Introduction to Python for Quantitative finance and investing

From 42 £ /h

Python is one of the most powerful programming/scripting tools of our times. However, learning from textbooks or online can become time consuming and inefficient, since we easily lose focus. In this class, we learn by doing. As you learn new techniques and concepts, you will immediately use them to build tools that will help you become a data-driven and informed investor or trader. At the end of the class, you are left with a basic understanding of what python can do, but also with a template code that you can later use to build you own strategies on top.

The class in a nutshell:

(1) How to extract market data with python, such as: OHLC quotes, volume, dividend history, financial history etc.
(2) How to store and handle data efficiently.
(3) How to build and group your own portfolio based on any custom metric (e.g. P/E ratio, Debt/Equity ratio, dividend etc)
(4) How to build future paths of a stock in our portfolio, via Monte Carlo simulations, based on your own beliefs (e.g. optimistic/pessimistic).

Extra information

A laptop with a connection to the internet is required. The rest can be worked out.

Location

Online from Netherlands

About Me

I come from Greece, but I moved in the Netherlands more than five years ago where I studied and obtained my PhD in High Energy Astrophysics. Since then, I have been working as a quantitative analyst for a big bank in the Netherlands. I have ample experience in building algorithms and quantitative tools for trading and investing using python. My main focus is derivative (option) trading and valuation, but that is a long discussion.The environment in my classes is very friendly and not formal at all, and I always welcome a nice conversation about the financial markets, philosophy or life in general.

Education

BSc, Physics ( Aristotle University of Thessaloniki, Greece)
MSc, Computational Physics ( Aristotle University of Thessaloniki, Greece)
PhD, Computational Astrophysics (University of Groningen & University of Southampton)

Experience / Qualifications

Blockchain application developer ( IT ), Groningen, the Netherlands
Quantitative analyst ( IT, Banking) , Utrecht, the Netherlands

Age

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Duration

60 minutes

The class is taught in

English

Greek

Skills

Finance

Investing

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

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.

Mohamed

4.88

(85)

This comprehensive course is designed to take absolute beginners with no prior coding experience to confident Python programmers. Through hands-on projects, real-world examples, and interactive exercises, students will master Python fundamentals and apply them to build applications, automate tasks, analyze data, and even explore game development.

What You’ll Learn:
🐍 Python Basics:

Syntax, variables, data types, and operators
Input/output, loops (for, while), and conditionals (if-else)

📚 Core Programming Concepts:

Functions, modules, and error handling
Lists, tuples, dictionaries, and sets

🎮 Real-World Applications:

File handling (read/write files)
Web scraping (intro to BeautifulSoup/Requests)
Basic game development (with Pygame)

🔢 Next-Level Skills (Towards "Hero" Level):

Object-Oriented Programming (OOP) – Classes & Objects
Working with APIs (fetching data from the web
Intro to data analysis (Pandas & Matplotlib basics)
Mini-capstone project to showcase skills

Giuliano

4.88

(85)

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!

Georgio

4.88

(85)

With experience in surgical precision

📈 Private Trading Lessons – CFDs on Stocks & Stock Indices 📉

Do you want to learn how to trade the financial markets seriously and develop a real investment strategy?
I offer personalized courses adapted to your level, from beginner to more experienced trader.

🎯 Proposed program:

Understanding and using the TradingView platform

Basics and improvement of Price Action

ICT & Smart Money Concepts (SMC) methodologies

Analysis via Volume Profile and Liquidity Zones

Reading chart patterns and market structures

Risk Management and Trading Psychology

Application on CFDs on Shares and Stock Indices

✅ Objective: to make you independent in your analysis and decision-making, by developing a rigorous and professional approach with the aim of becoming profitable and profitable.

👨‍🏫 Format:

Online courses (video conferencing, screen sharing, live case studies)

Step-by-step monitoring and support

📩 Contact me now for more information or to book an initial discovery session.

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.

Amine

4.88

(85)

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.

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.

