Machine Learning with Python and PyTorch: Practical Hands-on Training

From 24 € /h

Welcome to "Machine Learning with Python and PyTorch: Practical Hands-on Training," a beginner-friendly course designed to introduce you to the exciting world of machine learning using two of the most popular tools in the industry: Python and PyTorch. This course focuses on practical, hands-on learning, ensuring you gain the skills needed to start building your own machine learning models.

#### Course Objectives:
- **Introduction to Machine Learning:** Understand the basic concepts and principles of machine learning.
- **Python Programming for Machine Learning:** Learn Python programming essentials tailored for machine learning applications.
- **PyTorch Fundamentals:** Get acquainted with PyTorch, a powerful and flexible deep learning framework.
- **Practical Experience:** Gain hands-on experience by working on real-world projects and exercises.
- **Model Building and Evaluation:** Learn to build, train, and evaluate various machine learning models.

#### Course Outline:
1. **Introduction to Machine Learning:**
- What is machine learning?
- Types of machine learning: supervised, unsupervised, and reinforcement learning
- Applications of machine learning in different industries

2. **Python Programming Essentials:**
- Introduction to Python programming
- Data structures and libraries (NumPy, Pandas)
- Basic data manipulation and visualization (Matplotlib, Seaborn)

3. **Getting Started with PyTorch:**
- Introduction to PyTorch and its ecosystem
- Setting up your environment and installation
- Understanding tensors and basic tensor operations

4. **Building Your First Machine Learning Model:**
- Data preprocessing and preparation
- Splitting data into training and testing sets
- Building a simple linear regression model with PyTorch

5. **Training and Evaluating Models:**
- Understanding the training process
- Loss functions and optimization algorithms
- Evaluating model performance using metrics

6. **Advanced Models and Techniques:**
- Introduction to neural networks
- Building and training a neural network with PyTorch
- Exploring convolutional neural networks (CNNs) for image classification

7. **Practical Projects and Applications:**
- Hands-on projects to reinforce learning
- Real-world applications and case studies
- Tips and best practices for successful machine learning projects

8. **Next Steps in Your Machine Learning Journey:**
- Exploring further learning resources
- Joining machine learning communities and forums
- Preparing for advanced topics and courses

#### Who Should Enroll:
- Beginners with no prior experience in machine learning
- Individuals interested in learning Python programming
- Aspiring data scientists and machine learning enthusiasts

#### Prerequisites:
- Basic computer literacy and familiarity with high school-level mathematics
- No prior programming or machine learning experience required

#### Course Outcomes:
By the end of this course, you will be able to:
- Understand the fundamental concepts of machine learning
- Write and execute Python code for machine learning tasks
- Use PyTorch to build, train, and evaluate machine learning models
- Apply your knowledge to real-world problems and projects
- Take the next steps in advancing your machine learning skills

Join us in "Machine Learning with Python and PyTorch: Practical Hands-on Training" to embark on your journey into the fascinating world of machine learning. Gain the skills and confidence needed to build and deploy your own models, and start making an impact with machine learning today.

Location

Online from Canada

About Me

Programming with several programming languages, such as C, JAVA, and Python.
Data scientist: extracting knowledge from structured, semi-structured, and unstructured data.
Teach programming languages and data science.
Five years of experience in teaching.

Education

Ph.D. in Artificial Intelligence Multi-modal from Sidi Mohamed Ben Abdellah University.
Master's degree in Big Data analytics and smart systems, from Sidi Mohamed Ben Abdellah University.
Bachelor's degree in Computer Science and Mathematics from Ibn Zohr University

Experience / Qualifications

Five years of experience in teaching.
Freelancer in several programming projects.

Age

Children (7-12 years old)

Teenagers (13-17 years old)

Adults (18-64 years old)

Seniors (65+ years old)

Student level

Beginner

Intermediate

Advanced

Duration

60 minutes

The class is taught in

English

Arabic

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

Teaching the Programming language(JAVA, Python, C, JavaScript)

20 € /h

### Course Description: Teaching the Programming Languages (JAVA, Python, C, JavaScript)

Welcome to the comprehensive course on Teaching the Programming Languages: JAVA, Python, C, and JavaScript. This course is designed for aspiring programmers and educators who aim to master the fundamentals and advanced concepts of four of the most popular programming languages in the industry.

