This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability.
Этот курс входит в специализацию ''Специализация Advanced Data Science with IBM'
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Об этом курсе
Недавно просмотрено: 65,305
Карьерные результаты учащихся
67%
начал новую карьеру, пройдя эти курсы
57%
получил значимые преимущества в карьере благодаря этому курсу
Сертификат, ссылками на который можно делиться с другими людьми
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100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 4 из 4 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Продвинутый уровень
Прибл. 13 часов на выполнение
Английский
Субтитры: Английский, Французский, Арабский, Китайский (упрощенное письмо)
Карьерные результаты учащихся
67%
начал новую карьеру, пройдя эти курсы
57%
получил значимые преимущества в карьере благодаря этому курсу
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 4 из 4 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Продвинутый уровень
Прибл. 13 часов на выполнение
Английский
Субтитры: Английский, Французский, Арабский, Китайский (упрощенное письмо)
от партнера
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.
Программа курса: что вы изучите
3 ч. на завершение
Week 1 - Identify DataSet and UseCase
In this module, the basic process model used for this capstone project is introduced. Furthermore, the learner is required to identify a practical use case and data set
3 ч. на завершение
1 видео ((всего 2 мин.)), 7 материалов для самостоятельного изучения, 2 тестов
1 видео
7 материалов для самостоятельного изучения
A warm welcome10мин
Overview of Architectural Methodologies for DataScience10мин
Lightweight IBM Cloud Garage Method for Data Science10мин
Data Sources and Use Cases10мин
Initial Data Exploration10мин
Architectural Decisions Document (ADD)10мин
Process Model Guidelines10мин
1 практическое упражнение
Milestones Checklist Week 1
3 ч. на завершение
Week 2 - ETL and Feature Creation
This module emphasizes on the importance of ETL, data cleansing and feature creation as a preliminary step in ever data science project
3 ч. на завершение
3 материалов для самостоятельного изучения
3 материала для самостоятельного изучения
Extract Transform Load (ETL)10мин
Data Cleansing10мин
Feature Engineering10мин
1 практическое упражнение
Milestones Checklist Week 2
2 ч. на завершение
Week 3 - Model Definition and Training
This module emphasizes on model selection based on use case and data set. It is important to understand how those two factors impact choice of a useful model algorithm.
2 ч. на завершение
2 материалов для самостоятельного изучения
2 материала для самостоятельного изучения
Model Definition10мин
Model Training10мин
1 практическое упражнение
Milestones Checklist Week 3
5 ч. на завершение
Model Evaluation, Tuning, Deployment and Documentation
One a model is trained it is important to assess its performance using an appropriate metric. In addition, once the model is finished, it has to be made consumable by business stakeholders in an appropriate way
5 ч. на завершение
5 материалов для самостоятельного изучения
5 материалов для самостоятельного изучения
Model Evaluation10мин
Model Deployment10мин
Data Product (optional)10мин
Create ADD - Architectural Decisions Document10мин
Create a Video of your final presentation10мин
2 практических упражнения
Milestones Checklist Week 4
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Рецензии
Лучшие отзывы о курсе ADVANCED DATA SCIENCE CAPSTONE
от партнера KW11 июля 2019 г.
Innovative teacher and course. Learned how to make a youtube video beside the data science challenge. On the whole specialization, very comprehensive and set me up to want to delve further next.
от партнера SS13 янв. 2019 г.
I liked the peer-graded environment. Like the final submission requirements. That's really helps in aquiring the skills like presentation skills, Documentation skills, project mangement
от партнера VT17 мар. 2019 г.
Like that course. It combine all you skills in a one project. It is very helpful for the understanding why and how ML can help for the business. Personal thanks for Romeo Kienzler!
от партнера MZ20 янв. 2020 г.
This is data crunching, varied machine learning model exploring, training, testing, validating and deployment course. What a goldmine for both novices and seasoned and initiated!
Специализация Advanced Data Science with IBM: общие сведения
As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability.
If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging.
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