Python Programming for Biology, Bioinformatics & Data Analysis

From 40 £ /h

Python is the industry-standard programming language for data analysis, machine learning, and scientific computing. This course provides hands-on, practical instruction tailored for biology students, medical researchers, and life science professionals seeking to automate research workflows and analyze biological datasets.

Drawing on my background in university lecturing and computational biology, I teach Python from foundational syntax to advanced data manipulation:
Core Python Fundamentals: Data types, loops, conditional statements, functions, and file handling (reading/writing FASTA, FASTQ, and CSV files).
Data Wrangling & Analysis: Using Pandas and NumPy for parsing genomic datasets, filtering experimental data, and statistical summaries.
Data Visualization: Creating publication-ready figures using Matplotlib and Seaborn (heatmaps, PCA plots, expression plots).
Bioinformatics Libraries: Utilizing Biopython for sequence manipulation, BLAST queries, and structural file processing (PDB).

Sessions are customized to your specific learning goals, whether you are writing your first script, working on a university project, or analyzing raw laboratory data.
Reach out to discuss your specific learning objectives or project requirements!

Location

Online from Luxembourg

About Me

I am Hadeer, an Assistant Lecturer (on leave) at Alexandria University, specializing in Biology and Genetics.

I hold a Master of Science in Biotechnology. My academic journey has provided me with a strong foundation in various fields of biology, complemented by a Professional Diploma in Bioinformatics.

Teaching and sharing knowledge has always been my passion. Over the years, I have taught a wide range of biology-related subjects, including General Biology, Genetics, and Biodiversity. My teaching experience spans from university-level courses at Alexandria University to hands-on lab sessions covering topics related to the biology and life science. Additionally, I have more than two years of experience in teaching biology to children, where I focus on creating interactive and engaging lessons that simplify complex concepts, making them accessible and enjoyable for young learners. I use a variety of teaching tools, including hands-on activities, visual aids, and storytelling, to foster curiosity and a love for science from an early age.

My teaching philosophy revolves around making complex scientific concepts accessible and engaging for students. Whether you're a high school student preparing for exams or a university student navigating advanced topics in biology and bioinformatics, I am here to help you succeed. I can also provide support with standardized test preparation, such as the GRE, focusing on the biology and analytical portions.

To know more about my teaching approach or to discuss your specific learning needs, please feel free to reach out. I look forward to helping you achieve your academic goals!

Education

Master of Science in Biotechnology, Egypt-Japan University of Science and Technology (E-JUST)

Bioinformatics Professional Diploma, Nile University

Bachelor of Science, Major in Botany; Minor in Chemistry, Alexandria University

Experience / Qualifications

Assistant Lecturer at Alexandria University with over 6 years of teaching experience in Biology, Genetics, and related subjects.

Extensive experience in bioinformatics research, including NGS data analysis and statistical analysis using R, Python, and Bash.

Proven track record of successful student outcomes and a passion for making science accessible and enjoyable.

Age

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

60 minutes

The class is taught in

English

Arabic

Skills

Python

Computer programming

Reviews

Availability of a typical week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

IB Biology (SL/HL) & Secondary School Biology Exam Preparation

45 £ /h

Mastering high school biology—especially the IB Biology Diploma Programme—requires both deep conceptual understanding and rigorous exam technique. This course is fully aligned with the IB Biology syllabus across all core themes: Unity and Diversity, Form and Function, Interaction and Interdependence, and Continuity and Change.

As a University Assistant Lecturer with over six years of academic teaching experience, I help students navigate both Standard Level (SL) and Higher Level (HL) topics, including:
Cell & Molecular Biology: Cell structure, membrane transport, enzymes, cellular respiration, and photosynthesis.
Genetics & Biotechnology: Nucleic acids, transcription, translation, inheritance patterns, PCR, and gel electrophoresis.
Human Physiology & Health: Organ systems, immunology, neurobiology, and hormonal regulation.
Ecology & Evolution: Natural selection, speciation, energy flow, biodiversity, and conservation biology.
HL Exclusive Content: Advanced gene expression, nucleic acid detail, tissue differentiation, and complex metabolic pathways.

Beyond theory, we focus on syllabus-specific assessment skills: step-by-step guidance on your Internal Assessment (IA) (research question design, data analysis, and statistical evaluation), mastering Paper 1 (MCQs & Data Analysis), and writing structured responses for Paper 2. Lessons are customized to your exam board and current learning pace.

Feel free to reach out to discuss your current syllabus topics or IA progress. I look forward to helping you achieve top marks!

Interactive Biology and Life Science Lessons for Primary & Middle School

40 £ /h

Building a strong foundation in science early on gives young learners a huge advantage in school. This course introduces primary and lower-secondary students to key life science curriculum standards through structured, age-appropriate units designed to foster scientific thinking.

