Data Architecture for the AI Era: From Data Design to AI Applications and Practical Work

I learned it the hard way, but I want you to learn it easily. I've discarded unnecessary theories and included only the core essentials of SQL. Build your SQL confidence quickly.

A DBA instructor with 30 years of experience teaches 45 essential SQL tuning techniques that can be immediately applied in practice through real-world examples. Master the practical know-how to make slow queries 10 times faster, from execution plan analysis to index optimization and join tuning!

Perfect preparation for the SQLD certification, from understanding SQL to practical function application, finishing with the latest exam questions!

A must-have subject for aspiring developers and those looking to get a job in big data!!

🚀 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.

"Big Data + AI Full Stack Development" - The process of building big data that breathes life into AI is carried out in the form of a pilot project. We identify requirements, configure the platform step by step, and perform smart car data exploration and analysis.

Sometimes, data processing is blocked and frustrating. If you are not a professional programmer or developer, learning unfamiliar fields such as Python or Java is not easy and there is not enough time. This is for those who only know Excel and SQL basics when it comes to frequently used things. This is the first part of the SQL query book that you can find and use when you need it.

Numpy and Pandas are the foundation of data analysis and the backbone of AI frameworks, and I've packed this course with the core practical know-how I've accumulated through my work and teaching experience. I've designed it with a hands-on approach so that marketers, planners, and beginner analysts can easily follow along with data cleaning and processing—the areas where they most often get stuck. Through this course, anyone can develop the skills to handle data and produce analysis results on their own, without needing help from developers.

Mastering difficult AI with just one single analogy?! A first step into AI principles, understanding through core concepts rather than just terminology.

Using the fictional e-commerce company Aurora Market as an example, build a Snowflake-based data warehouse from start to finish. Gain practical experience across the entire process—from loading raw data through staging and core transformations, fact and dimension modeling, incremental ELT pipelines, and data quality validation to delivering data marts, optimizing performance and costs, and developing operational and recovery strategies—while acquiring the skills to design and operate an enterprise-grade data warehouse.

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.

You will learn Apache Airflow, the most widely used Orchestrator for creating software data pipelines.

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.

mongoDB, NoSQL You hear a lot these days, but is it still an unfamiliar database? Aren't you using it like a relational database (RDS/SQL)? No matter how good the technology is, if it's not used correctly, it will have the opposite effect. That's why we often see cases of failure in using MongoDB. This lecture will teach you everything from basic concepts to practical know-how so that you can use MongoDB as MongoDB-like as possible.

