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Since March 2021
Instructor since March 2021
Translated by GoogleSee original
Learn the basics of industrial automation and its different applications.
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From 41 C$ /h
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You will learn to use the basics of automation (combinatorial logic, algorithms ...) as well as the basic use of TIA Portal (siemens programming software).
With these courses you will be able to apply for complete automation training or simply do many small personal projects that require the notions of automation.
Extra information
The desire to learn and curiosity are the major assets for success in this field.
Location
location type icon
Online from France
About Me
Hello to you!
Currently an automation engineer for 3 years in the industry, I am passionate about my job and want to share my knowledge with whoever wants to!
Very attentive, I take my pleasure when understanding is well acquired and the person is happy to have a new string to their bow;)
Education
University of Saint-Etienne
DUT GEII
BAC S SI
Experience / Qualifications
3 years of experience as an automation specialist in the mainly food industry.
Age
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
French
English
Availability of a typical week
(GMT -04:00)
New York
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
Nowadays and in the current context, it is complicated to pass a job interview or simply to be spotted by employers.
For this I offer you my different techniques to succeed first in catching the eye of your future employer and then we will discuss the different ways to succeed in the interview.
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Hello, I am a doctor 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, automation, electrical engineering, automation, programming).

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The course content is titled: Advanced Analysis and Data Mining.
The book can be searched for using its name or the author's name.

Table of Contents

Chapter 1: Introduction to Advanced Analysis and Data Mining
1-1 What is data mining, its procedures and tools
1-2 What type of data is mined?
1-3 What are databases?
1-4 Relational Database
1-5 Query Language
1-6 Benefits of Database Mining
1-7 months data mining applications
A - Business Intelligence (Business Intelligence)
B - Internet search engines

Chapter Two: Data Recognition
2-1 Data Types, Characteristics, and Features
2-2 Statistical Description of Data
2-3 Visualization of Data
2-4 Measuring data similarity and difference
Chapter Three: Preparing Data for Analysis and Mining
3-1 The importance of preparing data for analysis and mining
3-2 Data Cleanup
3-3 Data Integration
3-4 Data Reduction
3-5 Data Transformation and Data Individualization

Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules
4-1 Basic Concepts
4-2 Shopping basket analysis (example)
4-3 Evaluating the dependency and correlation rules being explored
4-4 Mining Multi-Level Dependency and Linkage Rules
4-5 Mining multidimensional dependency and correlation rules
4-6 Rules of nominal and quantitative dependency and correlation
4-7 Exploring and identifying rare and negative patterns
4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage
4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones
4-10 Measuring the type and strength of the relationship in dependency and correlation rules
4-11 Applications of pattern mining in practical life

Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms
5-1 Basic Concepts
5-2 Classification using decision tree extrapolation
5-3 Classification using probability theory (hypothetical theory)
5-4 Classification using hypothetical network theory
5-5 Classification using correlation rules extrapolation
5-6 Classification using neural network algorithm
5-7 Classification using the nearest neighbor algorithm
5-8 Multi-category classification algorithms
5-9 Evaluating the efficiency and selection of classification algorithms

Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms
6-1 Basic Concepts
6-2 Clustering by Division
6-3 Hierarchical Clustering
A. Hierarchical clustering
b. Hierarchical fission
6-4 Probability Clustering
6-5 High-Dimensional Clustering
6-6 Clustering of graphs and network data
6-7 Conditional Clustering
6-8 Cluster Segmentation Assessment

Chapter Seven: Analyzing and Mining Outliers and Complex Data Types
7-1 Basic Concepts
7-2 Types of extreme values
7-3 Ways to Explore Extreme Values
7-4 Complex Data Analysis and Mining

Chapter Eight: Planning Data Mining Operations and Their Applications in Society
8-1 Planning Data Mining Operations
8-2 Data Mining in the Community
8-3 Data mining applications in vital areas of society
8-4 Practical Application: Recommendation System Usage Scenario

Appendix 1: Database Fundamentals
Appendix 2: Data Warehouse Fundamentals
Appendix 3: Glossary of Data Mining Terms
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Do you want to learn to program, prepare for an exam, or develop your computer skills?

