About this Course

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Learner Career Outcomes

65%

started a new career after completing these courses

50%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 18 hours to complete
English
Subtitles: English, Vietnamese

Skills you will gain

StatisticsData ScienceInternet Of Things (IOT)Apache Spark

Learner Career Outcomes

65%

started a new career after completing these courses

50%

got a tangible career benefit from this course
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 18 hours to complete
English
Subtitles: English, Vietnamese

Offered by

IBM logo

IBM

Syllabus - What you will learn from this course

Content RatingThumbs Up87%(2,720 ratings)Info
Week
1

Week 1

5 hours to complete

Introduction the course and grading environment

5 hours to complete
2 videos (Total 3 min), 3 readings, 3 quizzes
2 videos
Overview of technology used within the course1m
3 readings
Intro to Apache Spark10m
Assignment and Exercise Environment Setup10m
IMPORTANT: How to submit your programming assignments10m
1 practice exercise
Challenges, terminology, methods and technology2m
Week
2

Week 2

5 hours to complete

Tools that support BigData solutions

5 hours to complete
7 videos (Total 48 min), 2 readings, 4 quizzes
7 videos
Parallel data processing strategies of Apache Spark7m
Programming language options on ApacheSpark10m
Functional programming basics6m
Introduction of Cloudant2m
Resilient Distributed Dataset and DataFrames - ApacheSparkSQL6m
OPTIONAL: Test Data Generator (data is provided for you already)8m
2 readings
Apache Parquet (optional)42m
Create the data on your own (optional)10m
3 practice exercises
Data storage solutions, and ApacheSpark12m
Programming language options and functional programming12m
ApacheSparkSQL and Cloudant12m
Week
3

Week 3

4 hours to complete

Scaling Math for Statistics on Apache Spark

4 hours to complete
7 videos (Total 35 min), 1 reading, 4 quizzes
7 videos
Averages5m
Standard deviation3m
Skewness3m
Kurtosis2m
Covariance, Covariance matrices, correlation13m
Multidimensional vector spaces5m
1 reading
Exercise 210m
3 practice exercises
Averages and standard deviation10m
Skewness and kurtosis10m
Covariance, correlation and multidimensional Vector Spaces16m
Week
4

Week 4

4 hours to complete

Data Visualization of Big Data

4 hours to complete
4 videos (Total 24 min), 2 readings, 2 quizzes
4 videos
Plotting with ApacheSpark and python's matplotlib12m
Dimensionality reduction4m
PCA5m
2 readings
Exercise on Plotting10m
Exercise on PCA10m
1 practice exercise
Visualization and dimension reduction10m

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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

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  • This Course doesn't carry university credit, but some universities may choose to accept Course Certificates for credit. Check with your institution to learn more. Online Degrees and Mastertrack™ Certificates on Coursera provide the opportunity to earn university credit.

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