Introduction to Artificial Intelligence AI - Institute of Business and Technology

About Course

Introduction to Artificial Intelligence AI

Course Content

Lesson 1. Course Introduction

Course Introduction

00:00

Lesson 2. Decoding Artificial Intelligence

Decoding Artificial Intelligence

00:00
Meaning, Scope, and Stages Of Artificial Intelligence

00:00
Three Stages of Artificial Intelligence

00:00
Applications of Artificial Intelligence

00:00
Image Recognition

00:00
Applications of Artificial Intelligence – Examples

00:00
Effects of Artificial Intelligence on Society

00:00
Supervises Learning for Telemedicine

00:00
Solves Complex Social Problems

00:00
Benefits Multiple Industries

00:00
Key Takeaways

00:00
Knowledge Check

00:00

Lesson 3. Fundamentals Of Machine Learning and Deep Learning

Fundamentals Of Machine Learning and Deep Learning

00:00
Meaning of Machine Learning

00:00
Relationship between Machine Learning and Statistical Analysis

00:00
Process of Machine Learning

00:00
Types of Machine Learning

00:00
Meaning of Unsupervised Learning

00:00
Meaning of Semi-supervised Learning

00:00
Algorithms of Machine Learning

00:00
Regression

00:00
Naive Bayes

00:00
Naive Bayes Classification

00:00
Machine Learning Algorithms

00:00
Deep Learning

00:00
Artificial Neural Network Definition

00:00
Definition of Perceptron

00:00
Online and Batch Learning

00:00
Key Takeaways

00:00
Knowledge Check

00:00

Lesson 4. Machine Learning Workflow

Learning Objective

00:00
Machine Learning Workflow

00:00
Get more data

00:00
Ask a Sharp Question

00:00
Add Data to the Table

00:00
Check for Quality

00:00
Transform Features

00:00
Answer the Questions

00:00
Use the Answer

00:00
Key takeaways

00:00
Knowledge Check

00:00

Lesson 5. Performance Metrics

Performance Metrics

00:00
Need For Performance Metrics

00:00
Key Methods Of Performance Metrics

00:00
Confusion Matrix Example

00:00
Terms Of Confusion Matrix

00:00
Minimize False Cases

00:00
Minimize False Positive Example

00:00
Accuracy

00:00
Precision

00:00
Recall Or Sensitivity

00:00
Specificity

00:00
F1 Score

00:00
Key takeaways

00:00
Knowledge check

00:00

About Course

Course Content

Lesson 1. Course Introduction

Course Introduction

Lesson 2. Decoding Artificial Intelligence

Decoding Artificial Intelligence

Meaning, Scope, and Stages Of Artificial Intelligence

Three Stages of Artificial Intelligence

Applications of Artificial Intelligence

Image Recognition

Applications of Artificial Intelligence – Examples

Effects of Artificial Intelligence on Society

Supervises Learning for Telemedicine

Solves Complex Social Problems

Benefits Multiple Industries

Key Takeaways

Knowledge Check

Lesson 3. Fundamentals Of Machine Learning and Deep Learning

Fundamentals Of Machine Learning and Deep Learning

Meaning of Machine Learning

Relationship between Machine Learning and Statistical Analysis

Process of Machine Learning

Types of Machine Learning

Meaning of Unsupervised Learning

Meaning of Semi-supervised Learning

Algorithms of Machine Learning

Regression

Naive Bayes

Naive Bayes Classification

Machine Learning Algorithms

Deep Learning

Artificial Neural Network Definition

Definition of Perceptron

Online and Batch Learning

Key Takeaways

Knowledge Check

Lesson 4. Machine Learning Workflow

Learning Objective

Machine Learning Workflow

Get more data

Ask a Sharp Question

Add Data to the Table

Check for Quality

Transform Features

Answer the Questions

Use the Answer

Key takeaways

Knowledge Check

Lesson 5. Performance Metrics

Performance Metrics

Need For Performance Metrics

Key Methods Of Performance Metrics

Confusion Matrix Example

Terms Of Confusion Matrix

Minimize False Cases

Minimize False Positive Example

Accuracy

Precision

Recall Or Sensitivity

Specificity

F1 Score

Key takeaways

Knowledge check