Who Should Take This Course?

This course is designed for experienced IT professionals, including Test Officers, Engineers and IT specialists.

What You Will Learn in This Course

Upon completion of this course, students will be able to:

• Learn the importance of data
• Know the methods used by AI tools to retrieve data from various sources
• Match a data set with the most promising inductive learning algorithms
• Train the machine with the given data to derive a particular conclusion
• Recognize the methods used to determine the best result
• Understand classification of data

Example-based “No Code” Learning focused on AI, Machine, & Deep Learning:

• Selecting Source Data: Determining the best Data Source for a given task
• Preprocessing Data: Integration, transformation, reduction, and cleaning
• Data Wrangling: Data Leakage and Deep Learning
• Data Smoothing: Missing, noisy, and inconsistent data
• Image Processing: Categories of images and their classification
• Image Processing Methods: Examples and strategies used in AI
• Image Processing Techniques: Rotation, Translation, Color, Zooming, & Flipping
• Image Recognition: Pixel, Image Type, Iterators, Code Execution & Result Processing
• Deep Learning: Defined
• Image Processing Algorithm CNN: Layers of CNN; Convolutional, Pooling, and Fully-Connected
• Object Recognition: Using MNIST for handwritten digit recognition
• Intelligent Document Processing (IDP) & Deep Neural Networks for Image Processing: Analog and Digital Image Processing
• Image Processing Phases: Acquisition, Enhancement, Restoration, Processing, Recognition, Representation & Description

Paying for Your Class

Discounted pricing is available for military-connected learners, University of Arizona alumni and others.

We can also work with your employer's tuition assistance, reimbursement or other education assistance program to fund your training.