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인프런 영문 브랜드 로고
Data Science

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Data Analysis

Creating a dashboard using Python Streamlit (feat. Big Data Analysis Engineer Practical Preparation)

This introductory course is designed to be the easiest and most practical course for Python beginners, and teaches you how to use Streamlit for intuitive dashboards and Google Cloud Platform for deployment. You can also prepare for the Big Data Analysis Technician practical exam.

(4.2) 10 reviews

116 students

Python
streamlit
Scikit-Learn
Pandas
Web Crawling
Thumbnail

This course is prepared for Beginners.

What you will learn!

  • Python Machine Learning

  • Python Data Analysis

  • Python Web Crawling

  • Python Dashboard

  • Big Data Analysis Article

Lecture Topics and Objectives 💎

1. Learn the basic Python grammar required for data science.

2. Learn the basic grammar of Streamlit, an open source dashboard.

3. Learn the basics of machine learning and time series.

4. Learn Google Cloud Platform for deployment.

  1. You can prepare for the Big Data Analyst practical exam together.

I highly recommend this course to these people! 🔑

I'm new to data analysis . Where and how should I start?

I'm a true liberal arts student and I want to learn data science. Is this possible?

I want to create a data analysis portfolio , but where do I start?

  • A beginner who is just starting out in data analysis

  • Non-majors who are hesitant about where to start and what to do

  • Job seekers who want to change careers to data analysis

This lecture is about project with Streamlit
It's all done in one go with Python !

This textbook contains a method to complete a project that implements various data visualizations using Streamlit, a Python open source library, in one go. You can see various dashboards and examples such as Python, Pandas, web crawling, Scikit-Learn, and Streamlit.

This textbook will be a quality guide for anyone aspiring to become a data analyst.

*Purchase of textbooks is not required.

What you will learn in this course 📚

  • Based on the basic grammar of Python, you will learn the following six items.


First, the main data science libraries
pandas, matplotlib, seaborn, scikit-learn, prophet, lightGBM

Second, Introduction to Geospatial Analysis
Analytics that use data associated with a specific location or geographic area

Third, crawling public data APIs
Using Python, data from the public data portal is stored in a data frame and analyzed through visualization.

Fourth, the Streamlit dashboard
Create simple, yet accurate data dashboards with Python Streamlit

Fifth, GitHub, Git, GitHub Action
Install, integrate, and utilize GitHub

Sixth, Google Compute Engine, Google BigQuery

Introducing the structure of this lecture 💻

This course contains various examples using Python Streamlit!

Become a data analyst by sticking to the basic concepts step by step and completing various practical tasks !
In addition to the lectures listed in the lecture list, additional lectures will be uploaded. Please look forward to it 🥨

Only in Inflearn lectures

Don't miss out on the benefits offered.

Please check before taking the class!!

This lecture is available for free on YouTube !

This lecture is from darkgreenchloeJJ

You can meet them all for free.

Key differences from YouTube video lectures

YouTube videos are intended for readers who have purchased the book , but the biggest difference is that there is no Q&A from viewers. It is true that it is difficult to respond to each and every question from readers who have not actually purchased the book.

So, the differences are:

  • The biggest difference is that it can provide Q&A through the Inflearn environment .

  • The source code and lecture materials for the lecture slides and other bonus lectures that are not in the book are not available on YouTube.

    In fact, some of the tutorials in this lecture (such as Selenium) are not included in the textbook.

💡 Lecture materials and source code

You can watch YouTube videos for free, but lecture materials and source code are not provided. Therefore, if you need source code or lecture material slides, I strongly recommend taking this course .

💡 Friendly and thorough Q&A

We do not operate comments on YouTube videos. You may ask many questions, but it is difficult to answer them all. If you ask questions through this lecture, we will answer them with sincerity .

A lecture that will continue to develop in the future

If you are currently hesitating to purchase the course, please read this.

  • Currently, the number of lectures is small at around 200, but this number is expected to continue to increase in the future.


  • The Google Cloud and Github Actions courses are scheduled to be filmed and completed by March 31, 2024. (Completed O)

  • In addition to Python-related lectures, we will continue to update various lectures essential for employment here. You can think of it as a kind of bonus lecture . We will continue to update various contents, not limited to the contents of the book. We plan to continuously update employment-related contents by collecting the requirements of students.


    • Example: How to create a GitHub portfolio and PPT portfolio

    • Example: Big Data Analyst Practical Test Scheduled to be filmed before May 31, 2024

  • If you like the sample lesson, please purchase it now.

Attention job seekers!

🙇‍♀ Just like when the book came out, this lecture is for job seekers .
If you have any questions regarding career paths or portfolios, please feel free to contact me at any time.
In the long term, we will upload lectures that can support job seekers through various methods such as project portfolios and blogs.

Please check before taking the class!

Since you will learn from the basic grammar , programming experience is not necessarily required.
I hope that you will make time to study consistently with this lecture so that we can grow together.

For better lectures 🍒

🦋 In order to provide better lectures, please leave a review after taking the lecture and I will reflect it as much as possible and upload the video!

🐣 If you tell me what you need additionally, such as 'Evan, please upload 00 other examples', I will reflect and upload them!

Recommended for
these people!

Who is this course right for?

  • People who are new to coding

  • People who want to create a job portfolio

  • People who want to prepare for the Big Data Analysis Technician practical exam

Hello
This is

116

Students

10

Reviews

18

Answers

4.2

Rating

1

Course

안녕하세요,

현재 국민대학교 비즈니스IT전문대학원에서 박사과정을 진행하고 있으며, 취업준비생들의 취업을 진심으로 돕기 위한 강의와 재직자들을 대상으로 R, Python, SQL, Excel, Tableau 등 분석과 관련된 강의로 밥벌이를 하고 있는 Evan입니다. 이제 만 3년이 되었는데, 국방부, 육군본부, 하나금융에서 단기강의로 강의를 시작한 이래로 다양한 기관(한국IT비즈니스협회, 한국능률협회, 한국소프트웨어기술진흥협회, 삼육대 등)에서 강의를 진행하였습니다. 현재는 2023년부터 위 기관 외에도 멀티캠퍼스에서 강의를 하나 맡아서 장기적으로 취업 준비생을 대상으로 교육을 진행하고 있습니다.

Curriculum

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230 lectures ∙ (32hr 58min)

Lecture resources

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