Building development skills and earning a certification: Prepare for the PCCP certification with Python

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!

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.

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

This lecture covers how to properly implement a linked list-based linear data structure using C language. You can understand the structure of the DB as well as the linked list at once.

Prepare for interviews using the algorithm coding interview methods of US Big Tech companies and implement them through differentiation strategies.

You will thoroughly understand the principles!

This course was created based on my personal experience passing the very first revised Information Processing Engineer practical exam, which had a pass rate of only 5.34%. The Information Processing Engineer practical exam can no longer be prepared for through simple memorization alone. In particular, the ability to read the execution flow of C, Java, Python, and SQL code to track results, as well as the ability to accurately distinguish short-answer concepts and write them as answers, has become crucial. This course is structured to help even beginners who are new to programming follow along step-by-step, covering everything from creating variable tables to tracking C, Java, Python, and SQL code, core practical terminology, and written exam subjects 1 through 5. Rather than being a video-centered course, this is a text-based course designed for fast reading and repeated review. It makes it easy to look up necessary parts again and focuses on practicing how to derive answers at the testing center by following the code and explanations directly. The 1st update covers the practical programming sections: C, Java, Python, and SQL. The 2nd update will organize core terms and concepts required for the short-answer practical questions and provide a "Stepper Simulator" to practice code tracking directly. The 3rd update will sequentially expand to cover written exam subjects 1 through 5. The Stepper Simulator is designed so that you don't just stop at reading explanations; you can understand how variable values change as the code executes line by line by following along yourself. If you have any questions while taking the course, please leave them in the Q&A. I will respond as quickly as possible to ensure your learning doesn't get stuck.

This course is designed to prepare you for the Information Processing Engineer practical exam solely through solving previous exam questions. Instead of unnecessary theories or vast amounts of content, it focuses on past exam questions that are repeatedly featured, allowing you to connect your learning directly to passing the exam. You can quickly grasp core points and question patterns by reflecting on the latest trends, and even learn tips for writing answers through the problem-solving process. This lecture is optimized for examinees aiming to pass efficiently in a short period of time.

New to Arduino but want to get certified? A current university professor and 4th Industrial Education expert with 20 years of experience will personally lead you to passing the Level 3 exam. From circuit connections to coding, we break down complex concepts easily using real-life examples.

When you learn machine learning, you learn how to improve accuracy. But the moment you try to put that model onto an actual chip, questions no one has answered remain. How many multiplications does this model perform? How much does it need to remember, and for how long? Can the chip specifications you are targeting handle those requirements? Machine learning textbooks talk about accuracy, and semiconductor textbooks talk about circuits, but materials that bridge the gap between them are rare. I repeatedly encountered this gap while implementing RISC-V CPUs and NPUs on FPGAs. The model with the highest accuracy often turned out not to fit on the board. In this course, you will build six algorithms directly in Python, measuring the number of multiplications, comparisons, memory usage, and accuracy each time. Then you will convert those figures into the resources of an actual FPGA board. Saying that something requires a certain number of multiplications is not enough to gauge its size, but knowing that it uses a certain percentage of the board makes the decision clearer. After nine Labs, when the six models are brought together in a single table, an unexpected picture emerges. We spent nine lessons counting multiplications, but multiplications were not what held us back. After that, we reduce floating-point values to integers, manage bit widths, and even establish criteria for evaluating the circuit. You do not need an FPGA board. The course is conducted entirely in Python, and the board is used only as a reference for converting the measurements.

I used to give up after studying only Python before even starting to study AI. Don't waste your energy learning every single feature you might only use once in a lifetime; I will teach you only the essential content you truly need to know.

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

You can understand the theoretical operating principles of the Kalman filter through easy examples.

When learning Swift, the iOS programming language, it can be confusing when multiple concepts appear all at once. That's why I created this course with the principle that "when understanding a new concept, only previously learned concepts should be used." So this course is meticulously designed with a sequential structure between concepts, where only one new concept appears at each stage, and no other unfamiliar concepts appear at all. One concept per minute, 180 concepts total. From the basics of variables and constants to understanding memory structure from a CS perspective, and even the latest syntax for asynchronous processing. In 3 hours, you'll learn 180 core concepts in the designed order.

Automate repetitive Excel, Word, Outlook, and PowerPoint tasks using Python. You will implement projects based on real-world business scenarios and learn how to design and create your own office automation system, going beyond simply learning basic functions.

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.

Theory, numerical approximations, intuition, and visualization in integral calculus. Enhance your math-coding skills.

A course where you can create programs for running a blog using Python and generate additional income through sales and branding.

Learn NoSQL technology for handling big data, one of the fundamental technologies used in the full-stack and data science fields at modern startups. MongoDB is one of the easiest NoSQL technologies to learn and use quickly. In this course, you will learn the basics of MongoDB in a short time, as well as how to work with and utilize MongoDB using Python.

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.