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Semester 3MCA301

Artificial Intelligence (MCA301) crash course, Online MCA, Semester 3:

This subject introduces the core ideas of Artificial Intelligence: how problems are represented, how search and heuristic algorithms like A* and AO* find…

  • 18 video lessons
  • 4h 12m
  • Study notes
  • 75 quiz questions
  • Assignment
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Artificial Intelligence crash course

18 lessons in Artificial Intelligence

Each lesson pairs one topic with a hand-picked video, trimmed to the part that teaches it.

About this subject

This subject introduces the core ideas of Artificial Intelligence: how problems are represented, how search and heuristic algorithms like A* and AO* find solutions, and how knowledge is expressed using propositional and predicate logic. You will be able to formulate problems as state spaces, choose and trace suitable search techniques, write logical representations of knowledge, and explain the basics of fuzzy logic, neural networks, NLP, expert systems and AI languages like LISP and Prolog.

  1. 1

    What is Artificial Intelligence and Why It Matters

    Module I, Introduction: AI and its importance

    Lec-3: What is Artificial Intelligence | Learn AI with Real Life Examples | Can Machine Think??· Gate Smashers· 9 min

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  2. 2

    AI Problems and Application Areas

    Module I, Introduction: AI Problem, Application area

    Introduction to ARTIFICIAL INTELLIGENCE (AI) || AI problems|| (Hindi- Eng) explanation· Rahit Rhymes· 8 min

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  3. 3

    State Space Representation in AI

    Module II, Problem Representations: State space representation

    Lec-4: What is State Space Search | Introduction to Problem Solving in Artificial Intelligence· Gate Smashers· 9 min

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  4. 4

    Problem Reduction Representation (AND-OR Graphs)

    Module II, Problem Representations: problem-reduction representation

    Problem Reduction | Problem Representation in AI - Kanika Vats· Kanika Vats· 8 min

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  5. 5

    Production Systems: Characteristics and Types

    Module II, Problem Representations: production system, production system characteristics, types of production system

    L38: Production System in Artificial Intelligence | Characteristics, Advantages, Steps to Solve· Easy Engineering Classes· 8 min

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  6. 6

    Uninformed Search: Brute Force, DFS and BFS

    Module III, Heuristic Search Techniques: AI and search process, brute force search, depth-first search, breadth-first search, time and space complexities

    2.1 Uninformed Search Algorithms | BFS | DFS | Depth Limited Search | Bidirectional Search· KnowledgeGATE Bytes· 20 min

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  7. 7

    Heuristic Search and Hill Climbing

    Module III, Heuristic Search Techniques: heuristics search, hill climbing

    Lec-19: Hill Climbing Algorithm in Artificial Intelligence with Real Life Examples| Heuristic Search· Gate Smashers· 10 min

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  8. 8

    Best First Search and A* Algorithm

    Module III, Heuristic Search Techniques: best first search, A*

    2.2 Heuristic(Informed) search in Artificial Intelligence | Best First Search | A* Search | AO* Sear· KnowledgeGATE Bytes· 19 min

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  9. 9

    AO* Algorithm

    Module III, Heuristic Search Techniques: AO* algorithm

    Lec-22: AO* algorithm in AI (artificial intelligence) in HINDI | AO* algorithm with example· Gate Smashers· 13 min

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  10. 10

    Constraint Satisfaction and Beam Search

    Module III, Heuristic Search Techniques: constraint satisfaction, beam search

    Lec-39: What is Constraint Satisfaction | Constraint Satisfaction Problem (CSP) in AI with Example· Gate Smashers· 8 min

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  11. 11

    Knowledge Representation: Mapping and Mechanisms

    Module IV, Knowledge Representation issues using predicate logic: Representation and mapping, knowledge representation mechanism, inheritable knowledge

    Approaches to Knowledge Representation || Knowledge Representation || Artificial Intelligence· Intelligible Tutorials· 8 min

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  12. 12

    Propositional Logic: Syntax and Semantics

    Module IV, Knowledge Representation issues using predicate logic: Prepositional logic: syntax and semantics

    Lec-27: Propositional Logic in Artificial Intelligence | Knowledge Representation | All Imp Points· Gate Smashers· 12 min

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  13. 13

    First Order Predicate Logic (FOPL)

    Module IV, Knowledge Representation issues using predicate logic: First Order Predicate Logic (FOPL)

    First Order Predicate Logic ( FOL ) in Artificial Intelligence in Hindi | Knowledge Representation· Perfect Computer Engineer· 15 min

