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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IBM Skills NetworkОб этом курсе
Недавно просмотрено: 270 135
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Сертификат, ссылками на который можно делиться с другими людьми
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100% онлайн
Начните сейчас и учитесь по собственному графику.
Начальный уровень
Прибл. 8 часов на выполнение
Английский
Субтитры: Арабский, Французский, Португальский (Европа), Итальянский, Вьетнамский, Немецкий, Русский, Турецкий, Английский, Испанский, Персидский
Чему вы научитесь
Describe what a methodology is and why data scientists need a methodology.
Apply the six stages in the Cross-Industry Process for Data Mining (CRISP-DM) methodology to analyze a case study.
Determine an appropriate analytic model including predictive, descriptive, and classification models to analyze a case study.
Decide on appropriate sources of data for your data science project.
Приобретаемые навыки
- Data Science
- Data Mining
- Methodology
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Начальный уровень
Прибл. 8 часов на выполнение
Английский
Субтитры: Арабский, Французский, Португальский (Европа), Итальянский, Вьетнамский, Немецкий, Русский, Турецкий, Английский, Испанский, Персидский
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IBM Skills Network
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Программа курса: что вы изучите
3 ч. на завершение
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.
3 ч. на завершение
5 видео ((всего 19 мин.)), 3 материалов для самостоятельного изучения, 4 тестов
3 ч. на завершение
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.
3 ч. на завершение
6 видео ((всего 22 мин.)), 3 материалов для самостоятельного изучения, 4 тестов
2 ч. на завершение
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.
2 ч. на завершение
3 видео ((всего 10 мин.)), 2 материалов для самостоятельного изучения, 3 тестов
Рецензии
- 5 stars71,13 %
- 4 stars21,55 %
- 3 stars4,87 %
- 2 stars1,54 %
- 1 star0,88 %
Лучшие отзывы о курсе DATA SCIENCE METHODOLOGY
от партнера JM26 февр. 2020 г.
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.
от партнера DP5 авг. 2020 г.
This course covers the end to end cycle suggested framework that can be useful not only in Data Science but also in other Research Projects that manage information to create and deploy a solution.
от партнера AP20 янв. 2020 г.
It is a good course, teaching about the general process and life cycle of a data science project. Excellent tips are provided. Overall, I feel it was lacking a bit in content for 3 weeks.
от партнера AM4 июня 2021 г.
A very important course to develop a fundamental understanding of data science. Excellent in-course example to simplify the process of learning (think of it as a recipe in cooking). Enjoyed it.
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