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Data Science

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Data Analysis

(Free) Introduction to Stock Data Analysis with Python (Finance/Quant)

This is a course for beginners in stock data analysis. Get started with stock data analysis using Python!

(4.7) 31 reviews

954 learners

Level Beginner

Course period Unlimited

  • HappyAI
Quant
Quant
Investment
Investment
Python
Python
Matplotlib
Matplotlib
Pandas
Pandas
Quant
Quant
Investment
Investment
Python
Python
Matplotlib
Matplotlib
Pandas
Pandas
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Reviews from Early Learners

Reviews from Early Learners

4.7

5.0

이원준

32% enrolled

It's great for review

5.0

최용원

32% enrolled

This was very helpful. Thank you.

5.0

jujufather

32% enrolled

Even as a beginner, it was really easy to understand.

What you will gain after the course

  • Working with Stock Data Using Python's Basic Syntax

  • Those who want to handle data using Pandas

  • Those new to stock data analysis

"Beginners who take this course will be able to overcome their uncertainty about stock data analysis."

Hello, I am Jin-gyu Lee, an AI developer and data analyst.

📖Just two years ago, I had no idea how to analyze stock data.

I studied several books with the idea of studying data-driven investing, but I was frustrated by the lengthy explanations of difficult stock market terms.

I studied stock data analysis, wondering if there was a course that covered only the essentials for beginners.

After studying stock data analysis to some extent, I learned about the things that are really necessary for beginners.

Beginners in stock data analysis are currently studying through various lectures and books, but they often spend a lot of time struggling with difficult stock terminology and coding syntax.

I have prepared a lecture that will help beginners save time and avoid getting lost like I did .

For those who have been lost like me, I have created this lecture by referencing 11 books on stock price data analysis on the market .

I decided to open a course that contains only the essential content that beginners need.

This course will help you quickly grasp the basics of stock data analysis!

 📖 Beginners don't need to spend hours struggling. Take this course and grasp the concepts of stock data analysis.

📖 This course is for those who are new to stock data analysis and are interested in it.

📚 This lecture provides a framework for liberal arts students and non-majors to avoid getting lost when starting to analyze stock data.

The first step in stock price data analysis!

Stock data analysis ! Want to give it a try, but don't know how to approach it?

This course provides a simple introduction to the basics of handling stock data using Python, and guides you through Google Colab exercises to immediately apply what you've learned.

Beginners interested in data-driven stock analysis

I am interested in data-driven stock investing, but I don't know Python.
A beginner who is worried because he doesn't know much

Anyone who wants to get started with data-driven investing by writing Python scripts

📖 This course is about handling stock data using Python.

This is an introductory course on handling basic stock data for Python beginners (Introduction to Quantitative Investment).

You can learn everything from basic Python grammar to simple stock data analysis methods!

You can develop an eye for data-based stock prices by conducting analysis exercises using actual stock price data!


For stock price data analysis
Build your confidence!

By taking this course, you will understand the basic grammar of Python and be able to conduct basic analysis using stock price data.

We hope you will gradually learn the curriculum, which consists of theory and practice, and develop the basic skills necessary for entering data analysis and quantitative investment.

Things to note before taking the course 📢

  • Learning Materials : You can check the code used in the lecture in the learning notes.
  • Prerequisite knowledge : Basic Python grammar
    *However, since the course also explains basic Python grammar, there is no problem taking the course even if you do not have prior knowledge.

Introducing the Knowledge Sharer ✒️

As a data scientist, I have experience working on data analysis and AI projects in various public institutions and companies.

We'll share our practical data analysis know-how and experience to help you easily get started with Python and stock data analysis.

Recommended for
these people

Who is this course right for?

  • Data Analysis Beginner

  • For those who want data-driven analysis, not relying on intuition

  • Beginner eager to learn Python basics and stock data handling

  • For new data-driven investors

Need to know before starting?

  • Python Basic Syntax

Hello
This is

4,481

Learners

225

Reviews

51

Answers

4.6

Rating

11

Courses

Lee JinKyu | Lee JinKyu

AI·LLM·Big Data Analysis Expert / CEO of Happy AI

👉You can check the detailed profile at the link below.
https://bit.ly/jinkyu-profile

Hello.
I am Lee JinKyu (Ph.D. in Engineering, Artificial Intelligence), CEO of Happy AI, who has consistently worked with AI and big data analysis across R&D, education, and project sites.

I have analyzed various unstructured data, such as
surveys, documents, reviews, media, policies, and academic data,
based on Natural Language Processing (NLP) and text mining.
Recently, I have been delivering practical AI application methods tailored to organizations and work environments
using Generative AI and Large Language Models (LLMs).

I have collaborated with numerous public institutions, corporations, and educational organizations, including Samsung Electronics, Seoul National University, Offices of Education, Gyeonggi Research Institute, Korea Forest Service,
and Korea National Park Service, and have conducted a total of over 200 research and analysis projects across various domains such as
healthcare, commerce, ecology, law, economics, and culture.


