Minimum Python for AI Development

We provide guidance on what to study for those starting AI development.

This is a lecture for people who are starting development for the first time. It's about programming thinking, which should come before development languages or UI frameworks.

This course is designed to teach the basics of the Python programming language in an easy and practical way that suits modern life. Python is easy to learn even for beginners thanks to its concise and easy-to-read syntax, and is used in various fields such as data analysis, web development, and artificial intelligence.

This course is designed for those with absolutely no programming experience, helping you learn Python, a popular programming language, from scratch. Python is one of the most suitable languages for beginners to learn due to its simple syntax and readability. It is used in various fields such as web development, data analysis, artificial intelligence, machine learning, and task automation, and is a very promising technology for the future. In this course, you can systematically learn Python's basic concepts through practice, including variables, data types, conditional statements, loops, functions, lists, dictionaries, and more. Furthermore, you can also learn practical skills by directly building actual applications or tools. We provide friendly and easy-to-understand explanations, along with abundant examples and practice problems, so that even those with fear of programming can easily follow along. By writing and testing code yourself, you can naturally increase your understanding and continue learning without getting tired. Upon completing this course, you will be able to write simple programs yourself and gain confidence in solving various problems using Python. Now is the perfect time to start Python as your first step towards career advancement or change.

“There are many ways to solve problems, but why do we feel lost during interviews?” This lecture offers coding interview survival strategies directly from a current engineer working in Silicon Valley. Focusing on problems frequently encountered in real interviews, we'll guide you not just through simple solutions, but also how to articulate your thought process and how you'll be perceived from the interviewer's perspective. Designed for mid-level developers and above, the curriculum is optimized for real-world interviews. If you are preparing for coding tests and technical interviews, gain practical skills and confidence through this lecture.

This course provides a complete introduction to programming with Python. You will start from the very basics and gradually build up to writing more advanced scripts and solving real-world coding challenges. With step-by-step explanations, practical exercises, and projects, this course is perfect for anyone looking to start their coding journey or strengthen their foundation in Python.

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

This class is for anyone who wants to become a SW instructor and provides a curriculum, materials, and the know-how and tips from a 15-year veteran instructor.

Pass the Information Processing Engineer practical exam in one go! We pinpoint only the core code and theory for you. Master past exam questions perfectly! Open the door to passing with our systematic lectures. 🏆 2024 Inflearn Rookie Award 🏆 2025 Students' Pick Award

"I want to start programming, but I don't know where to learn..." This is the perfect introductory course for beginners like you. In this course, you can efficiently learn Python basics in 90 minutes in an environment optimized for Mac users. Since we use Google Colaboratory, no software installation required! You can start practicing right away.

1. AI practice using an AutoML platform that performs data analysis and AI modeling without coding 2. Carrying out the entire process from data exploration, visualization, and preprocessing for data analysis to AI modeling 3. This course is optimized for passing AICE Basic, an AI certification organized by KT

Develop a deep understanding and intuition for calculus. Solve problems and implement algorithms by hand and in Python.

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.

Do you manually type in numerous commands every time you build a complex project or create a deployment package? Currently, most open-source projects use build automation scripts to save the trouble of typing commands. Do you also find building tedious? Then use this course to automate your builds and increase your work efficiency.

You can systematically learn stock trading automation using Python and the Interactive Brokers API, which holds the top spot in global market share.

What if ChatGPT were embedded within your own application? In this lecture, we will develop various programs using the ChatGPT API. We will cover all processes in detail, from basic API usage to program creation and deployment.

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.

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.

Learn Python coding. Learn design scripting with Rhino3d Grasshopper. Learn creative coding such as computational thinking, parametric, and generative design.

Solve coding test problems using Python.

If you can master DB and programming, you should be more than halfway prepared for the information processing engineer exam. Let's take a look at the DB and programming parts, which are worth 45 to 55 points in the practical exam, and pass the written exam steadily.