#### Course Objectives:
- **Introduction to Programming Concepts:** Understand the core principles of programming, including variables, data types, control structures, functions, and algorithms.
- **Language-Specific Syntax and Features:** Gain proficiency in the syntax and unique features of JAVA, Python, C, and JavaScript.
- **Hands-On Coding Practice:** Apply your knowledge through numerous coding exercises, projects, and real-world scenarios.
- **Debugging and Problem-Solving:** Develop strong debugging and problem-solving skills to efficiently resolve coding issues.
- **Advanced Topics:** Explore advanced topics such as object-oriented programming, web development, data structures, and algorithms.
- **Teaching Methodologies:** Learn effective teaching strategies to impart programming knowledge to others, whether in a classroom setting or online.

#### Course Outline:
1. **Introduction to Programming:**
- Basics of programming and computational thinking
- Overview of the four languages: JAVA, Python, C, and JavaScript

2. **JAVA Programming:**
- Syntax and basic constructs
- Object-oriented programming concepts
- Exception handling and multithreading
- Building GUI applications

3. **Python Programming:**
- Syntax and basic constructs
- Data structures and libraries
- Functional programming and modules
- Web development with Flask/Django

4. **C Programming:**
- Syntax and basic constructs
- Memory management and pointers
- File handling and system programming
- Data structures and algorithm implementation

5. **JavaScript Programming:**
- Syntax and basic constructs
- DOM manipulation and event handling
- Asynchronous programming and AJAX
- Front-end frameworks (React, Angular, or Vue.js)

6. **Integrated Projects:**
- Cross-language projects to solidify understanding
- Real-world applications and problem-solving

7. **Teaching Strategies:**
- Curriculum development and lesson planning
- Interactive and engaging teaching methods
- Assessment and feedback techniques

#### Who Should Enroll:
- Aspiring programmers who want to learn multiple programming languages
- Educators and trainers looking to enhance their teaching skills
- Professionals seeking to expand their coding expertise for career advancement

#### Prerequisites:
- Basic understanding of computer operations
- No prior programming experience required, but familiarity with basic programming concepts is beneficial

#### Course Outcomes:
By the end of this course, you will be able to:
- Write, debug, and optimize code in JAVA, Python, C, and JavaScript
- Develop comprehensive projects using each language
- Effectively teach programming concepts to others
- Apply advanced programming techniques to solve complex problems

Join us in this journey to become proficient in four powerful programming languages and enhance your teaching abilities to inspire the next generation of coders.

AI and data science (the steps to handle a project)

26 € /h

Embark on a comprehensive journey through Artificial Intelligence and Data Science with our course, "AI and Data Science: The Steps to Handle a Project." This course is meticulously designed for individuals who aspire to become proficient in managing and executing AI and data science projects from inception to deployment.

#### Course Objectives:
- **Foundational Knowledge:** Understand the core principles of AI and data science, including key concepts, methodologies, and tools.
- **Project Lifecycle Management:** Learn the systematic approach to handling AI and data science projects through each project lifecycle phase.
- **Hands-On Experience:** Gain practical experience through real-world projects and case studies.
- **Advanced Techniques:** Explore advanced techniques and algorithms in AI and data science.
- **Ethical and Responsible AI:** Understand the ethical implications and best practices for responsible AI development and deployment.

#### Course Outline:
1. **Introduction to AI and Data Science:**
- Overview of AI and data science
- Key concepts and terminologies
- Applications and industry use cases

2. **Project Scoping and Planning:**
- Defining the problem statement
- Identifying objectives and success metrics
- Project planning and timeline management

3. **Data Collection and Preprocessing:**
- Data collection methods and sources
- Data cleaning, transformation, and integration
- Exploratory data analysis and visualization

4. **Model Development:**
- Selection of appropriate algorithms and models
- Training, validation, and testing of models
- Hyperparameter tuning and optimization

5. **Model Evaluation and Validation:**
- Evaluation metrics and performance analysis
- Cross-validation techniques
- Model interpretability and explainability

6. **Deployment and Monitoring:**
- Model deployment strategies and tools
- Monitoring and maintaining model performance
- Continuous integration and continuous deployment (CI/CD)