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- Algorithms and programming logic
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- Object-oriented programming (OOP)
- Data structures and algorithms
- Debugging and best development practices
- Preparation for exams, final projects and school projects

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- Python
- VS#
- Java
-JavaScript
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Hello, I am a doctor 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, automation, 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)
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Python,VHDL
PIC Microprocessor and Microcontroller
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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.

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• Each session begins with a simple explanation of key concepts (variables, loops, functions, objects, etc.), immediately followed by practical exercises to help you progress quickly and effectively.

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With these personalized courses, you will:
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🚀 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 🏗️
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Lists, Tuples, Dictionaries – Understanding Data Structures 📊
File Management – Reading and Writing Files 📄
Exception Handling – Making Your Code More Robust ⚠️
Introduction to modules and libraries 🏛️
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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.
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✅ 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.
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✅ 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.

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The sciences presuppose a certain standard of rationality. An ability to distinguish between correct reasoning and claims that do not follow from the assumptions. In this class we study the basic principles of logic and apply mathematical techniques to the study thereof.
Topics include:
Propositional and Predicate Logic
Syntax and semantics
Natural deduction
Semantic tableaux
Correctness and soundness
Completeness

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A formal language is an abstraction of general characteristics of programming languages. Such a languages consists of a set of symbols together with some rules to determine whether a string made up out of those symbols is a member of the language.

Topics include:
Regular languages, context-free languages
Finite automata, pushdown automata, Turing machines
Regular expressions
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verified badge
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The goal is to restore confidence, develop logic and reasoning skills, and make mathematics more accessible and concrete.

This course is also suitable for students in scientific, technical or linguistic fields who need regular or occasional support.
verified badge
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verified badge
I recently graduated with a Master's degree in Mathematics from EPFL, where I also worked as a student assistant for 4 years, notably for the CMS (Special Mathematics Course), the MAN (Upgrade), as well as for several first-year Bachelor's courses. I also served as a corrector for multiple exam sessions and wrote a handout for a course for Master's students in Mathematics at EPFL. Through these experiences, I had the opportunity to support many students in successfully completing their first year, often considered one of the most demanding.

Today, I offer private math tutoring for all levels, from compulsory schooling to the Swiss Federal Maturity Certificate, as well as for Bachelor's students needing support in subjects with a strong mathematical component. Currently pursuing a doctorate in Germany, I offer exclusively online tutoring. However, I have extensive experience in distance learning, having had the opportunity to support numerous students in this format.

Passionate about teaching, what I appreciate above all is seeing students' progress, their confidence and their growing understanding. My methodology is based on an intuitive understanding of concepts, through simple and clear examples, as well as structured support in reasoning. I place particular emphasis on solving exercises, because it is through regular practice that we consolidate our knowledge and truly progress in mathematics.
verified badge
I offer training in Algorithms and Python programming for students and beginners.
Level 1: variables, logical syntax, balls, blocks and functions.
Level 2: packages, file processing, graphical presentations (dashboard).
verified badge
Welcome to the starting line of how software actually works!
This class is designed for anyone curious about how we get computers to solve problems efficiently. You don’t need to be a math genius or an expert coder yet, this class is all about training your brain to think step-by-step.

What You'll Learn:
Thinking in Steps: How to take a big, messy problem and write clear instructions for a computer to follow.

Organizing Information: Discovering the best ways to store and arrange data.

Classic Strategies: Learning the smart, time-tested tricks programmers use to sort data, search for answers, and tackle tough tasks.

Think of this course as learning the blueprints behind your favorite apps and systems. By the end, you won't just be writing code, you'll understand the clever logic that makes that code run fast and smart.

