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<Course Description> This course is designed for beginners who are interested in learning programming with Python. It covers the basic concepts of programming such as data types, variables, control structures, functions, and file I/O. Participants will learn how to write Python programs, debug code, and design algorithms using Python. The course also introduces the basics of object-oriented programming and the Python libraries used for data manipulation and visualization. <Prerequisites> No prior programming experience is required. However, familiarity with basic computer concepts such as files, folders, and operating systems is recommended. <Learning Objectives> By the end of the course, participants will be able to: * Understand the fundamentals of programming and how it applies to Python * Write Python code for simple applications and automate repetitive tasks * Use control structures such as loops and conditional statements * Create functions to encapsulate code and enable code reuse * Work with Python libraries such as NumPy, Pandas, and Matplotlib * Use object-oriented programming principles to design more complex programs * Debug code and use error-handling techniques <Course Outline> The course is divided into modules that build on each other to provide a comprehensive introduction to Python programming. Each module consists of lectures, demonstrations, hands-on exercises, and quizzes to reinforce learning. Here is an outline of the course: Module 1: Introduction to Python History and Overview of Python Setting up Python environment Writing and running basic Python programs Variables, data types, and operators Module 2: Control Structures Conditional statements and Boolean logic Loops and iteration User input and output Module 3: Functions Writing and calling functions Scope and namespaces Return values and parameters Lambda functions Module 4: File Input and Output Reading and writing files File modes and buffering Handling exceptions and errors Module 5: Object-Oriented Programming Classes and objects Inheritance and polymorphism Data encapsulation and abstraction Special methods and decorators Module 6: Python Libraries Introduction to NumPy, Pandas, and Matplotlib Data manipulation and analysis with Pandas Data visualization with Matplotlib Conclusion This beginner's programming class in Python provides a solid foundation for anyone interested in learning programming and using Python for data analysis, automation, or software development. With hands-on exercises, interactive quizzes, and a comprehensive final project, participants will learn how to write Python code that is efficient, maintainable, and elegant.

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Hi! Welcome to my class on Matlab programming! As a PhD student in Geophysics my main tool is my computer. In order to do science one needs to know how to program. I often use Matlab in order to analyze data, run numerical models, plot results and much more. So, let's embark on the journey of learning Matlab and explore its diverse capabilities together! For beginners: I have designed it for absolute beginners to become at ease with the language within 5 sessions of 1h. Message me to know the 5 classes curriculum and I will be more than happy to share it with you! For intermediate users: If you already know the basics of Matlab but want to go more in-depth on certain packages this is the right place! Message me and we can discuss what your needs are!

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Both the algorithm and the C language are of considerable importance in the field of computer science and programming. Here is their respective importance: Importance of algorithms: Problem Solving: Algorithms are essential for solving complex problems, whether related to computer science or other fields. They help describe a sequence of logical steps to achieve a specific objective. Efficiency: A good algorithm can improve the efficiency of computer programs. By designing optimized algorithms, one can reduce execution time and memory usage, which is crucial for resource-intensive applications. Code Structuring: Algorithms help organize code in a logical and systematic manner. They allow developers to break down a complex problem into smaller, manageable sub-problems. Reusability: Well-designed algorithms are reusable. Once an algorithm is created and tested, it can be applied to different similar situations. Foundation of Artificial Intelligence: Algorithms are at the heart of artificial intelligence and machine learning. They enable systems to process data, detect patterns and make intelligent decisions. Importance of C language: Portability: C language is widely used to develop software that can be run on different platforms. Its portability makes it a popular choice for embedded systems, operating systems and cross-platform applications. Performance: The C language allows more precise control of system resources, making it particularly suitable for applications requiring high performance. Memory Access: The C language provides direct access to memory, through the use of pointers, which allows developers to efficiently manage memory and optimize resource usage. Basis of Many Other Languages: Many other modern programming languages have been influenced by C language. So, good knowledge of C language makes it easier to learn other languages. System Development: The C language is used to develop operating systems, device drivers, and other low-level software needed to run a computer. In short, understanding algorithms and mastering the C language are essential skills for developers and IT professionals. These skills enable the creation of high-performance, efficient and robust software, which contributes to the advancement of technology and the improvement of the applications and systems we use every day.

Engineer in engineering sciences option electrical engineering Senior professor of engineering sciences SKILLS IS engineering sciences Embedded system (microcontrollers, z80 microprocessors, Motorola, ARM), Real-time system, network concept (OSI, TCP/IP), design of systems and electronic cards (analog, digital, power supply), signal processing, communication protocols ( SPI, I2C, CAN BUS, UART...), telecommunications. Technical skills : Languages: C / C ++, JAVA, VHDL / VERILOG, Python, Assembler. Professional software: MATLAB, SIS + PSIM + PSpice, QUARTUS, IDE68, Mikro C, Xilinix ISE, Labview, CoIDE. Technologies: Siemens PLC, Allen bradeley, STM32, FPGA, TIA Portal, STEP7, RSLogix  Electrical engineering: Electric motors, Transformers  Renewable energies: study of the solar pumping installation and the wind turbine installation.  Electronics: analog, digital, power electronics, system electronics and instrumentation biomedical.  Networks and telecommunications.  Industrial IT and programmable logic controllers.  Automatic: modeling, identification and control of systems.  Mechatronics.  MATLAB • Noise and vibration of asynchronous motors • Speed variator • Study and implementation of LV / MV standards • Electrical accreditation: NF C18-510 standard • NF C 15-100 electrical installations • Management of electrical energy in networks (Continuous Power Flow)