About this Course
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7 ratings
3 reviews
Specialization
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100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Advanced Level

Advanced Level

Hours to complete

Approx. 14 hours to complete

Suggested: 5 hours/week...
Available languages

English

Subtitles: English, French...
Specialization
100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Advanced Level

Advanced Level

Hours to complete

Approx. 14 hours to complete

Suggested: 5 hours/week...
Available languages

English

Subtitles: English, French...

Syllabus - What you will learn from this course

Week
1
Hours to complete
3 hours to complete

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...
Reading
1 video (Total 2 min), 6 readings, 2 quizzes
Video1 video
Reading6 readings
A warm welcome10m
Overview of Architectural Methodologies for DataScience10m
Lightweight IBM Cloud Garage Method for Data Science10m
Data Sources and Use Cases10m
Initial Data Exploration10m
Architectural Decisions Document (ADD)10m
Quiz1 practice exercise
Milestones Checklist Week 1m
Week
2
Hours to complete
3 hours to complete

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 ...
Reading
3 readings, 2 quizzes
Reading3 readings
Extract Transform Load (ETL)10m
Data Cleansing10m
Feature Engineering10m
Quiz1 practice exercise
Milestones Checklist Week 2m
Week
3
Hours to complete
2 hours to complete

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. ...
Reading
2 readings, 2 quizzes
Reading2 readings
Model Definition10m
Model Training10m
Quiz1 practice exercise
Milestones Checklist Week 3m
Week
4
Hours to complete
5 hours to complete

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 ...
Reading
5 readings, 3 quizzes
Reading5 readings
Model Evaluation10m
Model Deployment10m
Data Product (optional)10m
Create ADD - Architectural Decisions Document10m
Create a Video of your final presentation10m
Quiz1 practice exercise
Milestones Checklist Week 4m

Instructor

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT

About 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....

About the Advanced Data Science with IBM Specialization

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....
Advanced Data Science with IBM

Frequently Asked Questions

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

More questions? Visit the Learner Help Center.