Learn and Master Data Science from Scratch with Python

From 22 £ /h

Learn Data Science from Scratch with Python

I am a graduate of the University of Westminster, where I began my journey into data science and machine learning through hands-on data analysis for physical and mathematical models. With over 16 years of experience teaching computer science and programming, I have developed a comprehensive approach to teaching data science that emphasizes practical application and project-based learning.

My lessons are tailored to suit both complete beginners and those who wish to deepen their understanding of data science and machine learning. Each session is designed to help you not just learn, but apply data science concepts effectively to real-world projects.

What I Offer:

Project-based learning: Engage in practical projects that will enhance your understanding of machine learning and data science. Examples of projects include:

- Predictive Modeling: Create a model to predict house prices, stock market trends, or sales forecasts using regression techniques.
- Data Classification: Build a spam email classifier, sentiment analysis tool, or an image recognition application.
- Clustering Algorithms: Apply clustering techniques to segment customer data for targeted marketing or identify groups within a dataset.
- Time Series Analysis: Forecast future trends using time series data, such as weather patterns or economic indicators.
- Recommendation Systems: Develop a movie or product recommendation engine using collaborative filtering techniques.

Customized lessons: Each lesson is tailored to your current skill level and goals. Whether you are starting from scratch or looking to fine-tune your expertise in Python, TensorFlow, scikit-learn, or other machine learning libraries, I adjust the content to match your needs.

Comprehensive ML pipeline training: Gain an in-depth understanding of the complete data science pipeline, including data collection, cleaning, feature engineering, model training, evaluation, and deployment.

Portfolio and project support: Receive guidance on developing projects that showcase your skills, whether for your personal portfolio or as part of a bootcamp assignment. I will help you ensure your projects are both functional and impactful.

Pre-class materials and homework: Access study materials prior to each session and complete follow-up assignments to consolidate what you’ve learned and apply it independently.

Flexible online lessons: Learn from the comfort of your home with lessons that fit your schedule.

My teaching approach focuses on fostering critical thinking and problem-solving skills that are essential for a successful career in data science. I have collaborated with companies, start-ups, and educational institutions, bringing practical, hands-on knowledge to students and professionals looking to excel in the field.

If you are ready to build a strong foundation in data science and gain the practical experience needed to excel in real-world scenarios, contact me to discuss your learning path and project ideas.

Location

Online from United Kingdom

About Me

I am a graduate of the University of Westminster, since then working as a freelancer in Data Management, Machine Learning and Online Security. I believe only creating secure and reliable applications can lead to success in your projects.

My passion naturally led me to applying mathematical and physical principles to real-world problems through data science, machine learning, and programming projects.

With over 16 years of teaching experience, I have worked with students of all ages, helping them unlock their potential in subjects ranging from mathematics and physics to computer science and programming. My tutoring is project-based, meaning that I help students learn by doing – whether it’s building a Python application, exploring databases, or tackling complex mathematical concepts.

I’m committed to helping my students understand not just the "how," but also the "why" behind the concepts they are learning. I tailor each lesson to the student's learning style, ensuring a clear and engaging experience. My goal is to foster a love of learning, problem-solving, and critical thinking in every student I teach.

Education

Python for Data Science Certificate from MiT
Python in Cybersecurity Certificate from MiT
Web Applications with JavaScript Certificate from MiT

Westminster University
London, United Kingdom
Masters Degree

Experience / Qualifications

18 years of experience
Python for Data Science
Python in Cybersecurity
Web Applications
Django
Flask
SQL
noSQL
Node.js
Pandas
Numpy

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

45 minutes

60 minutes

90 minutes

120 minutes

The class is taught in

English

Polish

French

Skills

Python

Computer programming

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

Master Databases through Practical Projects – Experienced Tutor with 16 Years of Teaching Experience

17 £ /h

As a graduate of the University of Westminster, I began my programming journey by applying my skills to data management and analysis in various projects. Over the past 16 years, I have been providing private lessons in computer science, with a strong focus on teaching databases to students and professionals alike.

Whether you're a beginner learning about SQL or a more advanced learner seeking to optimize database performance, I offer tailored lessons designed to help you understand and apply database concepts in real-world scenarios.

What I Offer:
Learn databases through hands-on projects: You'll develop a deep understanding of relational databases (SQL), non-relational databases (NoSQL), and data modeling by working on real-world projects.
Customized lessons: Each lesson is adapted to your learning style and current level, whether you’re just starting or need to refine your skills.
Portfolio and project support: Need help building a database project for your portfolio or finalizing a boot camp assignment? I provide guidance to ensure your project is both functional and impressive.
Database optimization: Learn how to optimize queries, structure your data efficiently, and improve database performance.
Study materials and exercises: Before each session, you'll receive all necessary materials to prepare for the next lesson, followed by homework assignments to reinforce the concepts covered.
Flexible online lessons: Access lessons from anywhere, on a schedule that suits you.
I currently work as a freelancer with companies, start-ups, and schools, offering online lessons and project support in database management.

Ready to Dive into Databases?
If you're interested in mastering databases through practical, real-world projects, or if you have any questions, don't hesitate to reach out. Let's build your database skills together!

This ad emphasizes practical learning in databases, tailored for students and professionals looking to enhance their skills through real-world projects. Let me know if you'd like any further refinements!

Python Learning through Practical Projects - Tutor with 16 Years of Teaching Experience

25 £ /h

I am a freelancer who graduated from the University of Westminster, where I began my journey into programming. During my studies, I started applying programming skills to solve physical and mathematical problems. Since then, I’ve developed a passion for continuous learning and have expanded my expertise in data implementation and software development.