7. **Project Documentation and Presentation:**
- Creating comprehensive project documentation
- Presenting findings and insights to stakeholders
- Effective communication of technical results

8. **Ethics and Best Practices:**
- Ethical considerations in AI and data science
- Ensuring fairness, accountability, and transparency
- Best practices for sustainable and responsible AI

#### Course Outcomes:
By the end of this course, you will be able to:
- Manage and execute AI and data science projects from start to finish
- Collect, preprocess, and analyze data effectively
- Develop, evaluate, and deploy robust AI models
- Communicate insights and results clearly to stakeholders
- Apply ethical and responsible practices in AI development

Join us to master the end-to-end process of handling AI and data science projects and become a proficient practitioner capable of delivering impactful solutions.

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Matías

4.85

(13)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Adam

4.85

(13)

This course is designed for beginners who want to get started with programming in Python, one of the most popular and accessible languages today. No previous experience is necessary. In one session, students will learn the basics of programming and will be able to create their first Python applications. With clear explanations, practical exercises, and real-world examples, this course is an ideal gateway to exploring computer science and coding.

Online Course: Introduction to Python - Programming Basics and Simple Applications

Duration :
- 60 minutes: intensive format to learn fundamental concepts.
- 90 minutes: In-depth format with more time for practical examples and interactive questions.
---

Educational objectives
At the end of the course, participants will be able to:
1. Understand the basics of programming, including the concepts of variables, data types, conditional structures, and loops.
2. Write and run simple Python scripts.
3. Manipulate inputs and outputs to interact with the user.
4. Solve practical problems with short, functional programs.

---

Course syllabus
1. Introduction (10-15 min)
- Presentation of Python: Why this language?
- Installation and configuration of a programming environment (IDLE, Visual Studio Code, or Jupyter Notebook).
- First program: *"Hello, World!"*.

2. Python Basics (20-30 min)
- Variables and data types (integers, strings, lists).
- Mathematical operations and data manipulation.
- Conditional structures (if/else) and loops (for/while).

3. Practical exercises (20-35 min)
- Write a program to calculate the sum of two numbers provided by the user.
- Create a simple application, like a currency converter or password generator.
- Bonus for 90 min format: Fixed a more complex issue involving lists or loops.

4. Q&A and conclusion (5-10 min)
- Summary of the concepts covered.
- Suggestions for resources to continue learning.
- Feedback on the course.

---

Teaching methodology
- Interactive and engaging: the course combines theoretical explanations with practical exercises.
- Personalized approach: Sessions are tailored to the needs of participants. Students are encouraged to ask questions at any time.
- Learning by doing: examples and exercises are designed to help you assimilate concepts quickly.

---

Target audience
This course is ideal for:
- Complete beginners in programming.
- Students or professionals wishing to acquire skills in Python for their personal or professional projects.
- Anyone curious to discover a powerful and versatile tool for solving problems.

---

Benefits of this online course
- Teaching by an experienced and passionate trainer.
- Interactive sessions adapted to your learning pace.
- Access to educational materials and exercises to continue practicing after the course.

Join us now to discover programming and its applications using Python!

---

Amin

4.85

(13)

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.

Baia

4.85

(13)

Are you ready to create interactive, visually appealing websites that stand out in today’s competitive market? In this course, you’ll master the essential front-end development skills:

✅ HTML, CSS, and JavaScript – Build responsive and modern web pages
✅ React & Vue.js – Learn cutting-edge frameworks for dynamic UIs
✅ Real-World Projects – Work on hands-on projects to strengthen your skills
✅ Problem-Solving & Creativity – Develop intuitive, user-friendly interfaces

🔹 Who is this course for?

- Beginners who want to break into web development
- Developers struggling with front-end concepts
- Anyone looking to level up their skills and build real projects

🚀 Stuck on a project? Want to learn high-income tech skills?
This course will help you gain confidence, land opportunities, and grow in the tech industry.

📩 Contact me for more details and start your front-end journey today!

Panos

4.85

(13)

Python is a vastly applicable scripting language combining classes, functions and versatile variable declarations. Its popularity has exploded for teaching or research and development.

This class addresses the needs of newcomer to the programming world, as well as advanced students that need an opportunity to discuss programming matters in more detail. The structure of this course is the following

Basics of programming and the Python programming language

Basics of Python: variable types, classes, functions

Useful modules: numpy, scikit, matplotlib, pandas, torch, tensorflow, os, sys, etc.

