Let, in first Lecture, we will see Unit wise subject introduction
- L1: AI Units Introduction
Fristly, we have to understand difference between data and information
- U1L2: Data Vs Information
- U1L3 -> Now Think Level 1++
What is DIKW Pyramid?, Data vs. Information vs. Knowledge
Are both knowledge and understanding same ?
Are both knowledge and Intelligence different?
Special characteristics of Intelligence behavior, Human Intelligence?
Attributes of Intelligence
What is Artificial Intelligence?, Goals in AI, Kinds of AI
U1L3: Levell 1++
- U1L4 -> Now Think Level 2
Now, we will try to understand little bit - What is AI?
then we wiil see four proposed defination (Human Vs Machine)
and easily understand that AI is a system that act rationally
We will also see the following
View of AI
Defination of AI
Intelligent Agent
AI vs HI
lastly, Programming Without and With AI
U1L4:Think Level 2
Now the time to give answer of following:
- Are Data and Information same?
- What is Full form DIKW Pyramid?
- Is Knowledge below than Understanding?
- Are both Knowledge and Intelligence useless?
- What is meant by Human Intelligence?
- What are Attributes of Intelligence?
- What is Artificial Intelligence?
- What are goals of AI?
- Are there different approaches of Artificial Intelligence?
- Can view of AI?
- What exactly is AI?
- Are you familar with Intelligent (Rational) Agents? Is it hardware?
- Are there no difference between AI and HI?
YES !!!!! I know all answer very well
- U1L5 -> Now Think little more and Level 2++
What Contributes to AI?
History of AI
Applications of AI
U1L5:Think Level 2
Now, you can easily able to explain following with examples:
The Foundation of AI
Philosophy, Mathematics, Economics, Neuroscience, Psychology, Computer Science, Linguistics
History of AI
Inductive Learning, LISP programming language, The resolution proof method for FOL , Perceptrons, Logic theorist, GPS, Perceptron Learning, DENDRAL, LUNAR, R1, FRAMES, Backprop, Belief networks
Applications of AI
Gaming, Natural Language Processing, Expert Systems, Vision Systems, Speech Recognition, Handwriting Recognition,Intelligent Robots
- U1L6-> Now what next in level 3
Structure of Intelligent Agents
What is an Agent & its Environment?
What kind of Agents….?
Agent Terminology
Rationality and its objective
Important Four Factors
What is PEAS?
Nature of Environments
Properties of Environment
U1L6: Now you are in level 3
I think, now you are able to answer following simple question:-
- Define Artificial Intelligence in terms of human performance.
- How the artificial intelligence is different than general intelligence?
- List of principle for success of AI.
- List various issues in knowledge representation
- Elaborate the approaches for AI with example.
- Give any two applications of AI in detail.
- What do you mean by Intelligent Agent ? What are the various types of Intelligent Agent ?
- Elaborate on the agent communication method by action.
- Define Turing test. Is Turing test sufficient to define the operational definition of artificial intelligence?
- U1L7-> Now what next in level 3++
Now, in level 3++, application area NLP
Natural Language Processing (NLP) refers to AI method of communicating with an intelligent systems..
There are two components of NLP - NLU and NLG
Difficulties in NLU
Ambiguity, different in different levels
NLP Terminology
Implementation Aspects
Production Rules
Parse Tree
Left and Right Derivations
U1L7: See more.. Level 3++
- U1L8-> Now what next in level 4++
What are the application of computer vision?
1. Optical character recognition (OCR)
2. Face Detection
3. Smile Detection
4. Object Recognition
5. Vision-Based Biometrics
6. Human shape capture
7. Medical Imaging
The big view of Computer Vision
Human Vision System Vs Computer Vision System
Fields of Computer Vision
History of Computer Vision
U1L7: See more.. Level 4++