For the past 16 years, I have been offering private programming lessons, helping students of all ages and backgrounds, from beginners to advanced learners. Whether you're a student looking to build a project portfolio, prepare for an exam, or a professional aiming to learn Python through practical applications, I can help you reach your goals.

What I Offer:
Learn Python by building projects: From the basics to more advanced concepts, you will learn programming through hands-on experience, working on real-world projects that solidify your understanding.
Customized lessons: I tailor each lesson to your learning style and needs, whether you're just starting out or looking to deepen your skills.
Project support: Whether you're working on a portfolio, completing a boot camp project, or preparing for an exam, I offer guidance and assistance to help you succeed.
Step-by-step approach: Before each lesson, you'll receive study materials and exercises designed to help you grasp the concepts we’ll cover. Afterward, you'll receive homework to reinforce what you've learned.
Flexible online lessons: Learn from the comfort of your home with flexible scheduling.
I currently work as a freelancer, collaborating with companies, startups, and schools to deliver online programming classes.

If you’re eager to learn Python in a practical, engaging way, or if you have any questions, feel free to send me a message - I will surely reply.

Thank you,
Alex

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

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

Enrique

4.85

(13)

Don't settle for anything less than excellence.
I am an Aerospace Engineer with a Master's degree in Quantum Physics and have completed Ph.D. work at the University of Cambridge in Computational Physics. Additionally, I have 4 years of experience developing MATLAB and possess deep programming skills in MATLAB/Simulink family, C/C++, Fortran, and Python.

With over 12 years of tutoring experience, I have successfully guided more than 50 students worldwide to achieve distinction in various fields. Consistent results are my priority, and I strive for excellence in all aspects of my teaching.

My lessons are customized to meet each student's unique needs and are designed to be engaging and insightful.

Whether you are at a school level or require advanced or professional-level instruction, I offer support in the following areas:
- Preparation for IB/IA, A-Levels, GCSE, University Entry, or equivalent.
- Experience in preparing students to access world-class schools and universities, including Cambridge University, Oxford, Ivy League and other top institutions in the UK and US.
- University levels (undergraduate and postgraduate).
- High school studies and diploma programs.
- Assistance with specific projects at a professional level, including job interview preparation.
- Extensive experience working with children.

Every lesson is meticulously planned in advance to ensure that it aligns with your goals and targets areas for improvement.
I prioritize a dynamic and interactive learning experience, with one-on-one sessions tailored to your individual requirements. Lessons will be conducted via webcam, enabling you to connect from anywhere.

I have a highly flexible schedule and can adapt to accommodate your needs.
If you have any questions about my teaching method, availability, or pricing, please don't hesitate to reach out. I am here to assist you and provide the support you need.

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.

Vikash

4.85

(13)

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.

Baia

4.85

(13)

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

4.85

(13)

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.

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.

Amr

4.85

(13)

# **Master C/C++: Build the Foundation of Modern Software Development**

Unlock the power of one of the most influential programming languages in computing history! Whether you're an absolute beginner or looking to deepen your expertise, this comprehensive C/C++ course delivers structured learning from fundamentals to advanced concepts that power operating systems, game engines, and high-performance applications.

## **Why Choose This C/C++ Program?**

**Industry-Relevant Curriculum:** Learn expert guidance on the design of effective classes, functions, templates, and inheritance patterns that form the backbone of professional C++ development. Move beyond basic syntax to understand how to write clean, efficient, and maintainable code that stands the test of time.

**Templates & Generic Programming Mastery:** Go beyond introductory material with in-depth coverage of templates—the cornerstone of modern C++—enabling you to create robust, reusable code components that work across multiple data types. Discover how function templates, class templates, and variadic templates work to maximize your coding efficiency.

**Practical, Hands-On Approach:** This isn't just theory! You'll build real-world projects that demonstrate memory management, object-oriented programming, and system-level programming techniques used in today's technology landscape.

## **Your Learning Journey**

Our structured path takes you from writing your first "Hello World" program through advanced template metaprogramming, with special attention to modern C++ standards (up to C++20). You'll gain the confidence to tackle complex programming challenges and understand the "why" behind effective C++ practices—not just the "how."

## **Transform Your Career Today**

C/C++ skills remain in high demand across industries from finance to gaming to IoT. By mastering these foundational languages, you'll develop problem-solving abilities that translate to any programming environment.

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

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

منال

4.85

(13)

📊Microsoft Office: To establish your office skills, manage data via Excel, write professional reports with Word, and prepare impressive presentations with PowerPoint.

📐 AutoCAD: To learn engineering drawing and design two-dimensional and three-dimensional plans with high accuracy and speed.

🛣️ Civil 3D: To learn road design, network design, surveying, and quantity surveying in a scientific and practical way

Tabitha

4.85

(13)

Have you ever wanted to learn how websites are created but didn’t know where to start? This class is designed for complete beginners who want to learn web development in a simple, practical and enjoyable way.

I will guide you step by step through the fundamentals of HTML, CSS and JavaScript, helping you understand how websites are structured, styled and made interactive.

In this class, you will learn how to:

- Understand the basics of web development and how websites work
- Use HTML to create the structure of a webpage.
- Use CSS to add colours, layouts, fonts and styles.
- Get started with JavaScript and understand basic website interactivity.
- Write and organise simple code.
- Build your first basic webpage through practical exercises.

No previous coding experience is required. We will learn at your pace, with clear explanations, hands on practice and time to ask questions.

My goal is to help you build a strong foundation in web development and gain the confidence to continue learning and creating your own websites.

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

Aditya

4.85

(13)

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.