Lessons are offered mostly in the afternoon hours, however, differences in the time zones (if any) can be discussed.

Zakaria

4.85

(13)

* This digital training aims to introduce you to the Scratch tool and through the game world, and gradually, to discover programming concepts such as loops, conditions or variables. It is aimed at anyone who is new to Scratch and who wants to create games and animations.

* Learning programming will allow students to develop their skills and will certainly allow them to meet the expectations of the future working world and emerging careers.

* In addition, learning programming allows the development of algebraic, algorithmic and computational thinking. Programming also helps to improve and develop students' sequencing ability, as well as their communication skills. Thus, there are several advantages to teaching programming, but the important thing is to remember that this learning teaches students that digital is not only for entertainment, but that it is possible to become creators. active and creative content.

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.

Amine

4.85

(13)

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.

Sandrine

4.85

(13)

Do you want to create your own website, understand how the code works, or master WordPress to become self-sufficient? I offer personalized online courses to help you learn step by step, with clarity and pedagogy.

👩‍🏫 What I propose:

* Introduction and improvement in HTML & CSS
* Using the Terminal (basic commands, Git, working environment)
* Creation of sites with WordPress (installation, themes, extensions, pages, basic SEO)
* Support for your personal or professional projects
* Advice on best practices and organization of your code

🎯 For whom?

* Complete beginners
* Freelancers, coaches, content creators
* Students or people in digital retraining
* Anyone curious to learn how to create a website

💡 Method: Interactive video lessons (Zoom/Meet), screen sharing, practical exercises, and flashcards. You progress at your own pace, with real support and simple explanations.

⏰ Flexible hours – 1 hour, 1.5 hour or 2 hour sessions
💶 Available packages
🌍 100% Online Courses – Wherever You Are!

See you soon.
Sandrine.

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.

Kevin

4.85

(13)

For many years, I have successfully supported Swiss students in the fields of statistics, data analytics, machine learning, and artificial intelligence. I have gained extensive experience using R as a statistical programming tool and know exactly what students in Switzerland are required to do. I have numerous sample projects, datasets, and exam questions at my disposal and have prepared many students for their assignments and exams in a targeted, sustainable, and highly successful manner. My focus is on explaining complex statistical procedures, algorithms, and data analyses in an understandable way, demonstrating them in a practical way, and building confidence in the secure handling of data. My goal is not only to improve grades, but also, in the long term, to develop a deep understanding of data-driven questions and modern technologies such as machine learning and AI, which are crucial in later professional life.

► How do I teach?

►I attach great importance to ensuring that my students truly understand statistical concepts, data analytics methods, machine learning, and AI models, rather than just applying them mechanically – this is how we achieve sustainable success in statistics, data analytics, and modern technologies.

►My success is based on my ability to flexibly adapt my teaching style to the individual needs of students in statistics, data analytics, machine learning and AI, including topics such as regression methods, logistic regression and other machine learning algorithms.

►I use practical, lively examples from statistics, data science and AI to clearly explain abstract concepts such as hypothesis testing, analysis of variance, linear and nonlinear models and to anchor them deeply in the memory.

►With patience and clarity, I break down complex statistical analyses, machine learning models, and data processes into their essential components so that no student is overwhelmed and can build a solid foundation in statistics, data analytics, and AI.

►I am convinced that trusting collaboration is crucial to reducing uncertainty in statistics or data science and creating a productive learning atmosphere.

►I offer intensive exam preparation and project support in statistics, data analytics, machine learning and AI, develop strategies to combat exam anxiety with my students and train them on real data sets and complex algorithms.

►As an experienced online tutor for statistics, data analytics, machine learning, and AI, I use modern tools such as interactive whiteboards and live coding sessions in R to make teaching as efficient and practice-oriented as possible.

►Locations: I teach statistics, data analytics, machine learning, and AI at your home, online, or by appointment – flexible, professional, and tailored precisely to your needs.

Meriem

4.85

(13)

Python is today one of the most widely used programming languages in the world, both in Data Science, Artificial Intelligence, Web Development and for task automation.
In this course, I will guide you step by step according to your level:

Beginner: basics of the language (variables, loops, conditions, functions).

