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This teacher has a fast response time and rate, demonstrating a high quality of service to their students.
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Since March 2023
Instructor since March 2023
Linux, Bash , Python Programming Beginner Class : 101
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From 22 C$ /h
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Python is a popular programming language known for its simplicity and ease of use. This beginner course is designed to provide a solid foundation in Python programming for those who are new to programming or have some programming experience but are new to Python.
The course is series of lectures that cover a wide range of topics, including Python syntax, data types, loops, functions, modules, and object-oriented programming. You'll start by learning the basics of Python syntax, including how to write basic programs, work with variables, and control flow. You'll then move on to more advanced topics like functions and modules, which are key building blocks in any Python program.
One of the key features of Python is its extensive library of modules and packages. You'll also learn how to work with files, handle exceptions, and debug your code.
Another important aspect of programming is understanding how to work with data. This course covers several data types in Python, including strings, lists, dictionaries, and sets. You'll learn how to manipulate these data types using built-in functions and operators, and you'll also learn how to create your own functions to manipulate data.
By the end of the course, you'll have a good understanding of how to use Python to create basic programs and applications, and you'll be well on your way to becoming a proficient Python programmer.
Location
location type icon
Online from India
About Me
I am experienced professional in the IT industry, close to two decades now. I have worked on the Network Automation, Telecom and Embedded System domains.
As an experienced coder and programmer with a passion for education, I have taught colleagues and students on the latest technology in the programming and automation areas.
My expertise in various programming languages, such as Python, Bash , Linux coupled with my ability to simplify complex concepts, I can teach you how to program and automate things which can make your work and life better.
In addition, I have several years of teaching experience in different formats, including online courses, boot camps, and workshops. I have developed a unique teaching approach that focuses on hands-on, project-based learning to ensure that students not only understand the theory but also know how to apply it in practical scenarios.
My teaching style is tailored to individual student needs and learning styles, and I believe in creating an inclusive and supportive learning environment that encourages creativity, innovation, and critical thinking.
Finally, I am committed to staying up-to-date with the latest trends and technologies in the programming industry, which ensures that my teaching is always relevant and engaging. I am eager to bring my expertise, passion, and teaching skills to your institution and help your students become proficient coders and programmers.
Education
I have a Bachelors in Electronics and Communication Engineering. I have done Embedded system course and Networking with Linux Course.
I have completed AWS cloud practioneer course.
Experience / Qualifications
I have 20 years of experience in the industry and have spent majority time on Network and Telecom industry. I can teach topics related to networking , python , automation , Network Analysis , wireshark , AWS , Scratch and Raspberry Pi topics
Age
Children (7-12 years old)
Teenagers (13-17 years old)
Adults (18-64 years old)
Seniors (65+ years old)
Student level
Beginner
Duration
60 minutes
The class is taught in
English
Tamil
Kannada
Telugu
Reviews
Availability of a typical week
(GMT -05:00)
Chicago
at teacher icon
Online via webcam
Mon
Tue
Wed
Thu
Fri
Sat
Sun
00-04
04-08
08-12
12-16
16-20
20-24
In a Wireshark class, students will learn the fundamentals of using Wireshark for packet analysis and network troubleshooting. The class typically covers the following topics:

1. Introduction to Packet Analysis:
- Understanding the importance of packet analysis in network troubleshooting and security.
- Overview of network protocols and their role in packet communication.

2. Wireshark Installation and Setup:
- Downloading and installing Wireshark on different operating systems.
- Granting necessary permissions for packet capture.

3. Capturing Packets:
- Selecting the appropriate network interface for capturing packets.
- Starting and stopping packet capture.
- Configuring capture options, such as promiscuous mode and packet filters.

4. Navigating the Wireshark Interface:
- Familiarizing with the main components of the Wireshark window.
- Understanding the packet list pane and its columns.
- Exploring the packet details pane and various protocol layers.

5. Filtering and Display Options:
- Using display filters to focus on specific packets of interest.
- Applying filters based on protocols, IP addresses, ports, and other packet attributes.
- Customizing column display and packet summary information.

6. Analyzing Packet Details:
- Understanding the structure of a packet, including Ethernet, IP, TCP/UDP, and application layers.
- Examining packet headers and payload.
- Interpreting key fields, flags, and protocol-specific information.

7. Following Streams and Conversations:
- Identifying and tracking network streams.
- Following TCP/UDP streams to analyze complete conversations.
- Extracting files and media from captured packets.


Throughout the class, students will gain hands-on experience by working with Wireshark in practical exercises and case studies. They will develop the skills necessary to efficiently capture, analyze, and interpret network packets using Wireshark, enabling them to troubleshoot network issues effectively and ensure network security.
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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.
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Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
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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
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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!
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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.
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Do you want to learn programming but don't know where to start? Are you a beginner looking for clear explanations, or do you want to improve your coding skills with personalized support?

