Section outline

  • Welcome to the world of Artificial Intelligence

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    Hello Students!

    Are you wondering about the future world and how that world will be ruled by automated machines that are intelligent?  

    If your answer is yes, then welcome to the course "Artificial Intelligence"  (CSE315) in Summer 2021. In this course, you are going to learn the fundamental concepts of AI to know and understand AI. You will get to know some basic searching algorithms for problem-solving, Game playing, and so on. We are going to study in an approach that you will get all the support in this online platform. The course is designed with plenty of tutorials and resources. You will find course contents, reference books, course delivery plans, all kinds of  announcements , and contact information here.

    So, let's start our journey and make this semester a great and remarkable one.

       

                                                                 

    • forum icon
      Announcements Forum
    • forum icon
      Announcements Forum

    • Instructor Name:           Shayla Sharmin

      Designation:                  Lecturer

      Email:                             shayla.cse@diu.edu.bd

      Office Address:             Room 509, AB 4 City Campus, Ashulia ,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

    • resource icon
      Text Book File

      Artificial Intelligence: A Modern Approach

      - Stuart Russel & Peter Norvig

      Edition: 3rd

    • Google Classroom Code:

    • Students must
      Mark as done

      Course material Link :

      https://drive.google.com/drive/folders/1FP5TbIwVSgF-K5EKFSSmvS6E7oEYeI5i?usp=sharing


  • Week-1 and Week-2: Preparing Background and Introduction to AI

    • Topics of Discussion:

      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.

    • Expected Learning Outcomes:

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


    • Students must
      Mark as done

      Resources of Learning:


    • resource icon
      Topic 1: Introduction to AI File
    • lesson icon
      Lecture Video(PC C) Lesson
      Not available unless: You belong to CSE412(PC C)

  • Week-3 and Week-4: Intelligent Agent

    • Topics of Discussion:

      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

    • Students must
      Mark as done

      Expected Learning Outcomes:

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

    • Students must
      Mark as done

      Resources of Learning:


    • resource icon
      Topic 2: Intelligent Agents File
    • forum icon
      Discussion on Understanding of Intelligent Agents Forum
    • resource icon
      Intelligent Agents(Extra Documents) File
      Students must
      Mark as done
    • Students must
      Mark as done

      a

    • lesson icon
      Class Recording video link(PC C) Lesson
      Not available unless: You belong to CSE412(PC C)

  • Week-5 and Week-6: Problem Solving By Searching


    • Topics of Discussion:


      After completeing this lecture students will be able to:

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

    • Students must
      Mark as done

      Expected Learning Outcomes:

      • Formulate AI problems
      • Get an idea about how agent solve problems by searching
      • Differentiate between toy problems and real-life problems in searching


    • Students must
      Mark as done

      Resources of Learning:


    • resource icon
      Expert System File
    • assign icon
      Sudden Evaluation(PC D) Assignment
      Not available unless: You belong to CSE412(PC D)
    • Students must
      Mark as done

      a

    • lesson icon
      Class Recording video link(PC D) Lesson
      Students must
      Mark as done
    • lesson icon
      Class Recorded video(PC C) Lesson
      Not available unless: You belong to CSE412(PC C)
    • forum icon
      Assessment OF PEAS Forum
      Not available unless: You belong to CSE412(PC C)

  • Week 7: Problem Solving By Searching (Continuation)

    • Lesson 7 and 8:

      Learning Objectives:

      After completing this lecture students will be able to:

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

    • resource icon
      Solving Problem by Searching File
    • forum icon
      Discussion on Problem Solving by Searching Forum
      Not available unless: You belong to CSE412(PC D)
    • forum icon
      Discussion on Uniform Cost Search Forum
      Not available unless: You belong to CSE412(PC C)
    • Students must
      Mark as done

      a

    • lesson icon
      Class recorded video Lesson
      Not available unless: You belong to CSE412(PC D)

  • Week-8: Expert Systems

    • Lesson 9:

      Continuation of topic 4 (Problem solving by Search).

    • Lesson 10:

      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

    • resource icon
      Informed Search and Exploration File
    • forum icon
      Discussion of week 5 topics Forum
    • Students must
      Mark as done

      a

    • lesson icon
      Class Recording video Lesson
      Not available unless: You belong to CSE412(PC C)
    • lesson icon
      Class Recorded Video Lesson
      Not available unless: You belong to CSE412(PC D)
    • hvp icon
      Bidirectional Search Interactive Content
      Students must
      Mark as done

  • Week 10: Informed or Heuristic Search: Greedy Best First Search, A*Search

    • Lesson 11:

      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


    • resource icon
      Informed Search Exploration File

    • Lesson 12:

      Review on midterm exam topics

    • forum icon
      Discussion on Midterm topics Forum

  • Quiz(Before MID Term Exam)

