Data Analysis Learned Through Python Code

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!

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

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

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

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

Let's become creators using ChatGPT and generative AI!

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

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

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

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!

Are you a digital talent interested in coding and development? Let's get started with the Internet of Things through micro:bit and Maqueen!

Are you a digital talent interested in coding and development? Let's get started with block coding through CoSpaces!

Let's cultivate professional expertise in programming, algorithms, and statistical analysis!

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

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 look into how to deploy Abyss for non-majors!

Have you studied Python syntax but felt lost when it came to actually handling data? You know you need to learn NumPy and Pandas, but if you've been wondering where to start and how to connect them, this PART 2 is the answer. In PART 2 of our 50-lecture data analysis curriculum, you will experience the step-by-step process of loading, cleaning, processing, and statistically interpreting real data. You won't just learn libraries and syntax; you will establish criteria for which tools to choose in specific situations. PART 2 is the turning point where you move from simply knowing Python code to actually being able to handle data.

There was a rumor that Ediya Coffee always opens its stores near Starbucks. How much of a difference is there really between the store locations of Ediya and Starbucks? Will the real estate price fluctuation trends from 2013 to 2019 be reflected in apartment pre-sale prices as well? What kind of parks are in my neighborhood? How can we best utilize the data available on the Public Data Portal? The goal is to become familiar with Python and various data analysis libraries by working with different types of data through public data.

Let's cultivate professional expertise in programming, algorithms, and statistical analysis!

1. A practice-oriented lecture designed to help you pass the AICE Associate, Korea's only nationally recognized AI certification. 2. Learn to the level of performing data analysis and AI modeling based on Python.

Let's use the R language, which processes data easily and conveniently, to help even non-computer science majors develop their skills in utilizing computer programs related to their own fields!

Analyze in an environment like Excel and automatically create Python code. This lecture will help you understand data analysis by comparing it to Pandas and Seaborn.

We guide non-majors and beginners to quickly obtain the Big Data Analysis Certification (Practical Exam)! Keep the theory light and the practice solid—focusing on core points that are guaranteed to appear on the exam through past questions, without the need for complex background knowledge.

Even office workers who know nothing about coding can easily learn the basic concepts and grammar of programming through practice, and learn file input/output, Excel data processing, automatic creation of MS-Word documents, graph drawing, web scraping, etc.

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 : )

If you are planning a service, a website is an essential element. Of course, beyond services, most current program infrastructures operate based on the web. The purpose of this course is to learn how to create a website using Python, which is considered one of the easiest programming languages, and to set it up for actual operation.

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

This course is designed for beginners and consists of easy explanations and various hands-on projects. It covers data collection using web crawling and LangChain tools, and summarization, extraction, sentiment analysis, and recommendation systems using LLM.

This course aims to acquire Python-based web crawling technology to collect data from web pages and improve data collection and analysis capabilities at work based on this.

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.

"The deep learning code runs, but why do the formulas in papers look so unfamiliar?" As you study AI, you eventually hit a wall of mathematical formulas. If you trace the source of that wall, it usually leads back to not having a solid foundation in the most basic mathematical language. Starting with the language of sets, this course covers core concepts across 18 lectures, including equations, functions, sequences, exponents/logarithms, and trigonometric functions. We don't make you memorize formulas. While we briefly touch upon how these connect to the context of AI, the primary goal of this course is one thing — to build an unshakable foundation for when you later learn linear algebra, calculus, and probability/statistics. As the first part of the Suminjeongeum series, this course will provide you with the common language needed to properly digest the remaining three parts.

This is a Python basics course for starters who want to grow as data analysts. - Those who want to do data analysis but don't know Python - Those who want to learn machine learning with Python - Those preparing for the Big Data Analytics Engineer practical exam - Those who want to develop machine learning-based applications with Python

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

[Lecture Summary: From Pixels to Practice, Building a Business Card Recognition System] * **Pre-processing:** We learned how to remove noise and extract the 'skeleton' of a business card using Gaussian Blur and Canny Edge detection. * **Hough Transform:** We went through an "audition" process to select the real 'borders' from tens of thousands of points using the $(\rho, \theta)$ voting system. * **Geometric Reasoning:** By solving complex linear equations through substitution and matrices, we precisely targeted the four corners $(x, y)$ of the business card. * **Data Sorting & Filtering:** We mastered data refinement techniques, such as removing overlapping lines and labeling the found points in the order of 'top-left, top-right, bottom-right, bottom-left.' * **The Magic of Transformation (Perspective):** We concluded with practical techniques for straightening tilted images or, conversely, compositing an image into a frame of your choice. 📢 "Does looking at formulas give you a headache? It was the same for me." When I first took on an image processing project in the field, what bothered me most were the screens full of $\sin$ and $\cos$ formulas. Textbooks were full of nothing but equations, and nowhere provided answers to practical problems like, **"Why can't this find the business card in my code?"** Through this lecture, I want to help you solve three chronic problems you will encounter: 1. **"The problem where math feels like an alien language"** → Solved through [The Power of Analogy]. Instead of simply memorizing linear equations, I help you understand them through **'lasers fired from the origin'** and **'shadow play.'** Once you understand the principles, the code follows naturally. I translate formulas into the 'easiest language' that I discovered after countless trials and errors. 2. **"The problem where you know the theory but can't apply it"** → Solved through [Data Auditions]. Why are there 10 borders on my business card? Why is the order of the corners scrambled? I have revealed all my debugging know-how on how to filter and sort the 'messy data' you inevitably encounter in practice. The audition logic for separating the wheat from the chaff will take your project to the next level. 3. **"The problem where the result is boring"** → Finished with [Interactive Composition]. This isn't a lecture that ends with just looking at black-and-white edges. The moment you tuck the business card you created into a 'Hall of Fame frame' that you clicked yourself with a mouse, you will experience **'the magic of manipulating space'** beyond simple coding. "Computer vision is not about math; it's the process of gaining a new set of eyes to see the world." I want to pass on to you that thrilling 'A-ha!' moment I realized in the field. You can close the complex theory books now. Let's paint images freely with the brush of code together!

You can easily learn how to collect and process data using Excel's Power Query feature, even if you don't know coding. You will learn Excel crawling skills by practicing the project below together.

You can learn the skills and know-how needed to improve work efficiency by utilizing Open API and Python.