AI Python Coding Basics

• Week 1, Lesson 2 introduces Python for AI coding basics
• The topics covered are what is Python, Python Development Environment, and Python Exercises

Development Process of AI Service

• Data collection involves gathering necessary data from web crawling, public, and customer data
• Data storage and processing involves preparing devices that can be purchased, built or provided as a cloud service, for storing and processing collected data.
• Program production involves creating a program that analyzes patterns in user queries using AI algorithms after the data is stored in the cloud.
• Service distribution involves deploying created programs with easy maintenance and management via cloud services

AI Development Programming Languages

• Python is a popular, general-purpose language, useful in AI because of its simplicity and extensive libraries.
• Java is a robust language, scalable and performant, suitable for large AI projects.
• R is a statistical language, widely used for data analysis and machine learning tasks.

Overview of Python

• Python, developed by Guido van Rossum in 1989, aims to be a programming language for everyone (CP4E).
• Python is free, easy to read, and easy to write being an interpreted language that combines code written in other languages with excellent ability and offers rich libraries.

Compiled and Interpreted Languages

• Compiled languages such as C, C++, Pascal & Ada have fast execution speed, where the CPU compiles the source code into machine code that can be executed.
• Interpreted Languages such as Python, Ruby, PHP & Perl, have a slower execution speed, because every time an application is run, the interpreter goes through the process of translating the source code into machine code.

Versatility of Python for AI

• Python is a versatile, general-purpose programming language.
• Python dominates AI, powering machine learning and natural language processing because of its ease of use and readability.

Key Features and Advantages of Python

• Key features include readability due to its simple syntax, making it easier to write and understand code.
• Python is cross-platform, so it works on many operating systems.
• There is a very large community for Python, providing support for debugging and troubleshooting.

Python's History and Evolution

• Guido van Rossum created Python in the late 1980s at the National Research Institute for Mathematics and Computer Science, Netherlands.
• Python served as a successor to the ABC programming language.
• Python emerged as a preferred language for AI development in the early 2000s.
• Python's simplicity and powerful libraries for machine learning and data analysis are key factors in its popularity.

Python's Role in the AI Ecosystem

• In machine learning, Python provides libraries like scikit-learn, TensorFlow, and PyTorch for classification, regression, and clustering tasks.
• In deep learning, Python develops neural networks for image recognition and natural language processing.
• In data analysis, Python libraries such as Pandas, NumPy, and Matplotlib enable data exploration, manipulation, and visualization.

Python Libraries and Frameworks for AI

• TensorFlow is a popular open-source machine learning library for deep learning, developed by Google.
• PyTorch, another machine learning library, is known for flexibility, dynamic computation graphs, and ease of use.
• Scikit-learn is a comprehensive machine learning library for classification, regression, clustering, and dimensionality reduction tasks.

Real-World Applications of Python in AI

• In healthcare, Python helps with AI-powered medical diagnosis, drug discovery, and personalized healthcare.
• In finance, Python is used for fraud detection, risk assessment, and algorithmic trading.
• In e-commerce, Python facilitates personalized recommendations, targeted advertising, and customer service chatbots.
• In entertainment, Python supports content recommendation systems, video game development, and special effects generation.

Python Fundamentals

• Variables in Python store data and you can assign values using the assignment operator (=).
• Python supports various data types, including integers, floats, strings, lists, tuples, dictionaries, and Boolean values.
• Control flow statements like if-else, for loops, and while loops control the execution of code based on conditions.

Installing Python: Windows using the Official Installer

• The official Python installer is recommended for developers needing a full-featured development environment due to it offering more customization and control.
• The first step is checking the operating system to know whether to choose the 32-bit or 64-bit installer.
• Navigate to the downloads page for Windows on Python.org to download the official Python installer.
• An installation wizard will appear after running the chosen installer.

Running Python

• Launch Python IDLE by pressing the Windows Start button.
• IDLE is a simple, bundled IDE with a text editor, an interactive shell, and code writing, running, and debugging tools.
• Before running the code, set the Font Face and Font Size, in the Configure IDLE menu.
• IDLE has interactive Python Shell mode and Python Editor mode.
• Use Python shell mode for short and simple codes and Python Editor mode for long and complex codes.

How to Run Python Shell Mode

• Write the code and press Enter key.
• Strings should be enclosed in quotes and numbers do not require quotes.
• You can exit IDLE by executing the Exit IDLE menu in File.

How to Run Python Editor Mode

• Launch code editor by clicking [File] -> [New File] in the IDLE window.
• Clicking the Run Module menu or pressing the F5 function key runs the code

Writing Python Exercises

• Basic calculator programs can do addition, subtraction, multiplication, and division by two static or input numbers
• Popular geometric drawing tools, such as turtle graphics, can now be implemented in code using Python.