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Data Science

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Data Analysis

Practical Python Data Analysis: Basic to Practical

From Python fundamentals to practical data analysis! You will learn practical Python skills for processing, visualizing, and analyzing data while solving business problems.

11 learners are taking this course

  • DataScienceOne
파이썬기초강의
이론 실습 모두
파이썬데이터
Python
Pandas
Matplotlib
Seaborn
data-visualization

What you will learn!

  • Python Environment Setup and Installing Required Libraries

  • Data Type Conversion and Formatting Mastery

  • Efficient Data Manipulation and Cleaning Using Pandas

  • Understanding various Join techniques for connecting multiple datasets

  • Learning Data Aggregation and Feature Engineering Techniques

  • Effectively handle date and time data with Python

  • Customized Data Visualization Using Matplotlib and Seaborn

  • Capstone Project: E-commerce Data Analysis and Visualization


"Is Python difficult and you don't know where to start?"
“Do you want to learn the data analysis process all at once?”

In this course, you will learn techniques to collect, organize, analyze, and visualize data using the powerful features of Python. This is a hands-on course that even beginners can easily follow.


Specific outcomes you will achieve through this course

Organized dataset
You can use Pandas to effectively organize data and quickly transform and refine the data you need.

Practical analysis and insight generation
You can explore data and derive statistical insights by leveraging Python's various libraries.

Attractive data visualization
Matplotlib and Seaborn help you visually express hidden patterns and insights in your data.

Practical project experience
You will gain hands-on experience with practical projects such as analyzing e-commerce data, sales trends, and customer behavior.


Why should I take this course?

💡 Python is the most widely used language for data analysis.
It's a powerful tool that even coding beginners can easily learn and use.

💡 It is structured as a practice-oriented project.
You can acquire skills that can be applied directly to practical work.

💡 You can learn the entire process of data collection, cleaning, analysis, and visualization.
Master the entire process of data analysis in one lecture!

🔥 Features of this course 🔥

1. Balanced composition of 50% theory and 50% practice

2. Project-based learning using real business data

3. A step-by-step learning process that systematically builds Python skills.

4. Provides various practical examples and datasets

I recommend this to these people


Workers who need skills to extract and analyze data



Students and entry-level analysts who want to learn efficient data processing with Python



Beginners interested in data science and data engineering


Data analysis using Python that anyone can easily learn - from beginner to practical!

This course is composed of 50% theory and 50% practice, so you can learn step by step. Through various practical examples, you will learn how to analyze data with Python and acquire skills that can be applied immediately in practice.

After taking this course, you will be able to:

Data collection and purification
Leverage Python's powerful libraries to collect, process, and refine data from the web, making it ready for analysis.

Data analysis and visualization
Analyze data with Pandas and visually express insights with Matplotlib and Seaborn.

Report creation and automation
You can efficiently organize analysis results and automate repetitive tasks with Python code to create reports.

Practical project implementation
You can gain practical experience by working on projects such as analyzing customer behavior and identifying sales trends based on actual business data.

#Python #Pandas #data-visualization #matplotlib #seaborn

Learn about these things.

1⃣ Data collection and refinement
Learn how to load and clean data using Python libraries (e.g. Pandas).

2⃣ Data Analysis and Problem Solving
Learn techniques to use Python to analyze data and derive useful insights for problem solving.

3⃣ Data Visualization
Learn how to visually represent data and communicate results effectively with Matplotlib and Seaborn.

4⃣ Practical-oriented projects
We systematically carry out the analysis process and complete the project results by utilizing actual business data.

Introducing the knowledge sharer (instructor)

Education:

  • Master of Health Informatics (University of Toronto)

  • Bachelor of Science in Medical Physics (Western University)

personal history:

  • Dec 2018 - Present: Ontario Workers Compensation Corporation - Senior Data Analyst

  • Sep 2015 - Mar 2018: CAMH Hospital - Lead Business Intelligence QA Analyst


bailiwick:

  • Business Intelligence / Data Modeling

  • Business Analysis / Data Analysis

  • Data Visualization / Product Development


Personal YouTube Channel:

  • Founder of YouTube Channel Data Science One


Things to note before taking the class

💻 Class environment information

  • Operating System and Version (OS) : 64-bit Windows 7, 8.1, 10 or macOS

  • Tools used : Anaconda installation (Python operation: Spyder IDE utilization)

  • PC specifications : A computer with minimum performance to run Python.

  • Target Audience : The course is structured so that even those with no programming experience can follow along, but an understanding of basic data structures will help you learn more smoothly.

Learning Materials

  • Download Materials : All materials are provided in the [Section 0. Download Lecture Package] for practice materials.

  • Hands-on examples and datasets : Problems designed based on real business data

  • Templates : Python code practice examples, capstone project templates

  • Solution: Python code practice examples, capstone project model answers


Player Knowledge and Notes

  • Requires Python installation and setup :


    You can install the Anaconda package (free).

  • Structured so that even those without programming experience can easily follow along

  • Unauthorized distribution of lecture materials is prohibited: The materials in this lecture are copyrighted, so please be careful not to distribute them without permission.

Recommended for
these people

Who is this course right for?

  • Office worker preparing for a career change with skills beyond Excel

  • Beginners new to tools like Python or R

  • New graduate interested in data analysis

  • Learner of data analysis and business data visualization

Need to know before starting?

  • Requirements: None, structured so beginners can easily follow

  • Recommended: Basic Excel experience

Hello
This is

78

Learners

8

Reviews

5

Answers

3.9

Rating

4

Courses

데이터싸이언스원 | Taesun Yoo

링크딘 프로필 강사소개 [클릭]

주요 경력:

  • 온타리오주 근로자 보험 공단 (WSIB) 시니어 어드바이저 (1년)

  • 온타리오주 근로자 보험 공단 (WSIB) 시니어 데이터 분석가 (경력 5년)


학력:

  • 토론토 대학교: 보건 정보학 석사

  • 웨스턴 대학교: 의학 물리학 학사


전문 분야:

Data Analytics/Data Modeling/Business Analysis

Business Intelligence/Data Visualization/Product Development (Power BI)


기타: 데이터싸이언스원 유튜브 채널 [클릭]

  • 데이터 분석가로 취업에 도움이 되는 팁, 짧은 데이터 분석 포트폴리오, 유데미 코스 프로모션 등을 목적으로 강의를 업로드하고 있습니다!


10년 이상의 경력과 노하우를 바탕으로, 북미에서 데이터 분석가로 취업을 원하시는 분들을 위해 기술을 갈고 닦을 수 있게 강의를 만들고 있습니다. 기초부터 실제 기업에서 사용하는 응용 문제(Use Cases)까지 다루고 있습니다.

Curriculum

All

103 lectures ∙ (14hr 18min)

Course Materials:

Lecture resources
Published: 
Last updated: 

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$44.00

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