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. Please note: You are requested to create a short video presentation at the end of the course. This is mandatory to pass. You don't need to share the video in public.
提供方
学习Course的学生是
- Data Scientists
- Machine Learning Engineers
- Data Analysts
- Data Engineers
- Economists
教学大纲 - 您将从这门课程中学到什么
周
1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
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
周
2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
3 个阅读材料, 2 个测验
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
周
3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.
2 个阅读材料, 2 个测验
2 个阅读材料
Model Definition10分钟
Model Training10分钟
1 个练习
Milestones Checklist Week 3
周
4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
5 个阅读材料, 4 个测验
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
Opt-in to receive your badge!
4.6
22 个审阅60%
完成这些课程后已开始新的职业生涯
50%
通过此课程获得实实在在的工作福利
来自Advanced Data Science Capstone的热门评论
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.
I liked the peer-graded environment.\n\nLike the final submission requirements. That's really helps in aquiring the skills like presentation skills, Documentation skills, project mangement
讲师
Romeo Kienzler
Chief Data Scientist, Course LeadIBM Watson IoT
关于 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.
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？
注册以便获得证书后，您将有权访问所有视频、测验和编程作业（如果适用）。只有在您的班次开课之后，才可以提交和审阅同学互评作业。如果您选择在不购买的情况下浏览课程，可能无法访问某些作业。
我订阅此专项课程后会得到什么？
您注册课程后，将有权访问专项课程中的所有课程，并且会在完成课程后获得证书。您的电子课程证书将添加到您的成就页中，您可以通过该页打印您的课程证书或将其添加到您的领英档案中。如果您只想阅读和查看课程内容，可以免费旁听课程。
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