Topic outline

  • Welcome to the world of Artificial Intelligence

    Assalamuwalikum  Students,  welcome to Summer'21. Throughout this semester I will be with you in any problem.

    Hope you have a great semester. Best, SSH

    Audio welcome letter:  




    •                   DIU - Daffodil International University

      Instructor Name:      Shahana Shultana

      Designation:              Lecturer

      Email:                         shahana.cse@diu.edu.bd

      Office Address:          Room 505, AB-04, Savar, Dhaka

    • Course Rationale:

      Artificial intelligence (AI) is a research field that studies how to realize the intelligent human behaviors on a computer. The ultimate goal of AI is to make a computer that can learn, plan, and solve problems autonomously. Although AI has been studied for more than half a century, we still cannot make a computer that is as intelligent as a human in all aspects. In this course, we will study the most fundamental knowledge for understanding AI. We will introduce some basic search algorithms for problem solving; knowledge representation and reasoning; game playing theories; Uncertainty; natural language processing and neural networks.

    • Course Objectives:

      The main objective of this course is to provide an introduction to the basic principles and applications of artificial intelligence.


    • After Completing the course students will be able to:

      CO1: Understand the concepts of Artificial intelligence, Intelligent Agents And issues in the design of search programs. 

      CO 2: Explain the role of agents and how it is related to environment and the way of evaluating it and how agents can act by establishing goals.

      CO 3: Analyze and simulate various searching techniques, constraint satisfaction problem and example problems- game playing techniques.. 

      CO 4: Explain the concepts of Logical Agents, Uncertainty,Natural Language processing and Expert Systems.

      CO 5: Analyze and design a real world problem for implementation and understand the dynamic behavior of a system.

    • Assessment:

       Class Attendance

                     07

       Assignment

                     5

       Class Test

                     15

      Presentation

                       8

       Mid Term Exam

                    25

       Semester Final Exam

                    40

      Total:    

      100



    • Grading Policy:

      Numerical Grade

      Letter Grade

      Grade Point

      80% and above

      A+

      (A Plus)

      4.0

      75% to less than 80%

      A

      (A regular)

      3.75

      70% to less than 75%

      A-

      (A minus)

      3.5

      65% to less than 70%

      B+

      (B Plus)

      3.25

      60% to less than 65%

      B

      (B regular)

      3.0

      55% to less than 60%

      B-

      (B minus)

      2.75

      50% to less than 55%

      C+

      (C Plus)

      2.5

      45% to less than 50%

      C

      C (regular)

      2.25

      40% to less than 45%

      D

       

      2.0

      Less than 40%

      F

       

      0.0

    • Text Book File

      Artificial Intelligence: A Modern Approach

      - Stuart Russel & Peter Norvig

      Edition: 3rd

  • Week 1


    • Lesson 1: Introducing Class

      Formal introduction between students and teacher. Outline of the course will be shared and course related topic will be discussed in order to make students familiar about the outcome of the course.

    • Lesson 2:

      Topic Name: Introduction to AI

      After completing the lesson students will be able to:

      • Understand the fundamental ideas of AI
      • Understand the foundational concepts of AI
      • Know about the initial experiments and and future scopes of AI


    • Feedback (PC-A, PC-B, PC-C) Choice

      Today's class was:

    • Review Assignment (Topic-1)

      Write down the differences between AI and Cybernetics

    • Topic-1 (PC-A) URL
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    • Topic-1 (pc-b) URL
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    • topic-1 (pc-c) URL
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    • Lab-1 (PC-C) URL
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  • Week 2

    Topics in AI : AGENTS

    • Lesson 3:

      Learning Objectives

      After completing the lecture students will be able to:

      • Explain about agent and rational agents
      • Define PEAS for any given agent
      • Explain about different kinds of Agents' Environments 
      • Differentiate between different kinds of agents

    • Review Assignment (Topic-2)

      Write down the PEAS description of a Football Player agent

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    • topic-2 (part-1) (pc-b) URL
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    • topic-2 (part-1) (pc-c) URL
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    • Lesson 4:

      Learning Objectives:

      After completeing this lecture students will be able to:

      • Describe the properties of Espert Systems
      • Explain different aspects of Expert Systems

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    • Topic-7 & Topic-2 (part-2) (PC-B) URL
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    • Topic-7 & Topic-2 (part-2) (PC-C) URL
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    • lab-2 (pc-c) URL
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    • Lab performance-1 regression Assignment
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  • Week 3

  • Week 4


    • Breadth-first search - Wikipedia

      Lesson 6:

      Learning Objectives:

      After completing this lecture students will be able to:

      • Formulate AI program
      • Apply Uninformed search algorithms on given problems

    • Topic-3 (part-2) (PC-A) URL
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    • topic-3 part-2 URL
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  • Quiz-1

  • Week 5

    A* search algorithm - Wikipedia

    • Lesson 6:

      Continuation of topic 4 (Problem solving by Search).

    • Learning Objectives:

      After completing this lecture students will be able to:

      - Explain Heuristic functions for some toy problems

      - Simulate Greedy search on a given problem

    • Feedback Topic-4 (Part-1) Choice

      Today's class was

    • Feedback Lab-5 Choice

      Today's Lab class was

    • Informed Search Review Assignment

      Prove the optimality of A* search

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    • classification lab part-1 URL
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    • lab performance-classification Assignment
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    • t-4 part-1 URL
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    • t-4 part-1 URL
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  • Week 6

    Evolving Solutions With Genetic Algorithms

    • Lesson 7:

      Learning Objectives:

      After completing this lecture students will be able to:

      - Explain Heuristic functions for some toy problems

      - Simulate and apply A* search on a given problem


    • Lesson 7:

      Review on midterm exam topics

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    • classification lab part-2 URL
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    • t-4 part-2 URL

  • Week 7

    Midterm Exam

    Date and time will be announced later.

    • Mid Term Exam Assignment
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      Please rename your answer script using your student ID and then submit.

    • Mid Term Exam Assignment
      Restricted Not available unless: You belong to PC-B

      Please rename your answer script using your student ID and then submit.

    • Mid Term Exam Assignment
      Restricted Not available unless: You belong to PC-C

      Please rename your answer script using your student ID and then submit.

  • Week 8

  • Week 9

  • Week 10


  • Presentation And Assignment

    • Presentation Assignment
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    • Presentation Assignment
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    • Presentation Assignment
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    • Assignment
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    • Assignment
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    • Assignment
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  • Lab Final (PC-C)

    • Lab final Assignment
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  • Project Final

    • Project Final Assignment
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  • Final Exam

    • FINAL EXAM Assignment
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    • FINAL EXAM Assignment
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    • FINAL EXAM Assignment
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  • Topic 20