[2026] Yellow Book 176 Practice Problems for Those Who Find SQLD Questions Difficult

SQLD, where should I start? For those of you feeling completely overwhelmed, this is the lecture for you. You will meet a transformed version of yourself after completing the course. SQLD All-in-One Pass!

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

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.

SQLD, where do I even start? A course for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

SQLD, where do I even start? A course for those who feel completely lost - you'll meet a transformed version of yourself after completing it. SQLD All-in-One Pass!

SQLD, where should I start? For those of you feeling completely overwhelmed, this is the lecture for you. You will meet a transformed version of yourself after completing the course. SQLD All-in-One Pass!

If you work with data, SQL is a fundamental skill you must know. In this course, we will learn SQL from a data analysis perspective, focusing on hands-on practice. The practice will be conducted in Google Colab using DuckDB.

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.

With the advent of the AI era, building data pipelines has become a core competency that determines a company's competitiveness. Learn how to build efficient data pipelines using Airflow, the most widely used tool, directly from a Silicon Valley expert (formerly Head of the Data Team at Udemy, currently a professor in the Data Masters program at San Jose State University) with practical experience and extensive lecturing experience.

How is processing big data different from processing data with Pandas? Let's learn about Spark, an essential framework for big data processing.

Practical Hadoop & Hive Big Data with LLM Hadoop Ecosystem with AI Tutor This course focuses on understanding the Hadoop Ecosystem, a core technology of the Big Data era, and provides hands-on learning on how to process large-scale data using Distributed Storage (HDFS), Distributed Processing (MapReduce), and Data Warehousing (Hive). The curriculum is designed to help you master the core technologies of big data processing step-by-step, from Hadoop's basic structure and operating principles to HDFS, YARN, MapReduce, and Hive. In particular, you will build practical skills applicable in the field by performing tasks ranging from setting up a virtual machine-based practice environment to actual data processing and analysis. Furthermore, this course goes beyond simple video lectures by providing a self-directed learning environment utilizing an LLM-based AI Tutor. Students can maximize their learning efficiency through the AI Tutor, which provides Q&A for Hadoop and Hive concepts, error troubleshooting, practice problem generation, HiveQL writing support, and project learning guides.

Starting from installing MariaDB and understanding its structure, you will learn step-by-step from writing SQL queries and utilizing functions to joins and subqueries. You will master core practical features such as table design, performance management, backup, and recovery through hands-on practice, completing the practical skills necessary for database development and operation.

Solve the challenges you inevitably face in real-world design—such as common codes, category hierarchies, history tracking, soft deletes, statistics, dynamic design, and JSON utilization—with 9 core patterns. This is not just simple theory; it contains practical know-how and selection criteria for various scenarios, proven across numerous projects. Now, become a true design expert who can confidently handle any requirement that comes your way.

"SQLD is an exam where past questions are not officially released." Preparing for the upcoming 60th exam (2026.3.7)— Practical study material featuring 50 vividly reconstructed questions by subject and chapter, based on the latest 59th exam!

This lecture is designed for job seekers preparing for Evaluation and Analysis roles in Samsung Electronics' DS Division (Memory, S.LSI, Foundry, TSP, AVP) and PE, AE, and Solution PE roles at SK hynix, who are struggling with the differences between business units and job functions. You will learn how to categorize job titles by company based on the actual workflow of Product Evaluation roles and how to translate your major-related experiences into professional terminology suitable for resumes and interviews. We will help you establish an application strategy by connecting experiences in Analog circuit design, Verilog/FPGA, process experiments, and data analysis with key industry terms such as Yield, Wafer Map, Shmoo Plot, and Failure Analysis.

The goal of this course is for you to efficiently learn SQL, apply it directly to practical work, and quickly develop data analysis skills. Let's grasp essential SQL fundamental concepts through solving Hackerrank problems, immediately apply them to real-world tasks, and truly enhance your skills.

The chemical and fine chemical manufacturing industry is a sector that requires complex processes and high safety standards. This course covers strategies for leveraging AI to increase productivity, reduce costs, and enhance safety. You can systematically learn practical skills centered on AI application cases that can be immediately applied in actual field settings, including process data analysis, quality prediction, equipment predictive maintenance, and environmental regulation compliance.

This course teaches Python-based text mining: basic theory and practice. It covers fundamental text mining data analysis for practical or thesis writing.

Learn the process of building data pipelines using Apache Airflow from basics to practical application. Understand Airflow's core concepts and architecture, and master advanced design patterns frequently used in practice such as dynamic DAGs, parallel processing, distributed processing, and Custom Operators through hands-on exercises. Set up a practice environment with Python and Docker, and develop practical skills to design and operate real workflows.

Not only developers, but also planners and data analysts learn databases step-by-step, starting from the basics of SQL.

Do you want to generate significant profits even in a bear market? Are you interested in automated trading but haven't been able to start because of coding, trading strategy design, exchange APIs, or server deployment? In this course, we guide even those new to Python to turn trading ideas into concrete strategies using ChatGPT and Codex, and implement them into backtesting and live automated trading code. We will practice Binance Futures automated trading using Python and CCXT, technical indicator strategies, DCA (dollar-cost averaging) backtesting, and Upbit API-based Kimchi Premium strategies. Afterward, we will apply Telegram notifications and order safety features, manage the completed bot with GitHub, and deploy it to a cloud server. Rather than leaving all investment decisions to the LLM, humans will determine the strategies and risk management criteria, while using the LLM as an assistant to help with strategy design, coding, and troubleshooting. After completing the course, you won't just be running the provided code—you will be able to create, verify, modify, and deploy your own unique strategies!

Through a systematic curriculum of 40 lectures, you will learn everything from the basic theories of AI to the applied AI technologies of each algorithm. Through mathematical intuition and R coding algorithm learning and practice, you will develop immediately applicable AI model development capabilities, covering everything from designing algorithm models for data analysis, machine learning, and their application tools to selecting and utilizing them.

It improves logical thinking skills, fosters the ability to understand how to use programming tools, and develops the capacity to design algorithms for problem-solving.

We are now in an era where data speaks louder than intuition. Learn data analysis easily with ChatGPT!

This course covers practical strategies for leveraging AI in the machinery and metal processing industry to enhance productivity and quality. It analyzes key process data from CNC, welding, cutting, and other operations, explaining how AI technology is applied to reduce defect rates, enable predictive maintenance, and manage worker safety through real-world case studies. Learners will understand AI-based processing optimization methods that can be immediately implemented in the field, from small and medium enterprises to large corporations, and gain insights to realize manufacturing innovation in global competition.