Artificial Intelligence + Machine Learning

Artificial Intelligence + Machine Learning

Rs.4,238.00

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SKU: cid_4140 Category:
Learning Outcomes

After completing this course, you will be able to:

  • Understand the applications of AI (Natural Language Processing, Robotics/Vision).
  • Boost your hireability through innovative and independent learning.
Target Audience

The course can be taken by:

Students: All students who are pursuing any technical/professional courses and interested in learning Artificial Intelligence basics.

Teachers/Faculties: All teachers/faculties who wish to acquire new skills or improve their efficiency in Artificial Intelligence.

Professionals: All working professionals who want to enhance their skills by learning AI concepts.

Why learn Artificial Intelligence?

According to the father of Artificial Intelligence, John McCarthy, Artificial Intelligence is “The science and engineering of making intelligent machines, especially intelligent computer programs”.

As per the latest study, the global market for artificial intelligence is estimated to post an impressive 36.1% CAGR between 2016 and 2024, rising to a valuation of US$3,061.35 billion by the end of 2024 from US$126.14 billion in 2015. The expert system segment was at the forefront of growth in 2015, representing 44% of the overall market revenue, and is poised to maintain its dominance until 2024. Thus, the career prospects are bright for the candidates having the knowledge of Artificial intelligence due to the availability of a few professionals in this field, and the demand in the industry is huge for this technology.

Course Features
  • 24X7 Access: You can view lectures as per your own convenience.
  • Online lectures: 20 hours of online lectures with high-quality videos.
  • Updated Quality content: Content is the latest and gets updated regularly to meet the current industry demands.
Test & Evaluation

Each lecture will have a quiz containing a set of multiple-choice questions. Apart from that, there will be a final test based on multiple-choice questions.

Your evaluation will include the overall scores achieved in each lecture quiz and the final test.

