Python and Statistics for Data Science Beginners

Let's develop the ability to find rational decision-making models based on mathematical thinking by understanding various elements of AI and data, and solving real-world problems using ChatGPT and no-code programming!

Let's understand the major algorithms of machine learning and deep learning, and get to know artificial intelligence!

Basic manners, etiquette, and communication skills training to foster global leaders leading the era of the Fourth Industrial Revolution.

Are you a digital talent interested in the Internet of Things (IoT)? Let's get started with IoT through Arduino!

Let's build a solid foundation in Python and solve data analysis problems!

Let's experience collaborative application development in a Linux shell and open-source software environment, and set up the development environment required for coding!

Let's acquire the Python coding skills necessary for artificial intelligence by learning the basics of the Python programming language!

Let's learn various data structures and algorithms and develop practical skills by implementing them through programming!

Let's build the skills to develop web applications using React and cultivate the capability to apply them in practice!

Let's collect and refine data through public data, web scraping, and more, and perform exploratory data analysis!

Experience text-based coding through block coding and let's control an Arduino!

Let's become creators using ChatGPT and generative AI!

Let's practice learning how to translate real-life and major-related problems into actual computer programs and utilizing Python-based AI tools!

Let's build a solid foundation in MATLAB and apply and understand the basic concepts of programming!

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

Let's design, implement, and develop while learning the basic and object-oriented concepts of the C++ language!

Understand and learn about Artificial Intelligence and AI ethics, and strengthen your AI digital capabilities by integrating them with your own field of study!

Let's have fun coding with various cute robots using artificial intelligence!

Let's look into how to deploy Abyss for non-majors!

Let's analyze and visualize data using Orange3 and explore machine learning concepts!

Introduces the main concepts and basic grammar of the programming language Python. This is a comfortable and friendly lecture that even beginners with no related knowledge can understand.

During our school days, the 'click' sound we heard in the computer lab... that was Minesweeper. In this course, we'll recreate those memories by implementing it with Python. Whether you're a beginner or even someone encountering Python for the first time, by following along line by line, you'll find that your very own Minesweeper game has been completed before you know it.

Data analysis sounds a bit grandiose, but it is actually a process of establishing a hypothesis and verifying it based on data. You can learn how to analyze what data to verify your hypothesis using Python.

Let's acquire the Python coding skills necessary for artificial intelligence by learning the basics of the Python programming language!

Anyone can easily create a Python game using the Pygame library, starting from zero base.

This is a Python coding test lecture centered on problem solving, tailored to those who are new to coding tests.

A course to understand and practice machine learning for efficiently conducting complex analysis and predictions! Even machine learning, which may seem difficult and complex, can be easy and fun to master with Masocampus's <Python Machine Learning>.

We will introduce the types of big data analysis techniques and Python libraries for analysis, and the basics of statistical analysis techniques and machine learning analysis techniques.

A lecture consisting of special lectures by professors from Canadian national universities. It covers Python, Code, Scratch programming introduction/basics and practical applications. After completing the lecture, receive a global certificate from Codesprint : )

Feeling overwhelmed by where to start with complex data analysis? I will clearly guide you through how to utilize R and AI Tutors using the practical know-how I've built up.

Based on the instructor’s experience of struggling when first learning machine learning, this course has been newly designed—unlike conventional courses—to help you understand machine learning easily and apply it to real-world problems.

Build data-driven investment strategies with Python quant investing and put them into practice. You can implement various asset allocation strategies and ultimately create your own unique investment strategy.

QML is a programming interpreter language for creating UIs provided by Qt. It is similar to JSON and can use JavaScript. Using QML and Python together, you can easily develop modern, advanced UIs.

If you're wondering, "I did the user research... but is this result truly representative of all users?" then pay attention! We will show you exactly how to add persuasiveness to your designs based on data. ✅ We explain complex statistical terms in very simple language. ✅ We carefully introduce the 3 core hypothesis tests essential for UX practice, covering everything from principles to hands-on practice. ✅ We show you how to easily analyze user data using AI—without costs or hallucinations.

Let's develop the capability to extract useful information from large-scale data and support decision-making!

In this course, you will learn the basics of Raspberry Pi and Python and practice creating simple but essential self-driving car and remote home monitoring projects.

If you ask an AI to "build a model with this data," the first few lines might look plausible, but as soon as things get slightly complex, it starts using the wrong columns, introduces data leakage, and results in a model that performs worse despite a higher score. This course does not teach you better prompts. Instead, it covers how to directly design a loop (harness) where an agent understands data, plans, writes code, validates its own results, and backtracks when wrong. After manually walking through the five-piece loop of DS-STAR, you will assemble components one by one, from data profile cards, hooks, and skill hierarchies to independent validators and ablation.

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

Understand the essence of data visualization as a balance between scientific accuracy and aesthetic expression, and systematically learn everything from color and symbology principles to graph design. By utilizing visual attributes based on cognitive science principles, you will complete your data communication skills to achieve reliability and persuasiveness in professional practice.