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.
课程信息
46,542 次近期查看
学生职业成果
67%
完成这些课程后已开始新的职业生涯
57%
通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 4 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
高级
完成时间大约为13 小时
英语（English）
字幕：英语（English）, 法语（French）, 阿拉伯语（Arabic）, 中文（简体）
学生职业成果
67%
完成这些课程后已开始新的职业生涯
57%
通过此课程获得实实在在的工作福利
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 4 门课程（共 4 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
高级
完成时间大约为13 小时
英语（English）
字幕：英语（English）, 法语（French）, 阿拉伯语（Arabic）, 中文（简体）
提供方
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.
教学大纲 - 您将从这门课程中学到什么
完成时间为 3 小时
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
完成时间为 3 小时
1 个视频 （总计 2 分钟）, 7 个阅读材料, 2 个测验
1 个视频
7 个阅读材料
A warm welcome10分钟
Overview of Architectural Methodologies for DataScience10分钟
Lightweight IBM Cloud Garage Method for Data Science10分钟
Data Sources and Use Cases10分钟
Initial Data Exploration10分钟
Architectural Decisions Document (ADD)10分钟
Process Model Guidelines10分钟
1 个练习
Milestones Checklist Week 1
完成时间为 3 小时
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
完成时间为 3 小时
3 个阅读材料
3 个阅读材料
Extract Transform Load (ETL)10分钟
Data Cleansing10分钟
Feature Engineering10分钟
1 个练习
Milestones Checklist Week 2
完成时间为 2 小时
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.
完成时间为 2 小时
2 个阅读材料
2 个阅读材料
Model Definition10分钟
Model Training10分钟
1 个练习
Milestones Checklist Week 3
完成时间为 5 小时
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
完成时间为 5 小时
5 个阅读材料
5 个阅读材料
Model Evaluation10分钟
Model Deployment10分钟
Data Product (optional)10分钟
Create ADD - Architectural Decisions Document10分钟
Create a Video of your final presentation10分钟
2 个练习
Milestones Checklist Week 4
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审阅
来自ADVANCED DATA SCIENCE CAPSTONE的热门评论
由 KW 提供Jul 11, 2019
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.
由 SS 提供Jan 13, 2019
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
由 VT 提供Mar 17, 2019
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!
由 MZ 提供Jan 20, 2020
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!
关于 Advanced Data Science with IBM 专项课程
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.
常见问题
我什么时候能够访问课程视频和作业？
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我订阅此专项课程后会得到什么？
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退款政策是如何规定的？
如果订阅，您可以获得 7 天免费试听，在此期间，您可以取消课程，无需支付任何罚金。在此之后，我们不会退款，但您可以随时取消订阅。请阅读我们完整的退款政策。
有助学金吗？
是的，Coursera 可以为无法承担费用的学生提供助学金。通过点击左侧“注册”按钮下的“助学金”链接可以申请助学金。您可以根据屏幕提示完成申请，申请获批后会收到通知。您需要针对专项课程中的每一门课程完成上述步骤，包括毕业项目。了解更多。
完成课程后，我会获得大学学分吗？
此课程不提供大学学分，但部分大学可能会选择接受课程证书作为学分。查看您的合作院校，了解详情。Coursera 上的在线学位和 Mastertrack™ 证书提供获得大学学分的机会。
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