Data Analysis Basics: Python Fundamentals and Practice for Non-Majors

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

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!

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!

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.

The only lecture that delves deeply into a specialized field! A subject-specific industry expert will show you the fastest way to pass the exam through a thorough analysis of the exam trends!

You will study the basic grammar of TensorFlow 2.0 and learn the theory of deep learning through TensorFlow practice code.

We guide non-majors and beginners to quickly obtain the Big Data Analytics Engineer practical certification! Theory lightly, practice thoroughly - even without complex background knowledge, we focus on learning only the essential points that appear on the exam, centered around past exam questions.

RAG (Retrieval-Augmented Generation) from theory to the latest multimodal and agent-based RAG! This is a hands-on lecture designed to be understandable even for non-majors. From paper reviews to practical code implementation, it's designed so that even those encountering RAG for the first time can easily follow along.

Trying to get a job, but it's not easy, is it? I, a liberal arts non-major and academy graduate, will share the 'effective portfolio' that I personally struggled for 'n' months to widely open the door to employment.

This course provides essential knowledge needed to understand the structure and operating principles of various artificial neural networks and create good models.

You can create a deep learning analysis environment in the cloud using Docker. When Docker images managed by Google, MS, etc. are combined with the cloud, you can work with the latest deep learning analysis methods on your computer.

This is a lecture on the National Technical Qualification Big Data Analysis Technician Practical with Python. We hope you all pass!

We help you accurately intuit the concepts of the theories that form the basis of deep learning.

We'll learn about the Tableau visualization tool needed for the Business Information Visualization Skills practical exam. Don't hesitate any longer and take on the challenge!

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems, If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)

Let's develop specialized skills in programming skills, algorithm skills, and statistical analysis skills!

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

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

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.

It's now an era where data speaks, not intuition. Learn data analysis easily with ChatGPT!

This course covers the entire process of evolving ChatGPT from a simple conversational AI to an intelligent AI Agent that performs actual work tasks. Using three core frameworks - LangChain, LangGraph, and LangSmith - you'll directly create AI Agents that can be immediately used in real-world applications.

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.

This course is designed to learn the fundamental theories and practical processes necessary for applying AI modeling and service planning to real-world work environments. Learners can acquire essential foundational knowledge to skillfully perform AI modeling projects and experience various practical procedures used in actual business settings. The course is specifically structured to provide step-by-step learning of the entire workflow from AI service environment analysis → goal setting → requirements analysis → service model design → scenario planning → utilization planning → execution plan development → performance evaluation planning. Through this approach, learners can develop systematic thinking and practical application skills for how to introduce and utilize AI from business and service planning perspectives, rather than limiting themselves to purely technical learning. Upon completing this course, learners will understand the overall planning and execution process of AI projects and will be able to strengthen their capabilities as AI service planners, PMs, and data-driven strategists in actual corporate environments.

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