Agent-Based Modelling using Mesa library in Python

From 58 € /h

Learn Agent-Based Modeling with a Pro!.

Got a complex system you want to crack? Or just curious about how a bunch of virtual agents can model everything from traffic jams to zombie apocalypses? With 5+ years of teaching bachelor’s and master’s students at TU Delft, I’m here to help you level up your agent-based modeling skills in Python using Mesa library.

We’ll explore how to:
• Simulate traffic jams (so you can finally figure out why your commute takes forever).
• Model epidemics (think less doomsday, more public health superhero).
• Model wealth distribution (yes, even agents argue about who gets the last piece of virtual pie).
• Build eco-simulations where foxes, rabbits, and plants fight for survival.

Whether you’re a total newbie or already know your way around Python, I’ll make the technical stuff simple, the concepts clear, and maybe even throw in a bad joke or two along the way.

Let’s turn your ideas into awesome simulations—and maybe have some fun while we’re at it!

Location

Online from Netherlands

Age

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

90 minutes

120 minutes

The class is taught in

English

Arabic

Dutch

Skills

Computer modeling

Network infrastructure

Python

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Mastering the Fundamentals: Personalized Math, Physics & Engineering Tutoring

15 € /h

With years of tutoring experience and a genuine passion for education, I provide high-quality guidance to help you overcome challenges and achieve success in these subjects. Whether you're struggling with math formulas, tackling physics problems, or diving into engineering concepts, I'm here to support you every step of the way.

My teaching approach focuses on interactive learning and practical applications, making complex topics more accessible and enjoyable. Whether you're a high school student preparing for exams or a university student navigating advanced coursework, my private lessons are designed to empower you to excel academically.

Arabic Language Mastery: Private Lessons for Proficiency

19 € /h

With a deep understanding of Arabic language and culture, along with extensive teaching experience, I provide high-quality guidance to help you master this beautiful language. Whether you're a beginner starting from scratch or an advanced learner striving for fluency, I'm here to support you every step of the way.

My teaching approach emphasizes practical communication skills, cultural insights, and interactive learning activities to make your Arabic learning experience engaging and effective. Whether you're learning for travel, work, or personal enrichment, my private lessons will empower you to confidently navigate Arabic language and culture.

Dr.

5.0

(15)

I am Dr Iyer- a tutor with over 18 years of teaching experience as of 2023 and students from across the globe. I teach one-on-one online (over Skype/ Google Hangout and other media) using a pen tablet and the screen-share feature.

I have helped several students in courses like Python Programming, R Programming, Data Science,
Machine learning etc. I can customise the content to domains like business, economics finance and investments as per student requirements.

I have taught students of various age groups - high school (IB/Cambridge/IGCSE/ ICSE,) University (bachelors, masters, doctoral) and working industry professionals.

More than anything, I trust that if I can replace the fear of a subject with love for it, then I would have truly made a difference to the student.

Matías

5.0

(15)

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

5.0

(15)

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.

5.0

(15)

Engineer in engineering sciences option electrical engineering
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.

Technical skills :
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)

Amin

5.0

(15)

Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
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:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

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.

Salah

5.0

(15)

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.

Amine

5.0

(15)

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.

Ali

5.0

(15)

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

5.0

(15)

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.

Baia

5.0

(15)

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

Pallavi

5.0

(15)

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.

Chalbi

5.0

(15)

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.

Giuseppe

5.0

(15)

I’m a SideFX Certified Instructor and 3D artist with 20 years of experience in CGI. I offer one-to-one online Houdini lessons tailored to your level, interests, and goals.

If you’re new to Houdini, we can start with the interface, nodes, attributes, and the principles of procedural modeling. If you already use it, we can focus on VEX, simulations, lighting and rendering, or building more effective procedural workflows. I can also help you understand and troubleshoot a project you’re working on.

Lessons are practical: we’ll work in Houdini together, and I’ll explain the reasoning behind each step so you can apply what you learn independently. Before our first session, tell me about your experience and what you’d like to achieve, and I’ll prepare a lesson around it.

Baptiste

5.0

(15)

My method is based primarily on practice, because I believe that it is by writing code and trying to solve problems that one truly progresses in programming.
Each lesson begins with an explanation of the new concepts we will cover. I then provide exercises tailored to the student's level, which we work through together gradually. The goal is not simply to give the answer, but to understand the reasoning that leads to the solution.
I adapt to each student's pace and difficulties: if a concept isn't understood, we take the time to review it with simple examples before returning to practice. Conversely, if the basics are mastered, we can move on to more complex exercises.
A typical lesson therefore usually takes place in three stages: review or discovery of a concept, guided practical exercises, then correction and explanation of errors.
My courses are primarily aimed at beginners and students discovering Python, particularly in high school or the first years of higher education. I can help them understand the basics of the language: variables, conditions, loops, functions, lists, dictionaries, etc.
My goal is for the student to gradually become autonomous when faced with an exercise, rather than simply learning solutions by heart.

Cedric

5.0

(15)

Vous souhaitez apprendre Python, découvrir la programmation ou renforcer vos bases ?
Enseignant en informatique et titulaire d’un Master en Sciences Informatiques, orientation Data Science, je propose des cours adaptés à votre niveau et à vos objectifs.
Nous pouvons travailler notamment sur les bases de Python, les variables et types de données, les conditions, les boucles, les fonctions, les structures de données, les fichiers, ainsi que la résolution de problèmes et les premiers projets en Python.
Mon approche est avant tout pratique : j’explique les notions progressivement, avec des exemples simples, puis nous les appliquons à travers des exercices. Le contenu et le rythme sont adaptés aux difficultés et aux objectifs de chaque apprenant.
Les cours s’adressent aux débutants, étudiants ou adultes souhaitant apprendre Python ou consolider leurs connaissances en programmation.