인프런 - 라이프타임 커리어 플랫폼

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.

"While following trends is important, unwavering fundamentals are what build true skill." This lecture is a beginner course designed to help you understand the flow of data science and properly master the most practical techniques.

This introductory course, designed to be the easiest and most practical for Python beginners, covers intuitive dashboards using Streamlit, Google Cloud Platform for deployment, and more. Additionally, you can also prepare for the 빅데이터 분석기사 practical exam.

Prepare perfectly for the Goorm environment—the biggest challenge of the Big Data Analysis Certification practical exam—on the practice platform provided by Algorun. Practice past exam questions for Task Types 1, 2, and 3 repeatedly in a setting identical to the actual exam environment to gain an intuitive feel for the test rather than just memorizing code. This is a practice-oriented lecture designed to train your hands to move automatically in an environment that differs from Colab or Jupyter.

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

1. Mock exam problem-solving for passing AICE Associate, Korea's only state-certified AI certification. 2. A course featuring 12 mock exam sessions with the same question types as the actual AICE Associate exam.

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

This is a lecture on the National Technical Qualification Big Data Analysis Technician Practical with Python. We hope you all pass!

This course is not just about "how to implement" a Transformer, but about dissecting why this architecture was created, what role each module plays, and how the entire model works from the designer's perspective. We deeply analyze the internal computation principles of Self-Attention and Multi-Head Attention, and directly verify through formulas, papers, and implementation code what limitations Positional Encoding, Feed-Forward Networks, and Encoder·Decoder structures were introduced to solve. Starting from Attention, we assemble the entire Transformer structure ourselves, and actually perform training to experience firsthand how the model operates. This course is the most structured and practical roadmap for "anyone who wants to completely understand Transformers."