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Master of Technology in Computer Science and Engineering with Specialization In Artificial Intelligence

Master of Technology in Computer Science and Engineering with Specialization In Artificial Intelligence

at University of Petroleum and Energy Studies India

Overview

In this specialisation, students learn about essential concepts such as data structures, algorithms, OOPS concepts using Java, databases, software engineering and design processes. Students will also obtain an in-depth knowledge of machine learning and artificial intelligence by implementing relevant real-world problems in a wide variety of application domains such as robotics, computer vision, natural language processing, etc. Students will be experienced in machine learning pipeline, data, models, algorithms, and empirics.

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30

Application Processing Days

Under Graduate

Program Level

Fact & Figures

Full Time On Campus

Study Mode

24

Duration

University of Petroleum and Energy Studies

Location

Master of Technology in Computer Science and Engineering with Specialization In Artificial Intelligence Assistant Fee

$225000

Tuition Fee

$NA

Average Cost of Living

$1300

Application Fee

Master of Technology in Computer Science and Engineering with Specialization In Artificial Intelligence Admissions Requirements

Minimum 60% marks at Higher and Senior Secondary level (10th and 12th)

B. Tech/BE in Chemical Engineering/ Chemical Technology/Petro Chemical Engineering/Petroleum Engineering, with minimum 60% marks. Or equivalent

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Detailed Program and Facts

30

Application Processing Days

Full Time On Campus

Program Intensity

Under Graduate

Program Level

24

Duration

Study Visa

In this specialisation, students learn about essential concepts such as data structures, algorithms, OOPS concepts using Java, databases, software engineering and design processes. Students will also obtain an in-depth knowledge of machine learning and artificial intelligence by implementing relevant real-world problems in a wide variety of application domains such as robotics, computer vision, natural language processing, etc. Students will be experienced in machine learning pipeline, data, models, algorithms, and empirics.

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In the upstream oil and gas industry, digital transformation is changing how business is performed. Digital transformation of E&P proprietary data could save the industry as much as $1 billion each year while boosting production up to 8 percent. E&P data stored in warehouses on various old media technologies cannot be accessed on today’s platforms, and that signifying missed opportunities. Oil and gas organizations possess a wealth of subsurface information. Optimal use of E&P data differentiates production plateaus from fresh income-generating insights using historical data. Companies can forego around nearly 8 billion dollars a year in non-productive time as their geologists, geophysicists, engineers, and data managers spend up to 70 percent of  time filtering mountains of well (onshore and offshore) cores, logscans, and subsurface seismic data in many current and defunct software applications and databases.
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Duration

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View All Courses by University of Petroleum and Energy Studies, India

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