Kỳ thi thực hành kỹ thuật viên phân tích dữ liệu lớn (Python)

In the [Beginner's] Data Visualization with Power BI course, you will learn how to edit data using the query editor, visualize data using various tools, and check and share the analyzed results.

Let's use the Folium library and Google Cloud API provided by default in Python. You can perform spatial data analysis based on coding without a separate tool.

Analyze in an environment like Excel and automatically create Python code. This lecture will help you understand data analysis by comparing it to Pandas and Seaborn.

In the [Learn Machine Learning with AutoKeras] lecture, you can learn about AutoKeras, which was developed from the Keras library previously used in machine learning, and use it directly through examples.

In the [Beginner's] Data Visualization with QGIS course, you will learn about basic spatial analysis methods using the QGIS program and spatial data.

This is a basic course on machine learning and deep learning analysis for data analysis beginners.

We will help those preparing for the Big Data Analysis Engineer Practical Exam with R to prepare for the exam. We will select and inform you of only the essential parts based on the questions that were on the Big Data Analysis Engineer Practical Exam. If you complete the course, you will be one step closer to passing the Big Data Analysis Engineer Practical Exam. We have reviewed the recent exam questions and uploaded related scripts and data. Also check out the latest exam information.

The Certified Big Data Analyst exam is a nationally recognized certification administered twice a year. This course provides detailed lectures covering everything from the basics to the core concepts to help you prepare for the practical exam. The exam difficulty increases with each iteration. To address this, we provide a range of essential content, starting with the fundamentals, to improve your chances of passing.

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.

I will guide non-majors and beginners to quickly pass the Big Data Analysis Engineer practical exam! Theory lightly, practice thoroughly. Even without complex background knowledge, focusing on past questions, we intensively study only the points sure to appear on the exam.

Many applicants want to solve past questions. Why is that? Because the question setter refers to past questions. Solving the latest past questions is the shortcut to success.

Understand the core of big data business and provide insights on how to utilize it in marketing strategies in the field.

This lecture aims to systematically learn the essential core concepts and functions absolutely necessary for the Business Information Visualization Practical Exam (Tableau), based on the exam guidelines of the organizing institution. It is structured around practical exercises so that you can freely use the functions frequently tested in the actual exam, and through solving mock exam problems of types A and B, you can improve your understanding of the exam types and your problem-solving skills together. Lecture plan and materials can be checked at https://github.com/hansikyung/Tableau_OneTime.

Unlike existing lectures, this course has been newly designed based on the instructor's initial failures in learning machine learning, enabling easy understanding and application to real-world problems.

In this class, you will learn techniques for retrieving (crawling) and processing data from various operating sites using Python, and apply them directly to various examples that you may encounter in the field. Through this, you will learn techniques that focus on solving practical problems based on an understanding of the basic principles of how the web works, rather than one-dimensional task automation by copying and pasting given codes, and accordingly, you will be able to collect and process data from any site in the future. You will also learn how to resolve various exceptions that occur in this process with code, and ultimately, you will be able to solve and automate various problems that occur in daily life with programming thinking.

With Python Quant Investment, you can create investment strategies based on data and invest according to the strategy. You can implement various asset allocation strategies and ultimately create your own investment strategy.

I want to create an algorithm trading bot that makes unlimited money and run it automatically. Where should I start?

This course covers how to leverage AI in the food and pharmaceutical manufacturing industry to enhance productivity and quality. Through real-world case studies, you'll learn how AI is applied in key stages such as raw material management, production processes, quality inspection, and regulatory compliance, while understanding defect rate reduction and efficient operational strategies. Through this course, learners will master ▲characteristics of the food and pharmaceutical industry and the necessity of AI adoption ▲data-driven quality management ▲predictive maintenance and equipment optimization ▲regulatory compliance monitoring and risk management ▲analysis of domestic and international implementation cases, gaining strategies and insights that can be immediately applied in the field.

Now display Python results as web pages! You can create your own web page using only Python. This is an opportunity to create an Interactive Dashboard that allows you to check results created with Python, such as data analysis and machine learning, on a web page!

Leveraging Python's basic syntax and popular libraries Auto-generating Python syntax and library code using ChatGPT

Hello! Have you ever gotten tired of repeatedly writing the same code over and over again while doing data analysis? 😫 Now let's give your projects wings with PyCaret! 🚀 This course will teach you the secret to automating most of the tedious and complex machine learning processes with just 5 lines of code. Here's how this course will transform you! ✨ Master Real-World Projects: 📈Customer purchase prediction (classification), 📉Medical cost prediction (regression), 🧩Customer grouping (clustering), ⏳Airline passenger prediction (time series)! You can develop 'real' problem-solving skills by following along with 4 core projects hands-on. Acquire Expert Skills: But that's not all! 🤖 We'll also teach you expert skills like managing your models with MLOps and creating API servers with just a few clicks. Pretty amazing, right? Protect Your Work-Life Balance: Most importantly, we'll drastically reduce your repetitive tasks and help you focus only on core analysis. Leaving work on time is a bonus! 😉 Whether you're not yet comfortable with coding or you're a current professional wanting to explosively boost productivity, everyone is welcome! 👋 Shall we transform together into a '10x faster data scientist'?

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.

"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.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.

Revolutionize your stock investments with AI! In this lecture, you will directly build a real, working AI automated trading system targeting the top 25 NASDAQ stocks. We provide a special opportunity to gain experience and know-how through simulated investments with the 한국투자증권 API, and to perform AI stock automated trading with a real account. Even stock beginners will have no problem. We will easily explain basic stock concepts and why you should invest in US stocks, and provide all source code and remote support. From now on, investment is essential for the next 60 years of our lives. Create your own AI investment partner that will be with you!

Learn NoSQL technology, which can handle Big Data, one of the fundamental technologies in full-stack and data science utilized by modern startups. MongoDB is the easiest and quickest technology to utilize among NoSQL databases. In this lecture, you will learn the basics of MongoDB in a short time, and also acquire the skills to manipulate and utilize MongoDB with Python.