If there is anything you would like to discuss or learn I am freely to that.
verified badge
Do you want to learn programming from scratch in an easy and practical way? This course is aimed at beginners and students who want to build a strong foundation in programming and algorithms.

We will learn step by step how to think computationally, design algorithms, and solve problems before writing code, and then we will move on to applying that using different programming languages such as **Python, Java, C, C++ and Bash**.

During the lessons you will learn:

* Programming basics from scratch.
* Basic algorithms and data structures.
Variables, conditions, loops, and functions.
* Object-oriented programming (OOP).
* Write clean and organized code.
* Solving programming exercises and problems.
* Assistance with university assignments and exam preparation.
* Implement small projects to apply what you have learned.

The lessons are hands-on, where you'll write code yourself and learn to think like a programmer, not just memorize commands. The content is tailored to each student's level and goals.
verified badge
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For Higher Education (Preparatory classes, Bachelor's degrees, Engineering schools): Programming languages (C/C++, Java, Python, JavaScript...), data structures, OOP, databases (SQL) and application development.
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Data Mining Algorithms and Techniques Training Course - Beginner and Intermediate Level, for Computer Science Professionals and Non-Professionals.

The course content is titled: Advanced Analysis and Data Mining.
The book can be searched for using its name or the author's name.

Table of Contents

Chapter 1: Introduction to Advanced Analysis and Data Mining
1-1 What is data mining, its procedures and tools
1-2 What type of data is mined?
1-3 What are databases?
1-4 Relational Database
1-5 Query Language
1-6 Benefits of Database Mining
1-7 months data mining applications
A - Business Intelligence (Business Intelligence)
B - Internet search engines

Chapter Two: Data Recognition
2-1 Data Types, Characteristics, and Features
2-2 Statistical Description of Data
2-3 Visualization of Data
2-4 Measuring data similarity and difference
Chapter Three: Preparing Data for Analysis and Mining
3-1 The importance of preparing data for analysis and mining
3-2 Data Cleanup
3-3 Data Integration
3-4 Data Reduction
3-5 Data Transformation and Data Individualization

Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules
4-1 Basic Concepts
4-2 Shopping basket analysis (example)
4-3 Evaluating the dependency and correlation rules being explored
4-4 Mining Multi-Level Dependency and Linkage Rules
4-5 Mining multidimensional dependency and correlation rules
4-6 Rules of nominal and quantitative dependency and correlation
4-7 Exploring and identifying rare and negative patterns
4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage
4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones
4-10 Measuring the type and strength of the relationship in dependency and correlation rules
4-11 Applications of pattern mining in practical life

Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms
5-1 Basic Concepts
5-2 Classification using decision tree extrapolation
5-3 Classification using probability theory (hypothetical theory)
5-4 Classification using hypothetical network theory
5-5 Classification using correlation rules extrapolation
5-6 Classification using neural network algorithm
5-7 Classification using the nearest neighbor algorithm
5-8 Multi-category classification algorithms
5-9 Evaluating the efficiency and selection of classification algorithms

Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms
6-1 Basic Concepts
6-2 Clustering by Division
6-3 Hierarchical Clustering
A. Hierarchical clustering
b. Hierarchical fission
6-4 Probability Clustering
6-5 High-Dimensional Clustering
6-6 Clustering of graphs and network data
6-7 Conditional Clustering
6-8 Cluster Segmentation Assessment

Chapter Seven: Analyzing and Mining Outliers and Complex Data Types
7-1 Basic Concepts
7-2 Types of extreme values
7-3 Ways to Explore Extreme Values
7-4 Complex Data Analysis and Mining

Chapter Eight: Planning Data Mining Operations and Their Applications in Society
8-1 Planning Data Mining Operations
8-2 Data Mining in the Community
8-3 Data mining applications in vital areas of society
8-4 Practical Application: Recommendation System Usage Scenario

Appendix 1: Database Fundamentals
Appendix 2: Data Warehouse Fundamentals
Appendix 3: Glossary of Data Mining Terms
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