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This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource... Read more
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource for nations’ advancement. Organizations increasingly heavily on sophisticated analytical tools to draw meaningful insights from data in order for their businesses to thrive.
This program focuses on the analysis and handling of data from multiple sources and for various applications in order to draw inferences from it. Topics include probability theory, inference, least-square and maximum likelihood estimation, forecasting, finding local and global optimal solutions (gradient descent, genetic algorithms, etc.), and generalized additive models. It also covers machine deep learning topics such as classification, conditional probability estimation, clustering, dimensionality reduction, and decision support systems. The program also covers big data analysis, including big data collection, preparation, preprocessing, warehousing, interactive visualization, analysis, scrubbing, mining, management, modeling, and tools such as Hadoop, Map-Reduce, Apache Spark, etc.
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource... Read more
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource for nations’ advancement. Organizations increasingly heavily on sophisticated analytical tools to draw meaningful insights from data in order for their businesses to thrive.
This program focuses on the analysis and handling of data from multiple sources and for various applications in order to draw inferences from it. Topics include probability theory, inference, least-square and maximum likelihood estimation, forecasting, finding local and global optimal solutions (gradient descent, genetic algorithms, etc.), and generalized additive models. It also covers machine deep learning topics such as classification, conditional probability estimation, clustering, dimensionality reduction, and decision support systems. The program also covers big data analysis, including big data collection, preparation, preprocessing, warehousing, interactive visualization, analysis, scrubbing, mining, management, modeling, and tools such as Hadoop, Map-Reduce, Apache Spark, etc.
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
Data Science and Analytics
KFUPM Main Campus, Dhahran, Saudi Arabia
# =84QS Subject Rankings
24 monthsProgram duration
MathematicsMain Subject Area
Programme overview
Main Subject
Mathematics
Degree
MSci
Study Level
Masters
Study Mode
On Campus
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource...
Read more
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource for nations’ advancement. Organizations increasingly heavily on sophisticated analytical tools to draw meaningful insights from data in order for their businesses to thrive.
This program focuses on the analysis and handling of data from multiple sources and for various applications in order to draw inferences from it. Topics include probability theory, inference, least-square and maximum likelihood estimation, forecasting, finding local and global optimal solutions (gradient descent, genetic algorithms, etc.), and generalized additive models. It also covers machine deep learning topics such as classification, conditional probability estimation, clustering, dimensionality reduction, and decision support systems. The program also covers big data analysis, including big data collection, preparation, preprocessing, warehousing, interactive visualization, analysis, scrubbing, mining, management, modeling, and tools such as Hadoop, Map-Reduce, Apache Spark, etc.
Read lessProgramme overview
Main Subject
Mathematics
Degree
MSci
Study Level
Masters
Study Mode
On Campus
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource...
Read more
This multidisciplinary program prepares professionals for a career in turning data into useful information, a discipline substantially demanded in the job market, as data is generated by the quintillion of bytes every day and is becoming a precious resource for nations’ advancement. Organizations increasingly heavily on sophisticated analytical tools to draw meaningful insights from data in order for their businesses to thrive.
This program focuses on the analysis and handling of data from multiple sources and for various applications in order to draw inferences from it. Topics include probability theory, inference, least-square and maximum likelihood estimation, forecasting, finding local and global optimal solutions (gradient descent, genetic algorithms, etc.), and generalized additive models. It also covers machine deep learning topics such as classification, conditional probability estimation, clustering, dimensionality reduction, and decision support systems. The program also covers big data analysis, including big data collection, preparation, preprocessing, warehousing, interactive visualization, analysis, scrubbing, mining, management, modeling, and tools such as Hadoop, Map-Reduce, Apache Spark, etc.
Read lessAdmission Requirements
Scholarships
Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.
To help students navigate this challenging process, we recommend the following articles:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
QS subject rankings
Subject: Mathematics
Ranking criteria
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