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Data Science

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Data Analysis

Creating Dashboards Using Python Streamlit (feat. Preparing for Big Data Analytics Engineer Practical Exam)

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.

(4.4) 14 reviews

131 learners

Level Beginner

Course period 12 months

  • Evan
Python
Python
streamlit
streamlit
Scikit-Learn
Scikit-Learn
Pandas
Pandas
Web Crawling
Web Crawling
Python
Python
streamlit
streamlit
Scikit-Learn
Scikit-Learn
Pandas
Pandas
Web Crawling
Web Crawling

Reviews from Early Learners

Reviews from Early Learners

5.0

5.0

hostage5601

100% enrolled

Thank you for the great lecture.

5.0

gy.lyu

5% enrolled

It's helping me a lot.

5.0

nullProperties

100% enrolled

great...

What you will gain after the course

  • Python Machine Learning

  • Python data analysis

  • Python web crawling

  • Python dashboard

  • Big Data Analysis Engineer

Lecture Topics and Objectives 💎

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

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

3. Build a foundation of machine learning and learn about 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 am a person who is learning data analysis for the first time and is in tears, wondering what to do.

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

As a true liberal arts student, I am at a loss as to how to learn data science.

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

This is a look of impatience on the face of a job seeker who wants to create a data analysis portfolio.

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

  • I'm just getting started with data analysis. Beginner

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

  • Job seekers looking to transition into data analysis

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

This is an interview with the instructor, who discussed his motivations for preparing the lecture and his potential for future development. Related books are also included.

This textbook covers a comprehensive approach to implementing various data visualization projects using Streamlit, an open-source Python library . You'll discover a variety of dashboards and examples, covering Python, Pandas, web crawling, Scikit-Learn, Streamlit, and more.

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

*Purchase of textbooks is not required.

👉 Textbook Purchase Link - https://bookk.co.kr/bookStore/67930908f3250118b233df2d (Revised 2nd Edition)

Cumulative sales

What you'll learn in this course 📚

  • Based on the basic Python grammar, 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, and GitHub Actions
Installing, integrating, and using GitHub

Sixth, Google Compute Engine and Google BigQuery

Introducing the structure of this lecture 💻

This course contains various examples using Python Streamlit!

0204_Streamlit_Inflearn

Become a data analyst by sticking to the basic concepts step by step and completing various practical tasks !
In addition to the lectures listed, additional lectures will be uploaded soon. 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

All of them are available for free.

Key Differences from YouTube Video Lectures ✅

While YouTube videos are intended for readers who have purchased the book , the biggest difference is that they don't allow for Q&A from viewers. It's difficult to respond to every single question from readers who haven't 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 not included 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

While YouTube videos are free to view, lecture materials and source code are not provided. Therefore, if you need source code or lecture slides, I strongly recommend taking the course .

💡 Friendly and thorough Q&A

We don't operate comments on YouTube videos. We receive many questions, but it's difficult to answer them all. If you have any questions during this lecture, please ask and we'll do our best to answer them .

A lecture that will continue to develop in the future

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

  • Updated for the second edition (Python classes, new Streamlit features, Cursor AI usage)

  • 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)

  • In addition to Python-related lectures, we will continue to update this site with various lectures essential for employment. Think of them as bonus lectures . We will continue to update the content with a variety of content, not just those contained in the book. We plan to continuously update employment-related content based on student needs.


    • Example: How to Create a GitHub Portfolio and PPT Portfolio

    • Example: Big Data Analyst Practical Exam Scheduled to be Filmed Before May 31, 2024

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


Job seekers!

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

Please check before taking the class!

Programming experience is not necessary because you will learn from the basic grammar.
I hope you will make sure to set aside time to study consistently with this course so that we can grow together.

For better lectures 🍒

🦋 To make the lecture better, 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 other examples', I will reflect it and upload it!

Recommended for
these people

Who is this course right for?

  • A person new to coding

  • Aspiring job portfolio creator

  • Big Data Analyst Engineer Practical Exam Prep

Hello
This is

131

Learners

14

Reviews

18

Answers

4.4

Rating

1

Course

Hello,

I am Evan, currently pursuing a doctoral degree at Kookmin University's Graduate School of Business IT. I make a living by providing lectures to sincerely help job seekers find employment, as well as conducting analysis-related training for professionals in R, Python, SQL, Excel, and Tableau. It has been three full years now since I began with short-term lectures at the Ministry of National Defense, Army Headquarters, and Hana Financial Group, and I have since conducted lectures at various institutions such as the Korea IT Business Association, Korea Management Association, Korea Software Technology Association, and Sahmyook University. Since 2023, in addition to these organizations, I have also been leading long-term training programs for job seekers at Multicampus.

Curriculum

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243 lectures ∙ (34hr 20min)

Course Materials:

Lecture resources
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