L&T EduTech

Industrial Applications of AI

This course is part of Intelligent Digital Factories Specialization

Taught in English

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

16 hours (approximately)
Flexible schedule
Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Recently updated!

March 2024

Assessments

5 assignments

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

16 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Intelligent Digital Factories Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 5 modules in this course

By the end of this module, learners will be able to: Understand the ML algorithms such as SVM, KNN, K-means, BERT, Random forest classifier, CNN and Mobile Net V2; Apply ML techniques in diverse real-time applications such as automated vehicle support, fraud system diagnosis, and shop floor management, neural networks for ground water quality analysis, diabetic retinopathy, image classification in IoT, forest fire detection and remotely piloted aircraft case studies

What's included

20 videos2 readings1 assignment1 discussion prompt

By the end of this module, learners will be able to: Apply ML Algorithm in various aspects of electrical engineering, such as load prediction and feature extraction in substations; Analyze the CNN based tasks related to substation analysis, infrastructure management, and infrared fault image diagnosis

What's included

22 videos1 assignment

By the end of this module, learners will be able to: Understand the impact of ML in the oil and gas industry; Interpret seismic data processing techniques, with a focus on salt body delineation using CNN; Demonstrate the process of geomodelling based on the Gaussian process regression algorithm; Examine AI applications in the upstream sector of the oil and gas industry; Infer the Service-Oriented Architecture (SOA) of big data for the oil and gas industry

What's included

18 videos1 assignment

By the end of this module, learners will be able to: Understand a generic ML modeling framework for civil engineering applications; Apply deep learning techniques in construction sites, with a focus on recycled cement strength prediction; Analyze the diverse ML application areas such as transport engineering, road traffic prediction, naval architecture, and wave height forecasting, using deep learning algorithms like ANN, CNN, and YOLO architecture

What's included

22 videos1 assignment

By the end of this module, learners will be able to: Understand the impact of AI in education; Interpret open-source AI software libraries such as H2O, ImageAI, OpenAI Gym, Keras, TensorFlow, PyTorch, and Scikit-learn; Demonstrate computer vision techniques for car object detection using YOLO; Infer the language and language reasoning in AI with an application of language identification in text; Investigate AI-based speech recognition technology in the healthcare sector for heart disease prediction; Explain policies and strategies related to AI adoption and implementation

What's included

19 videos1 assignment

Instructor

Subject Matter Expert
L&T EduTech
15 Courses14,961 learners

Offered by

L&T EduTech

Recommended if you're interested in Support and Operations

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