Topics to be covered
  1. Introduction
    • What is AI: Some Definitions?
    • Can Machines Think?
    • What is Arithmetic (as related to AI)?
    • What are some basic ideas in Representation and Reasoning?
  2. Introduction to Knowledge Representation and Reasoning
    • What are some more ideas in Knowledge Representation and reasoning?
    • What is the history of AI (in brief)?
    • What is Physical Symbol system hypothesis?
    • What are some important features of intelligent agents?
  3. An Introduction to Formal Logic
    • What is formal logic?
    • What are the various types of logic?
    • What are the different Types of First Order Logic?
    • What are the Properties of Logic systems?
  4. Propositional Logic: Language, Semantics and Reasoning
    • How is knowledge represented in Propositional Logic?
    • How is reasoning related to Propositional Logic?
    • What is Propositional Language?
    • What is the syntax of Propositional Language?
  5. Propositional Logic: Syntax and Truth Values
    • What are the formulae related to Propositional Language?
    • What are truth values as related to Propositional Logic?
    • How many binary connectives do we need?
    • What are the types of formulae in Propositional Logic?
  6. Propositional Logic: Valid Arguments and Proof Systems
    • Can we look at a proof system in Propositional Logic 1/2?
    • What are the Rules of inference in Propositional Logic?
    • What are the Rules of Substitution in Propositional Logic?
    • Can we look at a proof system in Propositional Logic 2/2?
  7. Propositional Logic: Rules of Inference and Natural Deduction
    • Can we have a recap of Propositional Language?
    • Can we have a recap of Proof systems?
    • What are indirect and direct Proof systems?
    • What are some examples of Proof systems?
  8. Propositional Logic: Axiomatic Systems and Hilbert Style Proofs
    • What is Frege's system as related to Propositional Logic?
    • What are derived rules in Propositional Logic?
    • What are Hilbert Style Proofs in Propositional Logic?
  9. Propositional Logic: The Tableau Method
    • What is the Tableau Method?
    • What are the rules of the Tableau Method?
    • What are some examples of the Tableau Method?
  10. Propositional Logic: The Resolution Refutation Method
    • Can we have a recap of the Tableau Method?
    • What is Resolution Refutation Method?
    • What is the clause form of the Resolution Refutation Method?
    • What is the Tautological Equivalence of the Resolution Refutation Method?
    • Can we look at an example of the Resolution Refutation Method?
  11. Syntax
    • How is First Order Logic different from Propositional Logic?
    • What is the syntax of First Order Logic?
    • What are the set of terms for the First Order Logic?
    • What are the set of formulae for First Order Logic?
    • What are the sentences in First Order Logic?
  12. Semantics
    • What are semantics of the First Order Logic?
    • What is interpretation mapping in First Order Logic?
    • How is truth assignment done to formulae in First Order Logic?
  13. Entailment and Models
    • What are Unary Relations in Semantics of First Order Logic?
    • What are the restrictions of First Order Logic?
    • What are the Entailment and models of First Order Logic?
  14. Proof Systems
    • What are the Rules of inference of First Order Logic?
    • What are the Rules of Substitution of First Order Logic?
    • What is Modus Ponens in First Order Logic?
    • What is Universal Quantifier in Implicit Quantifier Form?
  15. Forward Chaining
    • Can we have a recap of Modified Modus Ponens?
    • What is the Most General Unifier in Modified Modus Ponens?
    • What is the List notation in Unification algorithm?
    • How do we deal with variables, constants and lists in Unification algorithm?
  16. Unification
    • Can we have a recap on dealing with variables, constants and lists in Unification algorithm?
    • Can we look at Example 1 of Unification algorithm?
    • Can we look at Example 2 of Unification algorithm?
    • Can we look at Example 3 of Unification algorithm?
  17. Forward Chaining Rule Based Systems
    • What are Reasoning algorithms in Forward chaining?
    • What is Theorem Proving in Forward Chaining?
    • What are Rules in Forward Chaining?
    • What is Inference engine in Forward Chaining?
  18. The Rete Algorithm
    • How is Rete Algorithm different from match algorithm?
    • What is Discrimination in Rete Network?
    • What is the Assimilative Part in Rete Network?
    • Can we look at an example of Rule in Rete Algorithm?
  19. Rete Algorithm - Example
    • Can we have a recap of the Rete Algorithm?
    • How do we write rules in Rete network?
    • How do we construct the Rete network based on rules?
    • What are rule based expert systems?
  20. Programming in a Rule Based Language
    • How are rule based expert systems used in forward chaining?
    • What are some of the Patterns in Expert systems?
    • What are the Negative Patterns in Expert systems?
  21. The OPS5 Expert System Shell
    • What is OPS5?
    • What are conflict resolution strategies?
    • What is specificity strategy for conflict resolution?
    • Can we look at an example of how conflict resolution strategies work?
  22. Skolemization
    • What is Existential Quantifier in Representation (in FOL)?
    • How is existential quantifier represented in implicit quantifier form?
    • What is skolemisation?
    • How do we identify the nature of a variable?
  23. Terminological Facts
    • What is explicit and implicit form in representation in FOL-I?
    • What is explicit and implicit form in representation in FOL-II?
    • What is recursion in FOL?
    • What are terminological facts?
  24. Properties and Categories
    • How do we represent properties in FOL-I?
    • How do we represent properties in FOL-II?
    • Can we have an introduction of reification?
    • How can we represent abstract ideas?
  25. Reification and Abstract Entities
    • Can we know more about reification?
    • How do we compare and add properties in FOL?
    • How do we represent numbers in FOL?
    • What are numbers?
  26. Resource Description Framework (RDF)
    • What are the problems associated with using ad-hoc predicates?
    • How can we use reification to present events?
    • What is resource description framework?
    • What are resources in RDF?
  27. The Event Calculus: Reasoning About Change
    • What is Event Calculus?
    • What are the predicates in Event Calculus?
    • What are the shortcuts and axioms in Event Calculus?
    • What is the Yale Shooting Problem?
  28. Natural Language Semantics
    • What do we mean by Understanding and Expectations?
    • Can we have an introduction to the CD theory?
    • What are conceptualizations?
    • What are state variables?
  29. CD Theory
    • How do we make inferences using CD theory?
    • What are conceptual cases?
    • What are some CD actions?
    • What are Instruments and state change verbs in CD theory?
  30. CD Theory (contd)
    • How do we model various actions in CD theory-I?
    • How do we model various actions in CD theory-II?
    • How do we model the action "Believe" in CD theory?
    • What are the physical actions that we talk about in CD theory?
  31. English to CD Theory
    • What is conceptual analysis?
    • How do you differentiate between the various senses of a word - and can we look at an example?
    • What is conceptual semantics?
    • What is syntactic ambiguity?
  32. Backward Chaining
    • What is the difference between backward and forward chaining?
    • Can we look at an example of backward chaining?
    • How can we do programming using backward chaining?
    • Can we look at an example of logic programming?
  33. Logic Programming
    • Can we have a recap of logic programming?
    • How do we define addition in logic programming?
    • What are goal trees in Logic programming?
  34. Prolog
    • Can we have a recap of addition in Logic Programming?
    • What are Fibonacci sequence in Logic Programming?
    • How can we make programs more efficient?
    • What is Prolog?
    • Can we look at an example in Prolog?
  35. Search in Prolog
    • Can we look at some efficiency problems in Prolog?
    • How can we make Prolog more efficient?
    • How to make Prolog more efficient - An example I?
    • How to make Prolog more efficient - An example (cont.)?
  36. Controlling Search
    • How do we define the sort function in Logic Programming?
    • How do we define the permutation function in Logic Programming?
    • How do we avoid useless search in Prolog?
    • What is negation by failure in Prolog?
  37. The Cut Operator in Prolog
    • What is the Cut operator in Prolog?
    • What are the different types of cut operator?
    • Can we look example of different types of cut operator?
    • Can we learn more about green cuts?
    • Can we look at an example of green cuts?
  38. Incompleteness
    • Can we have a recap of theorem proving?
    • Can we look at a recap of how to convert formulae into clause form?
    • What is incompleteness of Forward and Backward Chaining?
    • What is the Completeness of Resolution Refutation Method?
  39. The Resolution Method for FOL
    • Can we look at an example of clause form?
    • What are resolution rules?
    • What is the resolution refutation method for FOL?
  40. Clause Form
    • Can we at some properties of the resolution method ?
    • Can we look at an example to illustrate the semidecidability of FOL?
    • How do we use answer prediction method?
    • How do we use answer prediction method-An example?
  41. Artificial Intelligence Part -1 Final Quiz
Note:
  1. Upto six weeks (or till submission of the final quiz) access to the course
  2. To get access to the certificate - you need to take the online exam at the end of the course
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