Python Big Data Analysis Basics

This is a special lecture summarizing the key points for passing the NCS revised Information Processing Engineer written exam. You can efficiently study the CBT written exam and written practical exam.

This is a special lecture summarizing the key points for passing the NCS revised Information Processing Engineer practical exam. You can efficiently study for the CBT written exam and written practical exam.

It's structured to enable understanding of ChatGPT and text generation AI, learning effective real-world use, practice via diverse examples, and direct application.

This course introduces core principles and practical uses of various generative AI technologies (text, images, video, music), helping foster creative problem-solving skills.

Through this lecture, you can learn the basic grammar of the C language. Instructor: Professor Eunmi Jeong (SW Convergence Education Center, Andong National University)

● Learn from the basics of data analysis to machine learning using Orange 3 software ● Strengthen practical skills through hands-on practice using actual datasets

This is a web programming course for beginners. It is designed to help you learn the basic grammar and usage of HTML, CSS, and JavaScript step by step. It covers the core elements of web development, such as web page structure and design, and implementation of interactive features.

Learn how to break down complex concepts into easy terms and apply them to collaborative projects from the ground up.

This course aims to understand IoT concepts and develop practical skills through hardware construction and coding using Arduino and Micro:bit.

Learn the basic grammar and object-oriented programming of Java.

Learn the basic grammar of the Python language, practice writing simple logic using it, and learn about various libraries.

Using block coding Entry, foster computational thinking and problem-solving skills, and through Entry AI tools, learn artificial intelligence concepts and practice simple machine learning.

Through this lecture, you will understand artificial intelligence and learn App Inventor programming to create smartphone apps using artificial intelligence technology.

You can solve everything from the concept of the metaverse to its utilization at once. It will be of great help to those who are new to the metaverse.

Learn about the basics of Python required for data analysis, the data analysis framework (pandas), and the data analysis process.

The [Customized Basic Python for Data Analysis] course that even non-majors have easily completed! Learn the basics of using ChatGPT alongside it to create a "starting point" for data analysis and AI utilization. From essential prerequisites for data analysis to customized learning from a "Data Analysis Instructor," you can build deep foundational skills while learning quickly. This course instills the courage and confidence needed for coding and provides a roadmap for your future data analysis studies.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

Build data-driven investment strategies with Python quant investing and put them into practice. You can implement various asset allocation strategies and ultimately create your own unique investment strategy.

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.

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.

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.

Let's learn how to collect data from the web and create a supervised learning model for machine learning!

A course to understand and practice machine learning for efficiently conducting complex analysis and predictions! Even machine learning, which may seem difficult and complex, can be easy and fun to master with Masocampus's <Python Machine Learning>.

In Part 3 of Creating a Python Trading Room for Quant Investment, you will learn about portfolio theory and concepts necessary for real investment, as well as how to implement them with code. In Parts 1 & 2, you mainly learned about code implementation methods for analyzing financial data, and in Part 3, you will learn about 'portfolios', which are an important part of quantitative investment. With the question of why you should create a portfolio, you will learn portfolio theory, implement it in Python, and practice the code necessary for real portfolio investment. I hope this lecture will be helpful for your own portfolio investment.

Let's build a solid foundation in Python and solve data analysis problems!

Let's cultivate professional expertise in programming, algorithms, and statistical analysis!

Based on the instructor's own failed experiences when first learning machine learning, this is a newly designed course that differs from existing lectures, making it easy to understand machine learning and apply it to real-world problems

You can learn the skills and know-how needed to improve work efficiency by utilizing Open API and Python.

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.

Revolutionize your stock investing with AI! In this course, you will directly build a functional AI automated trading system targeting the top 25 Nasdaq stocks. We provide a special opportunity to gain experience and know-how through mock trading using the Korea Investment & Securities API, and then transition to AI automated trading with a real account. Even stock market beginners will have no problem. We explain basic stock concepts and the reasons why you should invest in US stocks in an easy-to-understand way, while providing all source codes and even remote support. From now on, investing is essential for the next 60 years of our lives. Create your own AI investment partner to join you on this journey!

Time Series: Become a Data Analysis Expert! Let's be analysts strong in theory & practice!

Those who have learned the basics of Python will learn how to utilize Python after watching this lecture.

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.