This private tutoring program is designed to help you master Python, one of the most versatile and easy-to-learn programming languages. Through a step-by-step approach, interactive exercises, and hands-on projects, you'll gain the confidence and skills to write code effectively and solve real-world problems.

💡 Why Choose this Program?
With these personalized courses, you will:
-
🚀 Learn at your own pace – Whether you’re a complete beginner or want to refine your skills, lessons adapt to your level.
🎯 Master the fundamentals – Understand key concepts like variables, loops, functions, and object-oriented programming.
🏗️ Complete hands-on projects – Work on real-world coding exercises, from simple scripts to mini-apps.
🐍 Develop problem-solving skills – Learn how to break down complex tasks and write efficient code.
🎓 Prepare for exams, jobs or personal projects – Whether you are a student, professional or enthusiast, Python is an essential skill.
💻 Get live support – Get real-time feedback, coding tips, and answers to your questions.
This interactive, hands-on learning experience ensures you understand Python while having fun coding!

📚 What Will You Learn?
This program covers everything you need to become comfortable with programming in Python:

✅ Python Basics (Great for Beginners)
Introduction to Python and installation of the development environment 🖥️
Variables, data types and user input 🔢
Operators and expressions 🧮
Conditional structures (if-else) and loops (for, while) 🔄
Writing and calling functions 🏗️
🚀 Intermediate Concepts (To Go Further)
Lists, Tuples, Dictionaries – Understanding Data Structures 📊
File Management – Reading and Writing Files 📄
Exception Handling – Making Your Code More Robust ⚠️
Introduction to modules and libraries 🏛️
🎯 Advanced Concepts (For the More Ambitious)
Object-Oriented Programming (OOP) – Classes, Objects, Inheritance 🏗️
Recursion and algorithm design 🧠
API and Web – Connecting Python to the web 🌐
Introduction to Databases – Storing and Retrieving Data 🗄️
🎨 Practical Projects & Applications
Creating simple games 🎮
Automation of repetitive tasks 🔄
Data analysis with pandas 📊
Web scraping and working with APIs 🌍
Introduction to Artificial Intelligence and Machine Learning 🤖 (optional for advanced learners)
🎯 An Interactive and Fun Learning Experience
Live Online Classes – Learn from home with interactive sessions via screen sharing.
Tailor-made lessons – Content adapts to your level for an effective and personalized learning journey.
Practical exercises and projects – Less theory, more practice! Learn with real-world examples.
Caring and motivating environment – No pressure, no judgment: progress at your own pace.
Practical application – Each concept learned is applied immediately through exercises and mini-projects.
🔔 For Who?
This program is ideal for:
✅ Complete beginners – If you’ve never written a line of code, no worries! The lessons start from scratch.
✅ Students – To prepare for programming courses, computer science exams or competitions.
✅ Self-taught – If you want to add Python to your skillset, this course offers you structured support.
✅ Professionals and people in retraining – Python is a sought-after skill in data science, automation and web development.
✅ Tech Enthusiasts – Curious to learn code? This course makes learning Python both fun and useful.

🚀 Ready to Embark on Your Python Adventure?
Join the "🐍 Personalized Private Lessons – 💻 Learn to Code and Program in Python!"
Gain the skills and confidence to write clean, efficient, and powerful code.

Sign up today and take your first steps into the exciting world of Python programming! 🔥
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Learn Physics and Mathematics with a PhD physicist from ITA who is currently completing his third postdoctoral research appointment and has more than 15 years of teaching experience. Lessons can cover Physics, Mathematics, Calculus, Linear Algebra, Statistics and Python. I adapt the content and pace to each learner, whether the goal is to strengthen foundations, understand a difficult university topic, improve problem-solving skills, prepare for an assessment, or use mathematical and computational tools in scientific work. Lessons are available in native Portuguese or professional English for learners aged 16 to 65. My approach combines conceptual clarity, step-by-step reasoning, worked examples and guided practice so students learn to solve problems independently.
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Learn Python by actually building things.

Whether you're starting from scratch, studying computer science, or already know the basics and want to become more confident, I'll help you learn Python through practical exercises and real projects.

We can work on:

• Python fundamentals
• Variables, conditions, loops and functions
• Lists, dictionaries and object-oriented programming
• Working with files and APIs
• Automation and useful scripts
• Debugging and understanding existing code
• Building small projects for your portfolio
• Introduction to AWS and cloud projects

I adapt the lessons to your current level and goals. You can also bring your own exercises, university assignments or personal projects and we can work through them together.

The goal isn't just to memorize Python syntax — it's to understand how to use it to solve real problems.
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Similar classes
arrow icon previousarrow icon next
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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.
verified badge
Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.
verified badge
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
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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!
verified badge
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.
verified badge
Do you want to learn programming but don't know where to start? Are you a beginner looking for clear explanations, or do you want to improve your coding skills with personalized support?

