needed, just curiosity and a computer. Book your first session and let's open the terminal!
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Session 1: Revolutionizing your Scientific Writing with LaTeX & AI
Duration: 2 Hours | Level: Beginner | Tools: Overleaf + AI**

First Hour: Foundations and Cloud Environment (60 min)

1. Introduction to LaTeX Philosophy (15 min)

- The "WYSIWYM" concept:** Explain the difference between Word (*What You See Is What You Get*) and LaTeX (*What You See Is What You Mean*). Why content takes precedence over form.
- Key advantages:** Unrivaled typographic quality, automatic reference management, stability on long documents (theses), and free of charge.
- The structure of a file:** Distinction between the **preamble** (the brain: settings and packages) and the **body of the document** (the heart: text).

2. Immersion in Overleaf (25 min)

- Configuration:** Creation of an account and first project "Blank Project".
- Exploring the interface:** The file panel (left), the code editor (middle) and the PDF preview (right).
- Real-time collaboration:** How to share a project and leave comments (like on Google Docs).
- History and versions:** How to revert to a previous version in case of a compilation error.

3. Practical Workshop: My First Document (20 min)

* Writing basic commands: `\documentclass`, `\usepackage[french]{babel}`, `\title`, `\author`.
* Compilation of the document and observation of the result.
* Structuring: Use of `\section` and `\subsection`.

Second Hour: Mathematics and the Magic of AI (60 min)

4. The Power of Mathematics (20 min)

- Mathematical modes:** Difference between the text (`$...$`) and the centered block (`\[...\]`).
- Essential syntax:** Fractions `\frac{}{}`, exponents `^`, indices `_`, and roots `\sqrt{}`.
- Introduction to AMS packages: Why amsmath and amssymb are essential for professional rendering.

5. From hand to screen: AI at the service of LaTeX (30 min)

- Presentation of OCR tools:** Use of **Mathpix Snip** (the leader) or models like Gemini/ChatGPT to transform a photo into code.
- Concrete demonstration:
1. Take a picture of a complex handwritten formula (e.g., an integral with matrices).
2. Use AI to generate the corresponding LaTeX code.
3. Correction and insertion: Learn to check the AI-generated code before copying and pasting it into Overleaf.

6. Conclusion and Q&A (10 min)

* Summary of achievements.
* Resources for further exploration
* Definition of the exercise for the next session.
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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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This course is aimed at students, technology enthusiasts and professionals in career transition who wish to demystify the world of networks and telecommunications.
The main objective is to make this discipline concrete, accessible and directly applicable.

What you will learn:
- Decode the architecture of modern mobile networks (4G, 5G) and data networks.
- Analyze the essential communication protocols that make the Internet work on a daily basis.
- Master the basics of transmissions (fiber optics, wireless links, routing).

My teaching method:
If you're a complete beginner or these concepts seem too abstract, don't worry. We'll go through each key concept step by step. I use simple visual diagrams, everyday analogies, and practical examples to avoid unnecessary jargon. My goal is to build your confidence and transform theory into real-world skills, all within a supportive and stimulating learning environment.
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This cohort is designed for young people who want to learn in an affordable, flexible, and enjoyable way without having to dedicate a huge amount of time each week or even just extra support.

This beginner-friendly course introduces students to the world of computers and computer science through simple explanation.

Students will learn how computers work, including hardware, software, memory, storage, data, and how a computer processes information. They will then explore how applications are used to create and organize information, with practical experience using tools such as Microsoft Word, PowerPoint, and Excel.

As the course progresses, students will be introduced to important computer science concepts including binary numbers, algorithms, programming, databases, networks, the Internet, and cybersecurity.

By the end of the course, students will have a good foundation in computer science and improved digital skills.
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Additional materials + practice qs | Lesson plans + regular feedback | Recording + session notes available

A common theme running through our lessons will be to simplify - even topics like electromagnetic induction can be reduced to small bits :)

Together, we'll:
1. Find learning gaps
2. Break concepts into small bits
3. Apply to real world and exam questions
4. Work on exam technique - like the difference between "explain" and "describe" questions
5. Build mark-scheme friendly language

“It's not that I'm so smart, it's just that I stay with problems longer”
- Albert Einstein, while studying superposition of waves, I’m sure :)
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