Data Analyst Application Rejected? I'll Tell You About Portfolios That Work

We explored the essential Python syntax necessary for big data analysis and, through various examples, presented methods such as big data file processing and visualization.

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!

The easiest ADsP introductory course that even non-majors can understand right away! From basic concepts to expected questions, everything you need to pass!

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.

SQLD Yellow Book 176 Problem-Solving Course for those who studied but can't solve problems. After completion, you'll go beyond passing to become an expert. SQLD All-in-One Pass!

If you want to properly learn OCR technology that's truly used in practice, this one course is all you need! Aiming for over 98% accuracy even with unstructured documents and complex layouts, based on the latest SOTA models and real-world know-how, we build enterprise-level OCR projects together.

This is a SQL lecture designed to help marketers learn SQL easily. We introduce the essential SQL grammar and analyze real data obtained from Kaggle.

Learn database design systematically through three stages: conceptual, logical, and physical, and strengthen your capabilities with a practical shopping mall project. Acquire real-world expertise through modern design techniques and the latest trends.

Here are some key competencies that are often overlooked by others in the fiercely competitive and complex semiconductor process job market.

You can use Python to analyze large amounts of data and visualize the analyzed data in graph form so that you can easily understand it at a glance.

LeetCode explained by Dalle, a Korean developer working at a Silicon Valley startup! This is a practical LeetCode problem-solving course that doesn't just provide answer codes, but compares multiple approaches for each problem, analyzes time and space complexity together, and explains why certain solutions are more efficient. First, we write the most intuitive approach and analyze its time/space complexity to identify bottlenecks and improvement points. Then, we explore alternative approaches applying various data structures and algorithmic techniques, comparing the performance differences and pros and cons of each method. Through this, it helps you develop problem-solving skills to design efficient solution strategies on your own when facing new problems.

The Intermediate Python course is designed to deepen your understanding of Python by covering advanced topics such as functional programming, metaprogramming, exception handling, and object-oriented programming.

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 course prepares you for the Information Processing Engineer practical exam solely through solving past exam questions. Instead of unnecessary theory or extensive content, it's designed to lead directly to 'passing' by focusing on past questions that repeatedly appear on actual exams. It reflects the latest exam trends, allowing you to quickly grasp key points and question patterns, and you can learn answer-writing techniques through the problem-solving process. This is a course optimized for test-takers aiming to pass efficiently in a short time.

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

Learn a systematic approach to S&P 500 pair trading with Python. Lay the foundation for an investment strategy that excludes emotions through professional data analysis.

Skip the complicated theories and concepts and just write SQL statements, practice, and follow along!

By implementing various practical data analysis cases using SQL, you can simultaneously improve your data analysis and SQL utilization skills.

🚀 Practical AI Anomaly Detection with Databricks! 💡 Stop using expensive and slow models! From large-scale data optimization to real-time deployment, complete an anomaly detection AI that can be used immediately in corporate practice.

If you're just learning Python and don't know what you can do or what you should do? Let's learn how to use web technologies with Python, such as web crawling, automation, and APIs.