Despite the recent increase in computing power and access to data over the last couple of decades, our ability to use the data within the decision making process is either lost or not maximized at all too often, we don't have a solid understanding of the questions being asked and how to apply the data correctly to the problem at hand.
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자막: 영어, 스페인어, 페르시아어
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일정에 따라 마감일을 재설정합니다.
초급 단계
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영어
자막: 영어, 스페인어, 페르시아어
제공자:
IBM
IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.
강의 계획 - 이 강좌에서 배울 내용
완료하는 데 4시간 필요
From Problem to Approach and From Requirements to Collection
In this module, you will learn about why we are interested in data science, what a methodology is, and why data scientists need a methodology. You will also learn about the data science methodology and its flowchart. You will learn about the first two stages of the data science methodology, namely Business Understanding and Analytic Approach. Finally, through a lab session, you will also obtain how to complete the Business Understanding and the Analytic Approach stages and the Data Requirements and Data Collection stages pertaining to any data science problem.
완료하는 데 4시간 필요
5개 동영상 (총 19분), 3 개의 읽기 자료, 4 개의 테스트
3개의 읽기 자료
Syllabus10m
Lesson Summary10m
Lesson Summary10m
2개 연습문제
From Problem to Approach30m
From Requirements to Collection30m
완료하는 데 4시간 필요
From Understanding to Preparation and From Modeling to Evaluation
In this module, you will learn what it means to understand data, and prepare or clean data. You will also learn about the purpose of data modeling and some characteristics of the modeling process. Finally, through a lab session, you will learn how to complete the Data Understanding and the Data Preparation stages, as well as the Modeling and the Model Evaluation stages pertaining to any data science problem.
완료하는 데 4시간 필요
6개 동영상 (총 22분), 3 개의 읽기 자료, 4 개의 테스트
6개의 동영상
Data Preparation - Concepts3m
Data Preparation - Case Study4m
Modeling - Concepts3m
Modeling - Case Study4m
Evaluation4m
3개의 읽기 자료
Correction10m
Lesson Summary10m
Lesson Summary10m
2개 연습문제
From Understanding to Preparation30m
From Modeling to Evaluation30m
완료하는 데 2시간 필요
From Deployment to Feedback
In this module, you will learn about what happens when a model is deployed and why model feedback is important. Also, by completing a peer-reviewed assignment, you will demonstrate your understanding of the data science methodology by applying it to a problem that you define.
완료하는 데 2시간 필요
3개 동영상 (총 10분), 2 개의 읽기 자료, 2 개의 테스트
2개의 읽기 자료
Lesson Summary10m
IBM Digital Badge2m
1개 연습문제
From Deployment to Feedback30m
검토
DATA SCIENCE METHODOLOGY의 최상위 리뷰
AG 제공2019년 5월 13일
This is a proper course which will make you to understand each and every stage of Data science methodology. Lectures are well enough to make you think as a data scientist. Thank you fr this course :)
JM 제공2020년 2월 26일
Very informative step-by-step guide of how to create a data science project. Course presents concepts in an engaging way and the quizzes and assignments helped in understanding the overall material.
SJ 제공2018년 8월 8일
This is my favourite in the series, the 10 questions to be answered were mind opening. The repetition after every video makes easier for important points to stick to the brain. Very good indeed...
TX 제공2019년 3월 31일
It just totally rebuilds my mind in thinking about how I should approach solving problems. I feel that I'm learning strong framework for an evidence-based logical approach. Just like a consultant.
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