🎒 Inquiries for Lectures and Outsourcing

Kmong Prime Expert (Top 2%)


📘 Bio (Summary)

  • 2024.07 ~ Present
    CEO of Happy AI, a company specializing in Generative AI and Big Data analysis

  • Ph.D. in Engineering (Artificial Intelligence)
    Dongguk University Graduate School of AI

    Major: Large Language Models (LLM) (2022.03 ~ 2026.02) 2023 ~ 2025 Public News AI Columnist (Generative AI Bias, RAG, LLM Utilization Issues) 2021 ~ 2023 AI & Big Data Specialist Company Stell

    Major: Large Language Models (LLM)

    Bio (Summary) 2024.07 ~ Present CEO of Happy AI, a company specializing in Generative AI and Big Data Analysis Ph.D. in Engineering (Artificial Intelligence) Dongguk University Graduate School of AI Major: Large Language Models (LLM)

    (March 2022 – February 2026)

  • 2023 ~ 2025
    Public News AI Columnist
    (Generative AI Bias, RAG, LLM Utilization Issues)

  • 2021 ~ 2023
    Developer at Stellavision, an AI and Big Data company

  • 2018 ~ 2021
    Government-funded Research Institute NLP & Big Data Analysis Researcher


🔹 Areas of Expertise (Lecture & Project Focused)

  • Generative AI and LLM Utilization

    • Private LLM, RAG, Agent

    • Basics of LoRA and QLoRA Fine-tuning

  • AI-based Big Data Analysis

    • Survey, review, media, policy, and academic data

  • Natural Language Processing (NLP) & Text Mining

    • Topic Analysis, Sentiment Analysis, Keyword Networks

  • Public/Corporate AI Task Automation

    • Document Summarization, Classification, and Analysis

      Natural Language Processing (NLP) and text mining for reviews, media, policy, and academic data. Topic analysis, sentiment analysis, and keyword networks. Public and corporate AI workflow automation for document summarization, classification, and analysis.


🎒 Courses & Activities (Selected)

2025

  • LLM/sLLM Application Development
    (Fine-tuning, RAG, and Agent-based) – KT

2024

  • LangChain·RAG-based LLM Programming – Samsung SDS

  • LLM Theory and RAG Chatbot Development Practice – Seoul Digital Foundation

  • Introduction to Big Data Analysis based on ChatGPT – LetUin Edu

  • AI Fundamentals & Prompt Engineering Techniques – Korea Vocational Development Institute

  • LDA & Sentiment Analysis with ChatGPT – Inflearn

  • Python-based Text Analysis – Seoul National University of Science and Technology

  • Building LLM Chatbots with LangChain – Inflearn

2023

  • Python Basics using ChatGPT – Kyonggi University

  • Big Data Expert Course Special Lecture – Dankook University

  • Fundamentals of Big Data Analysis – LetUin Edu


💻 Projects (Summary)

  • Building a Private LLM-based RAG Chatbot (Korea Electric Power Corporation)

  • LLM-based Big Data Analysis for Forest Restoration (National Institute of Forest Science)

  • Private LLM Text Mining Solution for Internal Networks (Government Agency)

  • Instruction Tuning and RLHF-based LLM Model Development

  • Healthcare, Law, Policy, and Education Data Analysis

  • AI Analysis of Survey, Review, and Media Data

Over 200 projects completed, including public institutions, corporations, and research institutes


📖 Publication (Selected)

  • Improving Commonsense Bias Classification by Mitigating the Influence of Demographic Terms (2024)

  • Improving Generation of Sentiment Commonsense by Bias Mitigation
    – International Conference on Big Data and Smart Computing (2023)

  • Analysis of Perceptions of LLM Technology Based on News Big Data (2024)

  • Numerous NLP-based text mining studies
    (Forestry, Environment, Society, and Healthcare sectors)


🔹 Others

  • Python-based data analysis and visualization

  • Data Analysis Using LLM

  • Improving work productivity using ChatGPT, LangChain, and Agents

Curriculum

All

19 lectures ∙ (2hr 17min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

31 reviews

4.7

31 reviews

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    genius05274392

    Reviews 3

    Average Rating 4.0

    4

    32% enrolled

    • kangseokin1308님의 프로필 이미지
      kangseokin1308

      Reviews 2

      Average Rating 4.5

      5

      32% enrolled

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        devhenry

        Reviews 3

        Average Rating 5.0

        5

        32% enrolled

        • wjlee13066793님의 프로필 이미지
          wjlee13066793

          Reviews 1

          Average Rating 5.0

          5

          32% enrolled

          It's great for review

          • yongwchoi261087님의 프로필 이미지
            yongwchoi261087

            Reviews 32

            Average Rating 4.9

            5

            32% enrolled

            This was very helpful. Thank you.

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