Become a Successful Coding Test Taker – Python Edition

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

Python Course for Programming Beginners! Python certification (PCEP, PCAP) ready, based on Python Institute's curriculum! How to utilize ChatGPT with Python is a bonus!

Let's begin developing with Copilot (copilot). With AI, even elementary school students can follow along!

If you have learned the Python language, this course will help you improve your Python skills and obtain a certificate through solving Cos Pro Level 2 problems, which will allow you to acquire simple problem-solving skills, analyze output values for input, and analyze requirements.

A mediocre developer portfolio won't get you hired! Revealing the portfolio secrets that actually landed jobs at major IT giants like Kakao, Samsung Electronics, and Naver!

Course Title: Big Data Analysis Engineer Practical Exam Pass Codebook This is a practical, certification-preparation course for candidates preparing for the Big Data Analysis Engineer practical exam. To reduce the burden of having to study extensive theory and content that is not directly necessary for the exam, this course focuses only on the key concepts and code needed to solve actual exam problems. The course consists of 23 lessons and covers everything step by step, from Python basics to Task Type 1 (data processing), Task Type 2 (machine learning), and Task Type 3 (statistical analysis). Rather than simply presenting completed code, the course explains the role of each section of code and why it is written, enabling students to follow along directly and develop their problem-solving skills. Main Course Content - Essential Python and pandas fundamentals required for the exam - Task Type 1 data processing and practical problem solving - Task Type 2 data preprocessing, machine learning modeling, and submission of prediction results - Task Type 3 statistical tests and regression analysis - Practical problem solving and code review for each session - How to use the exam practice environment and final review immediately before the exam Learning Materials Provided - An e-book summarizing key concepts and solution code - Python practice files for hands-on learning - Problems and explanations for each session - Final review materials for before the exam The primary goal of this course is to help students avoid wasting time studying unnecessary material and enable them to write code independently and solve problems at the exam site. The course is structured so that even candidates with limited Python fundamentals can learn in order, allowing them to prepare for everything from learning essential code to solving practical problems in one course.

“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 is not about non-developer office workers learning coding itself, but rather an education focused on developing the ability to solve business problems directly using AI agents. Previously, one had to rely on IT departments or outsourced development when problems arose, but we are now in an era where you can design alongside AI and create immediate prototypes to implement task automation. The core competencies required for this are problem definition, establishing solution strategies through AI collaboration, and the ability to build the necessary tools yourself. In particular, by utilizing Codex CLI, existing ChatGPT users can practice agentic coding immediately without additional costs, allowing non-developers to quickly gain practical experience. The curriculum is structured step-by-step, covering everything from understanding changes in the AI agent era to development basics, terminal usage, Codex CLI-based agentic coding, problem structuring, Django web app development, and the creation of actual task automation apps. Learners can secure task automation capabilities by directly building applications applicable to real-world work, such as To-Do lists, checklists, schedule management, meeting minutes, and summarization tools. The entire course is designed as a modular micro-learning system composed of short units, allowing for rapid learning of necessary content and immediate reuse during work.

Why this course is special: Key Advantages • Intuitive Visualization: Directly observe algorithm operations in real-time with Pygame 2D simulations • Practical Implementation Experience: Go beyond theory and internalize autonomous driving algorithms by coding directly • Master Core Algorithms: Focused learning of essential algorithms such as Dijkstra, Pure Pursuit, ICP, etc. • Step-by-step Advanced Learning: Systematic difficulty progression from basics to SLAM • Lidar-based SLAM: Practical map building and localization in unknown environments

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.

This course covers calculus at a first-year university level. In particular, it focuses on the integration of single-variable functions, allowing you to master various integration methods and technical approaches. As applications of integration, we will cover problems such as volume and surface area. You will also learn numerical integration methods using Python coding.

Are you using code written by AI without even knowing what it does? It’s not enough for it to simply work—you need to make it perform well, yet when asked, “Why did you implement it this way?” you find yourself at a loss for words. The source of that frustration is a lack of fundamental CS knowledge and an understanding of how GPUs work. Through this course, you will learn the principles applied to CPUs and GPUs, along with the relevant CS knowledge, enabling you to control AI and give it instructions effectively. You will also be able to avoid being replaced by AI at your current company or when seeking employment or changing jobs, and earn a higher salary.

This course is intended for students with little to no programming experience and focuses on understanding the role of computers in problem-solving. Students will build confidence in writing simple programs using the Python 3 programming language.

■ We carefully select only the core Python grammar and organize it for you in a short time. ■ Quickly learn only the essential content such as data types, conditional statements, loops, and functions. ■ Perfect for those who want to quickly grasp a "Pythonic" grammar sense in a short period. ■ Structured so that working professionals, job seekers, and non-majors can follow along without burden. ■ A practical Python introductory course where you learn quickly and apply immediately.

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.

Are you knocking on the door of employment, but finding it difficult? As a non-major humanities graduate and academy completer, I will share the "portfolio that actually works" which I used to break through and open the doors to employment after months of trial and error.

This is a coordination course. Coordination is the process of establishing a concept strategy that incorporates requirements and creating a prototype-style planning document before diving into design and development. This course is suitable for web planners preparing to become Project Leaders (PL).

- I am a Research Engineer/AI PM running a 4-year-old AI startup. - This video is a lecture for those who want to start studying artificial intelligence "now" or in "2026". - Looking at college students, I see many who have no idea how to get started with artificial intelligence. - I hope that after watching this lecture, you'll be able to start studying artificial intelligence. - For reference, this lecture is not about "using AI in my work" or "getting started with monetization methods using GPT". - This is a video about how students, graduate students, or developers can get started when they want to study artificial intelligence.