Bioinformatics & Computational Biology: Data Analysis and Tools

From 53 $ /h

Modern biological research relies heavily on computational tools to analyze complex genomic, transcriptomic, and proteomic data. This course offers practical, hands-on tutoring in bioinformatics for university students, researchers, and biological science professionals looking to gain strong computational and analytical skills.

Drawing on an extensive academic background in biological sciences and computational methodologies, I guide students through core computational workflows:
Sequence Alignment & Search: BLAST algorithms, multiple sequence alignment (Clustal Omega, MUSCLE), and pairwise alignment techniques.
Genomics & Transcriptomics: Next-Generation Sequencing (NGS) data processing, variant calling, and differential gene expression analysis.
Structural Bioinformatics: Protein structure prediction, molecular visualization (PyMOL, Chimera), and macromolecular interaction analysis.
Biological Databases & Programmatic Access: Extracting and parsing data from NCBI, UniProt, Ensembl, and PDB using Python/R scripting.
Phylogenetics & Systems Biology: Building phylogenetic trees, evolutionary distance calculations, and metabolic network modeling.

Sessions are tailored to your specific coursework, thesis project, or research needs, helping you transition seamlessly from raw biological data to meaningful biological insight.

Feel free to reach out with your project details or course outline to discuss how we can structure your lessons!

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

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

Database

Python

Reviews

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

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

60 $ /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

53 $ /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!

Matías

4.88

(85)

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.

Amin

4.88

(85)

Are you a university student, engineer, or professional who needs to actually use data — not just learn theory about it?
This course is built around real problems and real code. We skip the textbook formulas and go straight to applying statistics and data science the way professionals do: with Python (pandas, NumPy, scikit-learn, matplotlib) and R (RStudio).
What we cover, adapted to your level and goals:
- Descriptive and inferential statistics (the ones that actually matter)
- Data cleaning, exploration, and visualization
- Regression, classification, and intro to machine learning
- Time series and forecasting basics
- R for statistical analysis and academic research

Who this is for:
- University students in statistics, economics, engineering, or biology
- Professionals wanting to move into data analysis or data science
- Researchers who need to process and present data properly

I use Python and R professionally as a working engineer — everything I teach comes from real application, not just academic exercises.

Salah

4.88

(85)

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.

Vikash

4.88

(85)

Master the art of web design and development with personalized 1-to-1 online tutoring in Python, PHP, and Other server side programming languages.

Whether you're a beginner looking to build your first web project or an experienced developer aiming to refine your skills, our customized tutoring sessions are designed to help you achieve your goals.

I really happy to teach people who will really want to part of my lesson.

My teaching style is the step by step oriented. We will start from basic and move towards advanced topics.

A very warm welcome my students on apprentus.com

Wish you all the best.

Patrick

4.88

(85)

I offer professional support in sampling, surveying, data collection, and quantitative data management. This service is designed for organizations, researchers, students, NGOs, and businesses seeking to design reliable surveys and effectively utilize their data. My services include defining appropriate methodologies, designing data collection tools, fieldwork supervision, quality control, and database organization and structuring. Support is also available for analyzing and interpreting results. My services are flexible and tailored to specific needs.

Baia

4.88

(85)

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.

Hayat

4.88

(85)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Amr

4.88

(85)

Private Programming Lessons for you / your family / your company employees
Programming Tutor – IGCSE & Computer Science Subjects
Deeper understanding, stronger results

• Lecturer at the American University AUC
• Over 20 years of experience in training students for government employees, oil companies (BP), food companies (Nestle), banks (CIB), and telecommunications companies (Vodafone).

• Teaching curricula, syllabuses, courses:
o IGCSE (Computer Science 0478, ICT 0417)
o Programming and computer courses for all educational levels (from primary to university)
o Microsoft Windows, Word, Excel, PowerPoint, Outlook, MS-Project
o Programming, C, C++, VB.NET, C#, Python, Database, SQL, MQL, VBA
o HTML, CSS, JavaScript, Angular
o Different database systems
o Data analysis using Excel
o Computer and Information Colleges Curricula
o Using artificial intelligence in life and work

• Master office applications to improve your job performance.
• Prepare yourself to work as a Front-End / Back-End / Full Stack Developer
• Theoretical and practical training for market requirements
• Don't miss out on technology. Lessons are designed for the elderly, in a simple and understandable way (use of computers and their programs, use of mobile phones, dealing with the Internet and social media).
• Lessons are available in person or online.

Mohamed

4.88

(85)

This course is for anyone who wants to learn to program in Python, whether you are a student, a professional, or simply curious.
Python is one of the most widely used languages today, thanks to its simplicity and power. You'll learn how to write your first programs, manipulate data, automate tasks, and understand the essential foundations of modern programming.
The objective is to make you independent in developing your own projects (scripts, small software, data analysis, etc.) and acquire a skill sought after in the academic and professional world.

Ali

4.88

(85)

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.

Vikas

4.88

(85)

Experienced Programming Language Tutor with 10+ years of teaching experience in Python, HTML, CSS, and JavaScript. I provide step-by-step, practical-oriented learning designed for beginners, students, and aspiring developers. My teaching approach focuses on real-world projects, hands-on coding exercises, and easy-to-understand explanations to help students build strong programming skills confidently.

What You Will Learn:
Python Programming Fundamentals to Advanced Concepts
HTML for Website Structure
CSS for Modern Web Design & Styling
JavaScript for Interactive Web Development
Real Projects and Practical Assignments
Debugging and Problem-Solving Techniques
Frontend Development Basics
Teaching Style:
Step-by-step guidance
Beginner-friendly explanations
Practical and project-based learning
Live coding sessions
Personalized support and doubt clearing
Easy learning methods with real examples

Perfect for:

School & college students
Beginners in coding
Future web developers
Anyone wanting practical programming skills

Ammar

4.88

(85)

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.

Pallavi

4.88

(85)

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.

Azhar

4.88

(85)

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

Aditya

4.88

(85)

Python class from basics to the advance from the students perspective with proper deep understanding of concepts.
Topics to be covered:
Basic Python and Programming fundamentals
Memory Management
OOPs
Data Structure and Algorithms
Libraries
Data analysis (using libraries Pandas, Numpy, etc.)
AI (ML, DL, RL, LLMs, RAG, Langchain etc.)

Maths using visualization of geometry, algebra, calculus, etc.