This private tutoring program is designed to help you master Python, one of the most versatile and easy-to-learn programming languages. Through a step-by-step approach, interactive exercises, and hands-on projects, you'll gain the confidence and skills to write code effectively and solve real-world problems.

💡 Why Choose this Program?
With these personalized courses, you will:
-
🚀 Learn at your own pace – Whether you’re a complete beginner or want to refine your skills, lessons adapt to your level.
🎯 Master the fundamentals – Understand key concepts like variables, loops, functions, and object-oriented programming.
🏗️ Complete hands-on projects – Work on real-world coding exercises, from simple scripts to mini-apps.
🐍 Develop problem-solving skills – Learn how to break down complex tasks and write efficient code.
🎓 Prepare for exams, jobs or personal projects – Whether you are a student, professional or enthusiast, Python is an essential skill.
💻 Get live support – Get real-time feedback, coding tips, and answers to your questions.
This interactive, hands-on learning experience ensures you understand Python while having fun coding!

📚 What Will You Learn?
This program covers everything you need to become comfortable with programming in Python:

✅ Python Basics (Great for Beginners)
Introduction to Python and installation of the development environment 🖥️
Variables, data types and user input 🔢
Operators and expressions 🧮
Conditional structures (if-else) and loops (for, while) 🔄
Writing and calling functions 🏗️
🚀 Intermediate Concepts (To Go Further)
Lists, Tuples, Dictionaries – Understanding Data Structures 📊
File Management – Reading and Writing Files 📄
Exception Handling – Making Your Code More Robust ⚠️
Introduction to modules and libraries 🏛️
🎯 Advanced Concepts (For the More Ambitious)
Object-Oriented Programming (OOP) – Classes, Objects, Inheritance 🏗️
Recursion and algorithm design 🧠
API and Web – Connecting Python to the web 🌐
Introduction to Databases – Storing and Retrieving Data 🗄️
🎨 Practical Projects & Applications
Creating simple games 🎮
Automation of repetitive tasks 🔄
Data analysis with pandas 📊
Web scraping and working with APIs 🌍
Introduction to Artificial Intelligence and Machine Learning 🤖 (optional for advanced learners)
🎯 An Interactive and Fun Learning Experience
Live Online Classes – Learn from home with interactive sessions via screen sharing.
Tailor-made lessons – Content adapts to your level for an effective and personalized learning journey.
Practical exercises and projects – Less theory, more practice! Learn with real-world examples.
Caring and motivating environment – No pressure, no judgment: progress at your own pace.
Practical application – Each concept learned is applied immediately through exercises and mini-projects.
🔔 For Who?
This program is ideal for:
✅ Complete beginners – If you’ve never written a line of code, no worries! The lessons start from scratch.
✅ Students – To prepare for programming courses, computer science exams or competitions.
✅ Self-taught – If you want to add Python to your skillset, this course offers you structured support.
✅ Professionals and people in retraining – Python is a sought-after skill in data science, automation and web development.
✅ Tech Enthusiasts – Curious to learn code? This course makes learning Python both fun and useful.

🚀 Ready to Embark on Your Python Adventure?
Join the "🐍 Personalized Private Lessons – 💻 Learn to Code and Program in Python!"
Gain the skills and confidence to write clean, efficient, and powerful code.

Sign up today and take your first steps into the exciting world of Python programming! 🔥
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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Learn Physics and Mathematics with a PhD physicist from ITA who is currently completing his third postdoctoral research appointment and has more than 15 years of teaching experience. Lessons can cover Physics, Mathematics, Calculus, Linear Algebra, Statistics and Python. I adapt the content and pace to each learner, whether the goal is to strengthen foundations, understand a difficult university topic, improve problem-solving skills, prepare for an assessment, or use mathematical and computational tools in scientific work. Lessons are available in native Portuguese or professional English for learners aged 16 to 65. My approach combines conceptual clarity, step-by-step reasoning, worked examples and guided practice so students learn to solve problems independently.
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Learn Python by actually building things.

Whether you're starting from scratch, studying computer science, or already know the basics and want to become more confident, I'll help you learn Python through practical exercises and real projects.

We can work on:

• Python fundamentals
• Variables, conditions, loops and functions
• Lists, dictionaries and object-oriented programming
• Working with files and APIs
• Automation and useful scripts
• Debugging and understanding existing code
• Building small projects for your portfolio
• Introduction to AWS and cloud projects

I adapt the lessons to your current level and goals. You can also bring your own exercises, university assignments or personal projects and we can work through them together.

The goal isn't just to memorize Python syntax — it's to understand how to use it to solve real problems.
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