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  14. 14

    Fuzzy Logic Basics

    Module V, Expert System: Basic understanding of Fuzzy Logic

    Lec-33: Fuzzy Logic in Artificial Intelligence with Example | Artificial Intelligence· Gate Smashers· 13 min

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  15. 15

    Artificial Neural Networks and the Perceptron

    Module V, Expert System: Artificial Neural Network, Perceptron

    Lec-48: Perceptron Learning in ANN | Single Layer Perceptron Model· Gate Smashers· 14 min

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  16. 16

    NLP, Pattern Recognition and Robotics

    Module V, Expert System: Natural Language Processing, Pattern Recognition, Robotics

    Lec-36: Natural Language Processing in Artificial Intelligence in Hindi | NLP with Demo and Examples· Gate Smashers· 17 min

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  17. 17

    Introduction to LISP and Prolog

    Module V, Expert System: LISP and Prolog

    AI-Languages (Prolog & LISP) In Urdu/Hindi | Part-1 | Artificial Intelligence· Academy Lovers· 29 min

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  18. 18

    AI in Biotechnology and Bio-inspired Computing

    Module V, Expert System: The role of Artificial intelligence in Biotechnology, Introduction to Bio-inspired computing

    Lecture 4 AI Biological Techniques and Goals | Artificial Intelligence· Edu Tech Learn· 32 min

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Assignment

AI Problem-Solving Workbook: Search, Logic, Fuzzy Sets and the Perceptron

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Less scrolling. More passing.

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    Hand-picked video lessons

    18 short lessons, each with the best YouTube explanation we could find, trimmed to the part that matters.

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    Study notes

    16 lessons come with a summary, key points, key terms and takeaways for quick revision.

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    Quizzes

    75 questions across the course, with the right answer and why, the moment you pick.

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    Assignments

    1 subject assignments with clear tasks, so you practise what each subject actually asks of you.

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    Notebook

    Write notes beside the video, stamped with the exact time, and jump back to that moment later.

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    Progress that follows you

    Completed lessons, quiz scores and where you stopped, saved to your account on every device.

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    Live chat

    A members-only live chat beside every lesson: doubts, tips, stickers and GIFs with your batch. One ₹19 pass opens every live chat.

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A live chat right beside the video, shared by everyone studying Online MCA. Ask a Artificial Intelligence doubt mid-lesson, share a shortcut, celebrate a finished semester.

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Artificial Intelligence: common questions

This subject introduces the core ideas of Artificial Intelligence: how problems are represented, how search and heuristic algorithms like A* and AO* find solutions, and how knowledge is expressed using propositional and predicate logic. You will be able to formulate problems as state spaces, choose and trace suitable search techniques, write logical representations of knowledge, and explain the basics of fuzzy logic, neural networks, NLP, expert systems and AI languages like LISP and Prolog. It's the Artificial Intelligence subject of Online MCA, Semester 3, in 18 lessons: What is Artificial Intelligence and Why It Matters; AI Problems and Application Areas; State Space Representation in AI; Problem Reduction Representation (AND-OR Graphs); Production Systems: Characteristics and Types; Uninformed Search: Brute Force, DFS and BFS; Heuristic Search and Hill Climbing; Best First Search and A* Algorithm; AO* Algorithm; Constraint Satisfaction and Beam Search; Knowledge Representation: Mapping and Mechanisms; Propositional Logic: Syntax and Semantics; First Order Predicate Logic (FOPL); Fuzzy Logic Basics; Artificial Neural Networks and the Perceptron; NLP, Pattern Recognition and Robotics; Introduction to LISP and Prolog; AI in Biotechnology and Bio-inspired Computing.

Yes. Every video lesson is free to watch without an account. A free login unlocks study notes, quizzes, the assignment, a notebook and progress that syncs across devices.

About 4h 12m of video across 18 lessons, plus time for notes and quizzes. Go at your own pace; your place is saved.

Yes: “AI Problem-Solving Workbook: Search, Logic, Fuzzy Sets and the Perceptron”. It comes after the last lesson, with a brief, clear tasks and how the work is judged.

A members-only live chat beside the video, shared by everyone studying Online MCA, where learners ask doubts, share tips and react with stickers and GIFs. One ₹19 pass, paid once from your InsideEdge wallet, opens the live chat for every degree.

No. It's a crash course to help you understand and revise the subject quickly. Use it alongside your official study material and assignments.

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