Programming Fundamentals with Python and Data Analytics Literacy

From 74 £ /h

Data Literacy is "the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods, and techniques applied — and the ability to describe the use case, application and resulting value."

Most companies recognize data in the hands of a few data experts can be powerful, but data at the fingertips of many is what will be truly transformational.
-- Brent Dykes, Forbes (2017)

The specific syllabus will be constructed with the student's goals and ambitions in mind.

Extra information

Students need only access to a personal computer with a good internet connection.

Location

Online from Netherlands

About Me

Five things you should know about me:
- I am passionate about all things physics, maths, and tech!
- I am currently a Data Scientist at leading tech firm in Amsterdam.
- After graduating from Royal Holloway, University of London with a First Class Honours degree in Physics, I studied Mathematics at King’s College London.
- I have academic research experience in theoretical statistical mechanics and computational molecular dynamics.
- I have acquired a comprehensive set of computing skills for scientific computing, data analysis, and web development.

Education

Physics BSc / First Class Honours
Royal Holloway, UK | Sep 2013 - Jun 2017
- Developed multiple computing projects with a focus on data analysis and molecular dynamics.
- Exposed to advanced experimental methods in collection of experimental data, evaluating its significance,
drawing relevant conclusions, and calculating the significant statistics.
- Experience in communicating scientific information and producing clear and accurate reports.

Mathematics GradDip
King’s College London, UK | Sep 2017 - Aug 2018
- Developed a robust mathematical foundation for further studies and research in theoretical physics.
- Refined my mathematical intuition to interpret and build models for simple and complex systems.
- The skills acquired are highly transferable to other fields of applied mathematics and statistics.

Experience / Qualifications

Data Scientist
Tiqets | Full-time
As a Data Science Engineer, I am part of Tiqet's core Data Team. I work closely with data scientists, analysts, software engineers, and the Product and Marketing departments. I apply software development, data analytics, and engineering to scale and operationalize data models and make the whole organisation more data-driven.

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

Skills

Python

Software engineering

Computer programming

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

Youssef

4.85

(13)

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

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

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

COURSE OBJECTIVES AND PEDAGOGICAL APPROACH

Resumption and deepening of fundamental concepts through exercises with course reminders.

Put the student in a situation of questioning and research.

Respond to individual issues and questions

Exercise training in order to achieve real mastery of the content.

Learn to build theoretical reasoning from observable facts or hypotheses.

Specific preparation for higher education requirements (in-depth content, increase in work capacity, enrichment of scientific background)

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

Associate professor provides support courses in electrical engineering

Matías

4.85

(13)

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

4.85

(13)

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.

Adam

4.85

(13)

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

Amin

4.85

(13)

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

4.85

(13)

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.

Roger

4.85

(13)

Do you need a boost in mathematics to better understand lessons, pass your exams or prepare for a competition? Do you want to learn to program in C, C++, Python or Java to develop skills sought after in the digital world?
This comprehensive and personalized academic support program is designed to meet your needs and help you succeed!

💡 Why Choose this Program?
This course offers tailor-made support, adapted to your level and your objectives:

🎯 Progress in mathematics by strengthening your foundations and mastering advanced concepts.
💡 Understand theoretical concepts in depth to better apply them in exercises and problems.
💻 Learn to program in C, C++, Python and Java with clear explanations and practical exercises.
🚀 Develop essential skills in algorithms and computer problem solving.
🎓 Effectively prepare for your exams (Bac, Licence, competitive exams) thanks to targeted revisions and practice subjects.
With a caring educational approach, this course helps you gain confidence and achieve your academic goals.

📘 Mathematics – From Secondary to Bachelor
Mathematics is the key to academic success in many scientific and technical fields.
This module covers:

Secondary Level (Middle and High School):

Arithmetic, fractions, percentages, proportionality.
Algebra: Equations, inequalities, functions (linear, quadratic, exponential, logarithmic).
Geometry: Theorems, trigonometry, analytical geometry.
Statistics and probability: Analyze data, calculate probabilities.
Preparation for exams: Brevet, Bac, entrance exams for grandes écoles.
University Level (Bachelor):

Differential and integral calculus: Derivatives, integrals, sequences and series.
Linear Algebra: Matrices, vectors, systems of linear equations.
Advanced Probability and Statistics: Random variables, probability laws, estimation and hypothesis testing.
Numerical analysis: Methods for approximate resolution of equations and systems of equations.
Discrete Mathematics: Graphs, Boolean logic, combinatorics.
This module offers progressive exercises, clear explanations and detailed corrections to understand in depth and train effectively.

