Hi, everyone. Now I will explain why we are learning Python, not other languages. Because Python is better than others in many aspects, that's why we are learning Python. Python was born on February 20th, 1991. It is an open-source, high-level, objective-oriented interpretation, interpreted, and general-purpose, dynamic programming language. Let me explain each concept one by one. It is an open-source. It means that it is for free. You don't have to pay any price for using Python. That's the benefit of using Python or R or other languages because most programming languages are offered for free. Wow. It is a great contribution of developers of Python to the world economy. It is for free. That's the great benefit of using Python. It is a high-level language; high-level means that it is a human-friendly language there's a connection between Python language and human language. So, using a specific human word, you are doing Python coding. So, for a human, it is easy to use the terminologis of Python language. It is very close to human language. That's why it is called a high-level programming language. The other one is object oriented-language. This will take some time for explaining the details of objective-oriented programming. I'm not going to explain in detail, but I'll explain the basic benefits of doing object-oriented programming; it improves efficiency in your coding. At the end of this course, I will introduce the object-oriented programming concept. And I'll show you how to use that philosopy in your programming. You must master object-oriented programming because it improves your coding performance greatly. So, it is a kind of beauty of learning programming languages. Without learning object-oriented programming. You cannot say you are a programmer. It is a very important concept and a very important approach in programming. As I said before, it is interpreted language, not compiled, not translated completely. So, whenever you run that program, the Python code is interpreted for machines to perform specific task. And it is a general purpose dynamic programming language, which means that it is used for many purposes. It is easiest to learn among programming languages. But as I said before, it is slow, but as computer performance capacity improves, the difference between interpreted languages and compiled languages is getting smaller. So nowadays, we are focusing on learning efficiency in terms of programmers. And also, as many people used it, you can share your code with others.. So, it is the most popular programming language, nowadays. It gains popularity over the past ten years, especially for machine learning and deep learning. So, nowadays, Python is a must-learn programming language. After learning Python, what you can do? There are many things you can do. First website development or software and mobile apps development. You can develop a machine learning algorithm. You can develop neural networks for object detection or understanding language. And also you can do scientific and numerical computing; for your research you can use Python. Why Python programming language is popular? Because it has powerful key libraries. Python has a standard library. Once you installed it, a standard library is automatically created. So, it is called sometimes pure Python. The basic pure Python standard library comes with Python installation. Then you need to install other powerful key libraries; NumPy for numerical computing; Pandas for panel data handling and processing. So, NumPy and Pandas are key libraries of Python, especially for handling numerical data. In the case of Pandas, not just numerical data, other text data also can be handled; Matplotlib and Seaborn those are two representative libraries for data visualization. Matplotlib and Seaborn, we are going to install all of them on your computer. SciPy for scientific computing, Scikit-learn for machine learning library. So, if you install Scikit-learn, another shortened name is a sklearn. With Scikit-learn, you can easily implement machine learning to solve specific problems. HadooPy and PySpark they are for big data processing. I mentioned only several key libraries here. And in our class, we are learning NumPy, Pandas, Matplotlib, and Seaborn, not others. But after finishing my course, you can study by yourself without others help. You can learn those libraries . Because on the web, there are so many courses or materials offered. There are many versions of Python. We are using Python version 3.8. 3.7, you can use it. No problem! 3.8, nowadays it comes with Anaconda. So we are installing Python using Anaconda distribution. Actually, we are installing Anaconda.But installing Anaconda automatically installs Python. So, we are choosing Python 3.8. Actually, right now, there is Python 3.9. It was released in October 2020. It means that last year, October newer version of Python 3.9 was released, but we are using Python 3.8. If you are doing only Python coding, using Python 3.9 is okay. But if you want to use Python for machine learning or especially neural network deep learning. In that case, you need to use Python 3.8 because there's a version problem with TensorFlow. That's why I'm introducing Python 3.8. So far, I explain why we are using Python, not other programming languages. Here's a question review question. Why do we learn Python? Oh, that's what I explained already. Choose one which is wrong. So, the first option is "For free". It means that open software. I gave you five multiples choices. Which one is the answer? The second, third, fourth, or fifth. So easy, obviously which one? This one! Python was developed in 1991, about 30 years ago. Right. So that is the answer which is is wrong. So see you next time.
