Machine Learning For Engineering : A-Z

AI For Engineering Applications: A-Z

4.36 (7 reviews)
Udemy
platform
English
language
Other
category
Machine Learning For Engineering : A-Z
36
students
12 hours
content
Apr 2023
last update
$19.99
regular price

What you will learn

Understand the needed AI for Engineering Applications

How to Code an Optimize model from scratch

How to Code a K-Means Clustering from scratch

How to Code a Q table Reinforcement Learning Engine from Scratch

Use Google Or-Tools to optimize a plant scheduling problem.

Use OpenAI baselines library to solve a control problem.

Use Keras to construct a U-net neural network to segment (outline) a crack on a surface.

Predict machine failure using real aircraft engine data.

Why take this course?

Description

This is a complete course that will prepare you to use Machine Learning in Engineering Applications from A to Z. We will cover the fundamentals of Machine Learning and its applications in Engineering Companies, focusing on 4 types of machine learning: Optimization, Structured data, Reinforcement Learning, and Machine Vision.


What skills will you Learn:

In this course, you will learn the following skills:

  • Understand the math behind Machine Learning Algorithms.

  • Write and build Machine Learning Algorithms from scratch.

  • Preprocess data for Images, Reinforcement learning, structured data, and optimization.

  • Analyze data to extract valuable insights.

  • Use opensource libraries.


We will cover:

  • Fundamentals of Optimization and building optimization algorithms from scratch.

  • Use Google OR Tools optimization library/solver to solve Shop job problems.

  • Fundamentals of Structured Data processing algorithms and building data clustering using K-Nearest Neighbors algorithms from scratch.

  • Use scikit-learn library along with others to predict the Remaining Useful Life of Aircraft Engines (Predictive maintenance).

  • Fundamentals of Reinforcement Learning and building Q-Table algorithms from scratch.

  • Use Keras & Stable baselines libraries to control room temperature and construct a custom-made Environment using OpenAI Gym.

  • Fundamentals of Deep Learning and Networks used in deep learning for machine vision inspection.

  • The use of TensorFlow/ Keras to construct Deep Neural Networks and process images for Classification using CNN (images that have cracks and images that do not) and crack Detection and segmentation using U-Net (outline the crack location in every crack image).

If you do not have prior experience in Machine Learning or Computational Engineering, that's no problem. This course is complete and concise, covering the fundamentals of Machine Learning followed by using real data with strong opensource libraries needed to apply AI in Companies. Let's work together to fulfill the need of companies to apply Machine Learning in Engineering applications to MAKE OUR FUTURE ENGINEERING PRODUCTS SMARTER.

Screenshots

Machine Learning For Engineering : A-Z - Screenshot_01Machine Learning For Engineering : A-Z - Screenshot_02Machine Learning For Engineering : A-Z - Screenshot_03Machine Learning For Engineering : A-Z - Screenshot_04

Charts

Price

Machine Learning For Engineering : A-Z - Price chart

Rating

Machine Learning For Engineering : A-Z - Ratings chart

Enrollment distribution

Machine Learning For Engineering : A-Z - Distribution chart
5161264
udemy ID
2/16/2023
course created date
4/3/2023
course indexed date
Bot
course submited by