Data Analytics and Artificial Intelligence for Manufacturing Engineers(Synchronous e-learning)
Training Provider: NATIONAL UNIVERSITY OF SINGAPORE
Course Reference: TGS-2020505954
S$855
Original: S$2,850
Save S$1,995
About This Course
"With the advent of Industry 4.0, modern day manufacturing facilities are increasingly equipped with smart technologies that allow for large data collection, efficient data sharing, advanced analytics and increased automation.
In this course, we introduce basic concepts in data analytics and artificial intelligence with a focus on applications that engineers commonly deal with under a manufacturing setting, including inventory management, quality control and predictive maintenance.
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What You'll Learn
"The course will first provide overview on how data analytics can be used to identify trends and patterns, yielding beneficial insights on various aspects of the production process. Second, we introduce machine learning models that can be used to perform predictions and classifications that can aid decision making. Third, we illustrate how these methods can be further extended to develop autonomous systems that are capable of making operational decisions.
At the end of this course, participants will have a good overview of data analytics and artificial intelligence. In addition, they will understand how advanced analytics can lead to higher productivity, lower costs, increased reliability, faster response and greater automation, thereby gaining a better appreciation of how advances in these fields are changing modern day manufacturing facilities.
1. Descriptive and inferential statistics
2. Regression
3. Neural networks and Markov decision processes"
At the end of this course, participants will have a good overview of data analytics and artificial intelligence. In addition, they will understand how advanced analytics can lead to higher productivity, lower costs, increased reliability, faster response and greater automation, thereby gaining a better appreciation of how advances in these fields are changing modern day manufacturing facilities.
1. Descriptive and inferential statistics
2. Regression
3. Neural networks and Markov decision processes"
Entry Requirements
A basic background in mathematics, statistics and probability is assumed. Basic familiarity with Microsoft Excel is also expected. This course will involve simple Python programming. Prior computer programming experience is helpful, but not required.
Course Details
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Note: To apply for this course, visit the SkillsFuture website or contact the training provider directly.
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