Data Science

what is Data Science?

• Data Science is a field that users statistical and computational methods to extract insights and knowledge from data.

• Data Science involves a variety of tecniques, such as data cleaning, data visualization, machine learning, and statistical modeling, to analyze and interpret data.

The Role of the Data Scientist

• Extracting insights and knowledge from data.
  This involves collecting, cleaning, and analyzing large and complex datasets

• developing and implementing models and algorithms to solve complex problems.
  creating visualizations and reports to communicate their findings

• use data to inform decision-making and drive value for the organization

Statistics VS Data Science

• Statistics :
  • Mathematical science for analyzing existing data
  • Determine cause-and-effect relationship in analyzed data
• Data Science :
  • Branch of computer science sed to gain valuable information
  • Identify underlying trends and patterns in data for decision making

Artificial Intelligence VS Data Science

• Artificial Intelligence :
  • Focus on the simulation of human intelligence processes by smart machines programmed to think like humans and mimic ther actions
• Data Science :
  • Multidiscliplinary field focuses on drawing insights that can help an organization make better decisions
  • Huge volume of data ➡️ Identify hidden patterns in data
    

Data Science Progress

• Defining Problems : 문제 이해 및 정의

  • Start by accurately understanding and defining the problems

• Understanding Data : 데이터의 이해 (데이터 준비, 탐색, 변환, 정리)

  • Data preparation, collection, transform, and organization

• Model & Algorithm : 모델링 (모델 선택, 알고리즘 학습)

  • The process of learning and applying various algorithms and methodologies to the collected data

• Model Test(Validation) : 모델 테스트 (최적화, 튜닝)

  • Testing the accuracy of the selected methodology and optimizing through repeated adjustments

• Distribution : 배포 (업데이트, 모니터링)

  • Monitoring, re-training, and update

Data Science Applications

• Customer behavior analysis
• Fraud(사기) detectoin
• Healthcare
• Smart factory / Manufacturing
• Marketing
• Sports

Summary

Data Science

• Data Science

  • An interdiscliplinary academic field
  • Extract knowledge and insight from data
  • Complementary relationship between other fields

• Data Science Process

  • Problem
  • Data
  • Model & Algorithm
  • Validation
  • Distribution

• Data Science Applications

  • Industry, healthcare, finance, and so on