About this Course
Specialization

Course 4 of 5 in the

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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.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 12 hours to complete

Suggested: 2- 5 hours per week...
Available languages

English

Subtitles: English
Specialization

Course 4 of 5 in the

100% online

100% online

Start instantly and learn at your own schedule.
Flexible deadlines

Flexible deadlines

Reset deadlines in accordance to your schedule.
Intermediate Level

Intermediate Level

Hours to complete

Approx. 12 hours to complete

Suggested: 2- 5 hours per week...
Available languages

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
Hours to complete
25 minutes to complete

GETTING STARTED

...
Reading
1 video (Total min), 2 readings
Reading2 readings
Best Practices for Online Learning10m
Learning Journey Syllabus10m
Week
2
Hours to complete
2 hours to complete

Data Management in MapReduce Systems

...
Reading
7 videos (Total 41 min), 7 readings, 1 quiz
Video7 videos
MapReduce: How it Works4m
HDFS3m
MapReduce Programming Model3m
Visualization of MapReduce System10m
MapReduce Execution Details5m
Operators in MapReduce8m
Reading7 readings
Introduction to MapReduce10m
How Does MapReduce Work?10m
Introduction to Hadoop File System (HDFS)10m
MapReduce Programming Model10m
Visualization of MapReduce System10m
MapReduce Execution Details10m
Operators in MapReduce10m
Quiz1 practice exercise
Knowledge Check: Data Management in MapReduce Systems30m
Week
3
Hours to complete
5 hours to complete

Data Management in Apache Spark and Apache Hadoop

...
Reading
3 videos (Total 58 min), 3 readings, 1 quiz
Video3 videos
Spark Ecosystem18m
Common Components of Apache Hadoop10m
Reading3 readings
Apache Spark RDD Data Processing System10m
Apache Spark Ecosystem10m
Common Components of Apache Hadoop10m

Instructor

Avatar

Mohamed Sarwat

Assistant Professor
Computer Science and Engineering

About Arizona State University

Arizona State University has developed a new model for the American Research University, creating an institution that is committed to excellence, access and impact. ASU measures itself by those it includes, not by those it excludes. ASU pursues research that contributes to the public good, and ASU assumes major responsibility for the economic, social and cultural vitality of the communities that surround it....

About the Data Systems Specialization

Database systems are used to provide convenient access to disk-resident data through efficient query processing, indexing structures, concurrency control, and recovery. This specialization delves into new frameworks for processing and generating large-scale datasets with parallel and distributed algorithms. Courses cover the design, deployment and use of state-of-the-art data processing systems, which provide scalable access to data. All courses in this Specialization form the lecture and skill practice component of a corresponding course in ASU’s online Master of Computer Science Degree. You can apply to the degree program either before or after you begin the Specialization....
Data Systems

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.