💻 Programming – C, C++, Python and Java
Mastering programming is a major asset for success in the digital and technological field.
This module covers the fundamentals of programming to enable you to:

Understand algorithmic logic and computer problem solving.
Master the syntax of the C, C++, Python and Java languages.
Writing your first programs: Variables, conditional structures, loops, functions.
Work on practical projects: Calculator, data management, simple games, sorting and searching algorithms.
Develop advanced skills:
Object-oriented programming (C++, Java): Classes, inheritance, polymorphism.
Memory management (C, C++): Dynamic allocation, pointers.
File manipulation: Reading and writing data.
Data structures: Lists, stacks, queues, binary trees.
Code optimization for faster and more efficient programs.
This module offers concrete examples, practical exercises and motivating projects to help you learn while having fun while developing skills useful in the professional world.

🎯 Interactive and Motivating Teaching
Dynamic online courses: Learn from home in an interactive format with audio and screen sharing.
Tailor-made method: The courses are designed according to your level and your objectives for learning at your own pace.
Practical exercises and concrete projects: To apply theoretical concepts and develop your skills.
Personalized monitoring: Regular support to monitor your progress and adapt the program to your needs.
Encouragement and motivation: A positive approach to building your confidence in your abilities.
🔔 For Who?
This program is aimed at:

High school students wishing to strengthen their foundations in mathematics or learn to program.
University students in science or computer science looking to deepen their knowledge of math and programming.
Candidates for exams and competitions preparing for the Baccalaureate, a License, or entrance exams to the grandes écoles.
Programming enthusiasts wanting to learn the fundamentals of C, C++, Python or Java.
Adults in professional retraining wishing to acquire programming skills.
🚀 Ready to Succeed?
Join the "🎓 Academic Support – 📘 Maths from Secondary to Bachelor & 💻 Programming in C, C++, Python and Java!" and benefit from personalized support to achieve your goals.
Whether you want to improve your grades, pass your exams or develop programming skills, this program will give you knowledge, confidence and motivation.

Register today and take the first step towards success!

Hamza

4.85

(13)

Discover the power of Python with an experienced computer trainer!
I'm Hamza, a passionate developer and seasoned mentor with extensive experience teaching programming. My unique teaching approach will help you quickly acquire solid Python skills while discovering its real-world applications in the professional world.
What you will learn:

Python Fundamentals (variables, control structures, functions)
Advanced Object-Oriented Programming
Data Analysis and Visualization with Pandas and Matplotlib
Developing graphical interfaces with PyQt
Practical projects inspired by real business cases

Why choose me?

Over 10 years of experience in training and mentoring
Teaching method adapted to all levels
Hands-on approach based on concrete projects
Contagious passion for code and technological innovation

Whether you're a beginner looking to get started in programming or a professional looking to improve your skills, this course will open up exciting new opportunities in the world of software development and data science.
Join me for a captivating journey into the heart of the most versatile and in-demand programming language on the market!
Book now and take the first step towards mastering Python. Your career as a Python developer starts here!

Mariem

4.85

(13)

Understanding algorithms is essential for anyone pursuing computer science or programming. In this course, I provide a structured approach to learning algorithms—from fundamental concepts like sorting and searching to advanced techniques such as dynamic programming and graph theory. Whether you're preparing for exams, coding interviews, or aiming to improve your problem-solving skills, this course is designed to build strong algorithmic thinking. Through practical examples and step-by-step explanations, I help students master the logic and techniques needed to write efficient and elegant code.

Wissem

4.85

(13)

I teach coding to beginners and intermediate students.
Lessons focus on logic, basic programming, and practical exercises.
Classes are adapted to the student’s pace.
Students can choose between website or mobile app development.Hands on dev

Ammar

4.85

(13)

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.

Baia

4.85

(13)

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

Azhar

4.85

(13)

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

4.85

(13)

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

4.85

(13)

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.