Generative AI is rewriting how the world works — and the people who learn it now will lead the next decade. Every industry is being reshaped in real time. Marketers are creating campaigns in minutes. Developers are shipping code faster than ever. Entire teams are automating work that used to take days. And at the center of it all sits one skill that separates those who get left behind from those who get ahead: knowing how to actually use Generative AI. The problem? Most people are still only scratching the surface. They've typed a question into ChatGPT, gotten an average answer, and assumed that's all there is. But beneath that simple chat box is one of the most powerful technologies ever built — and once you understand how it works and how to direct it, you'll never work the same way again. That's exactly what this course is built to do. Introduction to Generative AI takes you from complete beginner to confident, capable AI user — no coding, no maths, and no prior experience required. In clear, jargon-free language, you'll discover what Generative AI really is, how it works under the hood, and how to put it to work in your job, your business, and your everyday life. This isn't a dry, theoretical lecture series. It's a practical, demo-driven journey packed with real examples you can follow and copy immediately. You'll start with the foundations — what Artificial Intelligence, Machine Learning, and Deep Learning actually mean, and how Generative AI fits into the bigger picture. You'll explore ChatGPT's features and capabilities hands-on, understand why this technology has exploded so quickly, and trace its remarkable evolution. From there, you'll demystify the engine that powers it all: Large Language Models. You'll see exactly how next-word prediction, embeddings, and fine-tuning work, and you'll understand game-changing concepts like Retrieval Augmented Generation (RAG) and the rise of Agentic AI — the difference between an assistant that answers and one that acts. Then comes the real superpower: prompt engineering. This is where most learners go from "AI is interesting" to "AI is indispensable." You won't just learn what prompting is — you'll master more than a dozen proven techniques used by professionals every day, including chain-of-thought prompting, zero/one/few-shot prompting, tabular prompting, perspective prompting, comparative prompting, reverse prompting, the RGC framework, and many more. You'll get ready-to-use prompt starters, learn how to revise and sharpen your prompts for dramatically better results, and discover how to generate fresh ideas, marketing copy, client emails, and content at scale. By the end, you'll know how to make AI do precisely what you want — consistently. You'll see it all in action. This course is loaded with practical demonstrations across real business scenarios. Watch AI summarise meetings and capture insights with an AI notetaker, draft polished email responses in seconds, and spin up multiple marketing headline variations from a single product image. You'll explore how Generative AI is transforming software development, retail, and marketing, and you'll see real tools at work — generating working code with GitHub Copilot and creating images and video with cutting-edge tools like Amazon Nova. These aren't hypotheticals. They're workflows you can start using the moment you finish the lesson. But great power demands responsibility — and this course doesn't skip the hard parts. You'll dive into Responsible AI and learn how to spot and manage hallucinations, factual inaccuracies, bias, and fairness issues. You'll understand the genuine technical limitations of today's models and the practical workarounds that experienced users rely on. Through real examples — including safety refusals and bias-correction rewrites — you'll learn to use these tools wisely, ethically, and with confidence, the way professionals and organisations are expected to. And you'll finish looking forward, not just at today. You'll discover how Generative AI is disrupting search and reshaping the way the world finds information, explore the road toward Artificial General Intelligence (AGI), and get a clear-eyed view of the jobs, certifications, and fast-growing career opportunities this field is creating. Whether you want to future-proof your career, boost your productivity, or build something new, you'll leave knowing exactly where this technology is heading and how to ride the wave. Why learn from this course? You'll be joining a community of over 207,000+ students taught across leading platforms, backed by a 4.6 instructor rating and 13,000+ reviews. Every concept is explained simply, every technique is shown in practice, and every lesson is designed to take you one step closer to genuine confidence with AI. No fluff. No overwhelm. Just clear, practical, up-to-date learning that respects your time. This course is for you if you're a beginner curious about AI, a professional who wants to work faster and smarter, a marketer, creator, developer, entrepreneur, or simply someone who refuses to be left behind by the biggest technology shift of our generation. If you can use a web browser, you can do this course — and you can start today. The gap between people who use AI and people who master it is widening every single day. The tools are here. The opportunity is now. The only question is which side of that gap you want to be on. Enrol today and start your journey from AI curious to AI confident — one practical, powerful lesson at a time.

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!

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.

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.

Using ChatGPT is completely different from developing an actual generative AI service. This is because you must master everything from API calls to conversation state management, structured outputs, function calling, document-based RAG, MCP integration, and AI agent implementation. Based on extensive experience in data analysis and AI instruction, this course explains complex concepts through Python-centered practice. You will learn step-by-step—from the principles of generative AI to the OpenAI Responses API, multimodal features, File Search-based RAG, external tool integration, and the Agents SDK—to complete a fully functional AI application.

"The deep learning code runs, but why do the formulas in papers look so unfamiliar?" As you study AI, you eventually hit a wall of mathematical formulas. If you trace the source of that wall, it usually leads back to not having a solid foundation in the most basic mathematical language. Starting with the language of sets, this course covers core concepts across 18 lectures, including equations, functions, sequences, exponents/logarithms, and trigonometric functions. We don't make you memorize formulas. While we briefly touch upon how these connect to the context of AI, the primary goal of this course is one thing — to build an unshakable foundation for when you later learn linear algebra, calculus, and probability/statistics. As the first part of the Suminjeongeum series, this course will provide you with the common language needed to properly digest the remaining three parts.