Kevin

4.88

(85)

► EXPERT BUSINESS, ACCOUNTING, FINANCE & ECONOMICS TUTOR FROM SWITZERLAND
► IB, A-LEVEL, IGCSE & INTERNATIONAL SCHOOL SUPPORT

I completed my Master’s degree in Business Information Systems at a Swiss University of Applied Sciences, where my academic background strongly combined business, finance, economics, mathematics, analytical thinking and problem-solving. This technical and business-oriented foundation shaped the way I teach today: clearly, logically and with a strong focus on real understanding.

For many years, I have successfully supported students in Business Studies, Accounting, Finance and Economics. As a tutor from Switzerland, I bring a structured, patient and highly individual teaching style to students who want to improve their grades, prepare for important exams and build real confidence in business-related subjects.

My lessons are designed for students who want more than just memorizing definitions and formulas. I focus on understanding business concepts, applying financial logic, interpreting economic relationships and solving accounting problems step by step.

► EXAM PREPARATION & ACADEMIC SUPPORT

► IGCSE BUSINESS, ACCOUNTING & ECONOMICS
I help students build a strong foundation in business concepts, financial calculations and economic thinking. My lessons include clear theory explanations, topic-by-topic revision and exam-style practice to prepare students confidently for their assessments.

► A-LEVEL BUSINESS, ACCOUNTING, ECONOMICS & FINANCE
A-Level subjects require strong analytical thinking, clear written arguments and confident application of theory to real business situations. I support students with structured revision, essay technique, calculation practice, case-study analysis and preparation for demanding exams.

► INTERNATIONAL BACCALAUREATE — IB BUSINESS MANAGEMENT & ECONOMICS
I provide structured support for IB students, focusing on deep understanding, strong terminology, analytical writing and exam technique. Students learn how to explain concepts clearly, analyse case studies, evaluate decisions and structure high-quality answers.

► INTERNATIONAL SCHOOL PROGRAMMES
I support students following international, bilingual and private school curricula in Business Studies, Economics, Accounting, Finance, Commerce and Management. Since every school can have different expectations, I adapt my teaching to the student’s syllabus, textbook, teacher requirements and exam format.

► UNIVERSITY & FOUNDATION COURSES
For older students, I offer support in Accounting, Corporate Finance, Economics, Business Administration, Financial Management, Statistics and quantitative business modules. I help students understand difficult theory, solve assignments, prepare for exams and develop strong analytical skills.

► HOW I TEACH

► I FOCUS ON REAL UNDERSTANDING, NOT MEMORISATION.
I explain business, accounting and economic concepts step by step so students understand the logic behind the theory and can apply it confidently in exams.

► I CONNECT THEORY WITH REAL BUSINESS EXAMPLES.
Business and economics become easier when students can see how concepts work in real life. I use practical examples to make topics clear, relevant and memorable.

► I SIMPLIFY COMPLEX CALCULATIONS.
In Accounting and Finance, I break calculations into clear steps so students understand what is given, which formula is needed and how to reach the final answer correctly.

► I TRAIN EXAM TECHNIQUE CAREFULLY.
Students learn how to structure answers, use key terminology, analyse case studies, justify decisions and manage time under exam conditions.

► I ADAPT EVERY LESSON TO THE STUDENT.
Every student learns differently, so I adjust my explanations, pace, examples and practice questions to match the student’s exact level and goals.

► YEARS OF EXPERIENCE WITH IB, A-LEVEL, IGCSE & INTERNATIONAL SCHOOL STUDENTS

Over the years, I have successfully supported students from prestigious schools and demanding academic programmes, helping them strengthen their understanding, master exam techniques and achieve excellent progress in Business Studies, Accounting, Finance and Economics.

► ONLINE LESSONS

► Interactive whiteboard
► Clear digital notes
► Personalised exercises
► Exam-style practice
► Flexible lesson structure
► Focused one-to-one support from Switzerland

Online lessons are structured, personal and highly effective. Students can ask questions directly, follow every step in real time and review the materials after the lesson.

► MY GOAL

My goal is not only to improve grades, but to help students become confident, independent and analytical thinkers. With the right guidance, Business, Accounting, Finance and Economics become logical, practical and much easier to master.