Covering primary science learning objectives, our lessons explore core topics including:
The Diversity of Living Things: Classifying plants, animals, fungi, and microorganisms, and understanding their habitats.
Human Body & Health: The major organ systems (circulatory, digestive, respiratory), nutrition, skeleton, and senses.
Plants & Ecosystems: Seed germination, photosynthesis, pollination, food chains, and environmental care.
Life Cycles & Inheritance: How organisms grow, reproduce, and pass on traits from generation to generation.

Lessons incorporate visual models, interactive diagrams, simple experiments, and structured guided practice to make abstract concepts tangible. Whether your child needs help keeping up with school coursework, preparing for key school assessments, or extending their knowledge beyond the textbook, every session is personalized to their age and confidence level.

Feel free to contact me to discuss your child's current science topics and learning goals. Let's make learning science an inspiring experience!

Hamza

4.88

(8)

Aged 31 and a Doctor in mathematical physics (theoretical physics), I teach physics and mathematics courses for high school and license in French, Arabic and English. As I have experience in the field of private lessons of 8 years and 2 years as teacher of the program of the French mission and access competitions to higher schools.

Youssef

4.88

(8)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Matías

4.88

(8)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Adam

4.88

(8)

doctoral student in engineering sciences provides support courses in analog and digital electronics at any DEUG level and engineering schools. having scientific and technical knowledge, three years of experience in the field of teaching, pedagogy and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they are having difficulty. for more info please contact me

Giuliano

4.88

(8)

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!

Salah

4.88

(8)

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

4.88

(8)

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.

Baia

4.88

(8)

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.

Abderrahim

4.88

(8)

Do you have a Python project to complete for your studies and you don't know where to start, or are you stuck in your code?
👉 I offer you fast, structured and results-oriented support to help you move forward effectively and succeed in your project.
🚀 What you will get:
Practical support for your university project (practical work, mini-project, dissertation, etc.)
A clear understanding of the code and logic used
Step-by-step solutions explained to help you progress quickly
Clean, structured and functional code
Greater autonomy for your future projects
🔍 My method:
Analysis of your topic and your needs
Breaking down the problem into simple steps
Clear explanations + direct practical application
Correction and improvement of your code
Tips to avoid common mistakes
👨‍💻 For whom?
Students in computer science or scientific fields
Students with projects or practical work in Python
Beginners or intermediates stuck on an exercise
Anyone with a project to finalize quickly
🎯 Objective:
👉 Helping you understand, correct and successfully complete your Python project effectively, while gaining autonomy
📩 Contact me now to move your project forward quickly and achieve concrete results

Farouk

4.88

(8)

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

4.88

(8)

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.

Azhar

4.88

(8)

Are you interested in learning Python but don't know where to start? This course is designed to help you understand the fundamentals of Python programming in a simple, practical, and enjoyable way.

Python is one of the most popular programming languages in the world. It is widely used in software development, automation, data analysis, artificial intelligence, and web development.

Whether you are a complete beginner, a student, or someone looking to develop new technical skills, these lessons will help you build a strong foundation in programming.

You will learn
1. Introduction to Python
2. Python Fundamentals
3. Conditional Statements and Loops
4. Working with Data
5. Functions and Practical Programming
6. Mini Projects

Aya

4.88

(8)

You have a kid that's interested in programming?? Set up a class for him with me. Aya a software engineer turned teacher. I was a software engineer for 3 years before I joined the teaching industry and I currently teach computer science in Chichester College in United Kingdom. I want to advocate for computer science and help familiarise kids at a young age with programming in Python.

Send me a message let's chat about what you want your kid to learn and what I can offer! :)

Khalil

4.88

(8)

Learn Python by building something you’ll actually use

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

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

Where you can go next

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

Your instructor

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

Ready to start?

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

Hugo

4.88

(8)

Is your code not doing what you want it to? Are you learning Python but just copying and pasting without really understanding?

Loops, functions, algorithms, data structures... Behind these intimidating concepts lie simple, visual ideas. My goal: to help you understand them, not just apply them.

These tools may seem difficult at first, but they make perfect sense once you visualize them in practice: seeing a loop run, a variable change, a list fill up. That’s the level I’d like to help you reach, using diagrams, analogies, and programs we’ll build together, line by line.

I offer computer science lessons (Python and other languages), from middle school through college, to help you:
- overcome obstacles and regain confidence,
- prepare for your exams (Brevet, Baccalaureate, midterms, entrance exams, NSI),
- make progress on your projects: lab assignments, scripts, games, digital projects...

Each lesson is tailored to your needs: we’ll go over the tricky parts, code together, and I’ll teach you methods to become self-sufficient.

Message me to schedule your first lesson: let’s make the abstract clear!