    • assign icon
      First Quiz(PC D) Assignment
      Not available unless: You belong to CSE412(PC D)
    • assign icon
      First Quiz(PC C) Assignment
      Not available unless: You belong to CSE412(PC C)

  • MID term Exam

    Mid Term Exam Topics

    Lecture 1: Introduction

    Topic - 2: Intelligent Agents

    Topic – 3: Solving Problems by Searching


    • Students must
      Mark as done

      Midterm Open Book Examination Answer Script and Guideline [Click on the image]

                

        

    • Students must
      Mark as done

      Exam Started 10 July, 2021 1.30 pm to 4.00 pm

      MIDTERM EXAM QUESTION [Click Below Link]

    • assign icon
      Mid Term Exam CSE412(PC C) Assignment
      Not available unless: You belong to CSE412(PC C)
    • assign icon
      Mid Term Exam CSE412(PC D) Assignment
      Not available unless: You belong to CSE412(PC D)
    • Students must
      Mark as done

      Please Join the meet link(It is mandatory) during the exam

      http://meet.google.com/wnx-vpst-ypo

  • Week 11: Informed or Heuristic Search: Local Search, Genetic Algorithm


    • Lesson 13:

      Learning Objectives:

      After completing this lecture students will be able to:

      - Explain about Hill Climbing Search

      - Explain about Local Search

      - Apply Local search on a given problem

    • resource icon
      Informed Search Exploration File

    • Lesson 14:

      Learning Obectives:

      After completing this lecture students will be able to:

      • Evaluate utility funcs of some basic game playing algorithms
      • Apply greedy and minimax algorithm on some popular turn taking games

    • resource icon
      Game Playing File
    • forum icon
      Discussion on Week 8 topics Forum
      Not available unless: You belong to CSE412(PC D)
    • forum icon
      A* Search Algorithm Forum
      Not available unless: You belong to CSE412(PC C)
    • Students must
      Mark as done

      a

    • lesson icon
      Class Lecture video(PC C) Lesson
      Not available unless: You belong to CSE412(PC C)
    • lesson icon
      Class Lecture Video(PC D) Lesson
      Not available unless: You belong to CSE412(PC D)

  • Logical Agent

    • Lesson 15:

      Learning Obectives:

      After completing this lecture students will be able to:

      • Evaluate utility funcs of some basic game playing algorithms
      • Simulate greedy and minimax algorithm for some popular turn taking games

    • resource icon
      Game Playing File

    • Lesson 16: 

      Topic: Logical Agent

      Learning Objectives:

      After completing this students will be able to:

      - Explain about Logical agents

      - Apply First Order Propositional Logic to infer new knowledge

    • resource icon
      Logical Agents File
    • forum icon
      Discussion on Week 9 topics Forum
    • lesson icon
      Lecture Video Lesson
      Not available unless: You belong to CSE412(PC D)
    • assign icon
      Class work on Logical Agents Assignment
      Not available unless: You belong to CSE412(PC C)

  • Uncertainty

    • Lesson 17: 

      Topic: Logical Agent

      Learning Objectives:

      After completing this students will be able to:

      - Explain about Logical agents

      - Apply First Order Propositional Logic to infer new knowledge


    • resource icon
      Logical Agents File

    • Lesson 18:

      Topic: Uncertainty

      Learning Objectives:

      After Completing this lecture students will be able to:

      - Explain about uncertain features of real world

      - Explain Kolmagorov's axioms

      - Apply Bayes Theorem to take decision in some uncertainty based problems

    • resource icon
      Uncertainty File
    • forum icon
      Discussion on Week 10 topics Forum
    • lesson icon
      Lecture Video(PC D) Lesson
      Not available unless: You belong to CSE412(PC D)

  • Week 13

    • Lesson 23

      Topic: Neural network

      Learning Objectives:

      After completing this lecture students will be able to:

      - Explain about the architecture of Neural network

    • resource icon
      Architecture of Neural Network File
    • resource icon
      Architecture of Neural Network File

    • Lesson 24

      Topic: Review of final Exam contents

    • forum icon
      Discussion on Week 13 Topics Forum
    • assign icon
      Final Presentation(PC D) Assignment
      Not available unless: You belong to CSE412(PC D)

  • Final Exam

    Final Exam Syllabus

    Topics 4: informed Search

    Topics 5:Game Playing

    Topics 6:Logical Agents

    Topics 8: Uncertainty

    • Students must
      Mark as done

      Final Open Book Examination Answer Script and Guideline [Click on the image]

                

        

    • Students must
      Mark as done

      Exam Started 31 August, 2021 1.30 pm to 5.00 pm

      Final EXAM QUESTION [Click Below Link]

    • assign icon
      Final Exam PC C Assignment
      Not available unless: You belong to CSE412(PC C)
    • assign icon
      Final Exam PC D Assignment
      Not available unless: You belong to CSE412(PC D)