► SUBJECTS: Business Studies, Accounting, Finance, Economics, Business Administration, Management
► LEVELS: IGCSE, A-Level, IB, International School, Foundation Courses, University Modules
► FORMAT: Online tutoring from Switzerland
► FOCUS: Deep understanding, exam confidence, analytical thinking and long-term academic success.

Yomna

4.88

(85)

This course is designed to introduce students aged 7 to 16 to the world of programming through two of the most widely used and industry-relevant languages: C++ and Python.

The class provides a structured, age-appropriate pathway into programming, whether the student is a complete beginner or already exploring coding through platforms like Scratch or Code.org. Emphasis is placed on understanding logic, building problem-solving skills, and writing real code in a supportive, project-based environment.

Taught by an engineering student with hands-on experience in both C++ and Python, this course empowers students to explore the power of code and build a strong foundation in computational thinking — essential for future studies in engineering, robotics, AI, or game development.

Léo

4.88

(85)

• Teaching methodology and techniques: I favour a personalized approach, adapting the courses according to the profile and academic background of each student.
• Typical course structure: tutoring in economics, econometrics, statistics and probability, financial mathematics, trading, investment, or political economy. Courses can take place at home, via videoconference, or at a pre-selected location, ideally quiet, free, and conducive to learning.
• Specifics as a teacher: I offer support throughout the school year, with free corrections of exercises outside of class, regular availability, and the guarantee of being accessible until the end of the year, subject to the general conditions of Superprof.
• Target audience: all levels, regardless of diploma, class or specific characteristics.
-------
The path and the method are in there; take a little bit of each.

Holding a degree in mathematics from EPFL, I offer private lessons in Geneva or online.

I graduated from EPFL with a degree in mathematics, having completed all the Bachelor's level courses in this discipline. I have gained significant experience tutoring students from middle school to university level (mathematics and physics). I have also assisted with teaching at EPFL, particularly in specialized courses such as analytic geometry (advanced mathematics course), analysis (first and second year Bachelor's level), and linear algebra (first year Bachelor's level). My in-depth mastery of the theory in these disciplines provides me with the skills and teaching abilities necessary to effectively support high school and university students, helping them understand the theoretical concepts in their courses and apply them practically in their exercises.

Typical course: a quick review (adapted to needs) of the essential concepts of the course, followed by practical exercises and oral role-playing (going to the board, discussion on the physical meaning, etc.), as in a competitive oral exam.

All my lessons are prepared in advance based on the topics covered in class (the student specifies their needs from one session to the next). I also create a handout containing sample exercises illustrating different methods, fully corrected and explained by me.

My commitment to my students' success is absolute. I only prioritize motivated students who are ready to put in the necessary effort to progress.

My main focus is on in-depth understanding and the quality of work. Depending on the student's request, I can also suggest exercises to do between sessions (not mandatory, depending on available time and homework already assigned by their school).

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

-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
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.

Jude

4.88

(85)

My lessons are designed to take you from simply following code to genuinely understanding how data science works.

We can cover the complete data science process, including data cleaning, exploratory data analysis, feature engineering, visualisation, statistics, machine learning, model evaluation and communicating results.

Depending on your goals, lessons can include:

Python, pandas, NumPy and scikit-learn
Data cleaning and exploratory analysis
Regression and classification
Decision trees, random forests and boosting
Clustering and dimensionality reduction
Cross-validation and model evaluation
Feature engineering and model interpretation
Neural networks and deep learning foundations
Bayesian modelling and PyMC
Portfolio and interview preparation
Support understanding university modules and projects

I use diagrams, analogies and practical demonstrations to make difficult ideas easier to understand. We will normally begin with an intuitive explanation, look at the underlying logic or mathematics, and then implement the concept in Python.

Lessons are personalised around your level. Complete beginners receive a structured learning path, while experienced students can focus on advanced topics, project guidance, debugging or interview preparation.

You will be encouraged to explain ideas back to me, interpret results and make your own modelling decisions. My goal is not only to help you produce working code, but to help you become an independent and confident data scientist.

Baia

4.88

(85)

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

Fatima

4.88

(85)

Teaching python to beginners!

In these classes, you will learn the basics of python programming, functions, lists, sets, and much more with practice assignments and assessments...

I have experience in teaching python to university peers.