This course teaches computer science with Swift and SwiftUI. Swift and SwiftUI are the building blocks of Apple app development. Learn how to develop iOS apps from building user interfaces, storing data, retrieving information from the internet, and set the foundation of your app development journey. Please ensure you have a compatible iPad or MacBook. Download Swift Playgrounds on your iPad, or download Xcode on your MacBook.

In each meeting, we'll go through basic things in HTML. There are several things I'll discuss, for instance, how to display a list on your website by using HTML tags, how to display images and videos, and how to add tables and animation to your texts. To make things easier, I recommend you use and be familiar with text editor apps or websites (I use sublime text). Don't hesitate to ask something you don't understand and feel free to chat me on Zoom/schoolhouse chat box. Thank you:) P.S.: Since I'm not a native English speaker and do not live in an English-speaking country, sometimes my explanations may be confusing. If you feel confused about what I'm saying, type your question or just open your microphone and ask me your question as clearly as possible. Thanks!

Dive into the world of Machine Learning with this hands-on tutoring series designed to equip you with the foundational skills and techniques to build models using Python. Whether you're a beginner or have some coding experience, this series will guide you through key concepts such as supervised and unsupervised learning, data preprocessing, model evaluation, and more. With Python as our tool of choice, you'll learn to implement algorithms like linear regression and neural networks. By the end, you’ll be able to confidently apply Machine Learning techniques to real-world problems and projects. In this series, we'll be covering the following: TensorFlow, Python, linear regression, variables, data analysis, data preprocessing, model evaluation, neural networks. Before the start of the series, I reccomend taking a look at GoogleColab and Tensorflow below are the links: [https://colab.research.google.com/ ](https://www.tensorflow.org/) [https://www.tensorflow.org/](https://www.tensorflow.org/). For your success in this class, I highly recommend having some experience with Python! While we'll cover essential Python libraries and functions for machine learning, having a basic understanding of Python syntax, data structures, and object-oriented programming will help you follow along more smoothly and get the most out of this series. Don't worry if you're new—I'll provide plenty of guidance along the way! Currently, there are only two sessions listed. More will be added soon.

Welcome to "Introduction to Data Science with Python" course! This is my second time hosting this course, and I have made adjustments and improvements from my first time. In this course, you'll learn how to use Python for data analysis and gain insights from large datasets. Python is a versatile language widely used in the data science community. You'll explore Python's fundamentals, including syntax and data structures. We'll also cover essential libraries such as NumPy, Pandas, and Matplotlib for efficient data manipulation and visualization. Through hands-on activities and projects, you'll develop the skills to analyze and present data effectively. By the end of this 17 session course, you will be an expert on the basics of data science, and you would have completed your very first data science case study project. Please note that there will be assignments after every session to best learn data science. Get ready for an exciting journey into the world of data science! :)