Introduction to Artificial Intelligence (AI)
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + srt | Duration: 13 lectures (2h 40m) | Size: 1.37 GB

Define strategy and engagement for Artificial Intelligence solutions
What you'll learn:
What Is AI
Key AI Capabilities and Technology
AI technologies and associated case studies
Components of a AI solution

Requirements
None

Description
As we deal with current data explosive world, much of the data is unstructured - forms, tables, images, and video. As we deal with social interactions in Covid-19, compliance for mask wearing gets added to a number of other image analysis problems.

We have a strong need to analyze large set of unstructured and semi-structured data to interpret the meaning using various AI technology. What are the different types of AI capabilities and associated technologies? How do you select an AI use case and associated technology.

In this course, you will understand

What is AI?

Major capabilities of AI

Various AI technologies and associated use cases

Components of an AI solution

Strategize an AI engagement and associated technologies

This course is divided into multiple sections. After this introductory section,

We will cover what is AI and four major tiers of AI capabilities. In each area, we will identify key technologies and how they drive and transform analytics.

First area is sensing - this includes perception capabilities embedded in our ingestion of speech, images, text, and sensors. We will cover this technology and will also include one case study in this area.

Second area is learning - here we discuss the role of adaptive learning in model improvement as seen today in supervised, unsupervised and reinforcement learning. We will cover this technology and will also include one case study in this area.

Third area is reasoning - our discussion here showcases the role of semantic knowledge representation in developing reasoning capabilities. We will cover this technology and will also include one case study in this area.

Four area is interaction - it covers our use of collaboration in human - machine interaction. We will define key characteristics of this technology and will also include one case study in this area.

Next, we will round up the four capabilities - perception, adaptive learning, semantic knowledge representation and collaboration and show how they have collectively shaped various common life use cases

In last summary section, we will review our findings and provide a set of recommended readings.

The course will cover many interactive quizzes to test your understanding on the subject.

Who this course is for
Business professionals
IT professionals
Senior year undergraduate and graduate students in Business & IT
Vendors, consultants and service providers for AI technology