Intermediate: data manipulation (Pandas, NumPy), file management, object-oriented programming.

Advanced: practical projects (data analysis, machine learning, automation, API, web scraping).

My goal is to make learning clear, practical, and motivating. You'll not only learn how to code in Python, but also how to structure your projects and apply your knowledge to real-life scenarios.

Farouk

4.85

(13)

These courses are part of a structured and progressive training in Object-Oriented Programming (OOP) with JavaScript, designed for beginner or intermediate developers who want to understand in depth how the language works, write clearer, more maintainable code and prepare themselves calmly for modern frameworks like React ⚛️.

Object-Oriented Programming is often perceived as complex or abstract.

My goal is simple: to make it logical, concrete, and immediately applicable.

🎯 Training Objectives

Upon completion of this training, you will be able to:

Understanding what Object-Oriented Programming really is (and when to use it)
Create and manipulate objects in JavaScript in a clean and efficient way
Use ES6 classes, constructors, and methods with confidence
Mastering this, the prototype, and the instantiation logic
Apply encapsulation, inheritance, and polymorphism without confusion
Avoiding common mistakes made by OOP beginners
Structure your JavaScript code like a professional developer

📖 Training Plan – Object-Oriented Programming in JavaScript
1. Introduction to Object-Oriented Programming 🧠
Understanding the concept, objectives and benefits of OOP.
2. Procedural Programming vs. OOP
Why unstructured code quickly becomes unmanageable.
3. Objects in JavaScript
Properties, methods and representation of the real world.
4. The keyword this
Understanding the execution context (often poorly understood).
5. Limitations of simple objects
Why duplicating code is a bad idea.
6. Constructive functions
Create multiple objects from the same model.
7. The keyword new
What it's actually doing under the hood.
8. The prototype
Sharing methods and memory optimization.
9. ES6 Classes
Modern syntax and best practices.
10. The builder
Proper initialization of objects.
11. Data Encapsulation
Protect the internal state of objects.
12. Inheritance between classes
Reusing code intelligently.
13. The keyword super
Communication between parent and child in the classroom.
14. Polymorphism
The same behavior, several forms.
15. Composition vs. Inheritance
Choosing the right architecture.
16. Best practices in OOP
Write readable, scalable, and maintainable code.
17. Common mistakes made by beginners
Pitfalls to absolutely avoid.
18. Guided practical exercise
Creation of a concrete class (product, user, etc.).
19. Assessment Quiz (Multiple Choice Questions)
To validate the actual understanding of the concepts.

🛠️ Teaching method: Understand before writing

This training program is based on a progressive and pragmatic approach:
Clear and illustrated explanations
Concrete examples from real projects
Simple but effective exercises
Constant questioning to avoid rote learning
Adaptation to the learner's level and pace
Here, we don't "recite OOP" — we understand it.

🚀 Learner's result

At the end of the training, you will not only know how to write a JavaScript class.
You will know:

1- Why does it exist?
2- When to use it
3- and when not to use it

You will leave with:
a solid understanding of OOP
a cleaner and more professional code
an ideal foundation for learning React, Node.js or any other modern framework

Dani

4.85

(13)

This advanced course builds on programming fundamentals using Python (programming language) and is designed for students who want to deepen their programming knowledge.

The course continues from functions and introduces advanced programming concepts including object-oriented programming principles such as polymorphism, inheritance, abstraction, and encapsulation.

Students will also learn data handling techniques, working with Python libraries, and developing structured programs using complex loops and data collections.

The course covers practical implementation of nested loops, nested lists, tuples, and dictionaries, as well as an introduction to data structures and algorithmic thinking.

Additional topics include graphical user interface development using libraries such as Tkinter, along with introductory concepts in data science and machine learning using Python.

Teaching combines theoretical explanation with real coding exercises to help students develop strong practical programming skills.

• Review of programming fundamentals and functions
• Object-Oriented Programming (OOP) concepts
• Polymorphism, inheritance, abstraction, and encapsulation
• Data structures basics
• Nested loops and complex data handling
• Lists, tuples, and dictionaries
• Introduction to algorithms
• Working with Python libraries
• GUI development using Tkinter
• Introduction to data science and machine learning concepts