Artificial Intelligence Lab (Summer 2021)

Section outline

• Select section Artificial Intelligence Lab - Python

  Artificial Intelligence Lab - Python

  Collapse all Expand all

  • Select activity Announcements

    

    Announcements Forum
  • Select activity Hello Students!Are you wondering about the future ...

    Completion

    Students must

    

    Mark as done

    
    

    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 LAB"  (CSE413) 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.

    
    

  • Select activity Instructor Name:        &nbs...

    Instructor Name:           Shayla Sharmin

    Designation:                  Lecturer

    Email:                             shayla.cse@diu.edu.bd

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

    
    

                                                  
    

  • Select activity Course Objectives:After completing the course stud...

    Course Objectives:

    After completing the course students will be able to:

    - Explain fundamentals of Python Language

    - Solve real life problems using Python

    - Implement a few basic ML algorithms

  • Select activity Assessment Policies:Class Attendance    ...

    Assessment Policies:

    Class Attendance	10
    Lab Performance	25
    Project	25
    Lab Final	40
    Total	100

    
    
    

  • Select activity Grading Policy:Numerical GradeLetter GradeGrade Po...

    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

    
    
    

  • Select activity Reference Books - 1

    

    Reference Books - 1 File
  • Select activity Reference Book - 2

    

    Reference Book - 2 File
  • Select activity Reference Book - 3

    

    Reference Book - 3 File
• Select section Session I: Basics of Python

  Session I: Basics of Python

  • Select activity Topics of Discussion: At the end of the session...

    
    

    Topics of Discussion:

    At the end of the session, student should be able to:

    • Give some simple examples of Prolog programs

    • Discuss the three basics of Python

    – Syntax

    – Variables and data types

    – List, tuples, dictionaries

    - Conditions and Loops

  • Select activity Resources of Learning:

    Completion

    Students must

    

    Mark as done

    
    

    Resources of Learning:

    
    

  • Select activity Discussion on Week 1's Topic

    

    Discussion on Week 1's Topic Forum
  • Select activity Basics of Python

    

    Basics of Python File
  • Select activity Lecture Video(PC C)

    

    Lecture Video(PC C) Lesson

    Completion

    Students must

    

    Mark as done
  • Select activity Lecture Content

    

    Lecture Content URL

    Completion

    Students must

    

    Mark as done
• Select section Session II: Basics of Python(Cotinued)

  Session II: Basics of Python(Cotinued)

  • Select activity Topics of Discussion:   • The followi...

    Topics of Discussion:
    

      • The following topics will be discussed in the class

    – Condition and Loops

    - Function

    - Class and Objects

    
    

  • Select activity Resources of Learning: (copy)

    Completion

    Students must

    

    Mark as done

    
    

    Resources of Learning:

    
    

  • Select activity Discussion on Week 2's Topic

    

    Discussion on Week 2's Topic Forum
  • Select activity Basic's of Python

    

    Basic's of Python File
  • Select activity Lecture Video(PC C)

    

    Lecture Video(PC C) Lesson

    Completion

    Students must

    

    Mark as done
  • Select activity Lecturer Content Link1.    &nb...

    Completion

    Students must

    

    Mark as done

    Lecturer Content Link

    1.         https://colab.research.google.com/drive/1JmLOrmo4eQmDzwfSogTv8igaOHR16hJm

    2.         https://colab.research.google.com/drive/1LjF7DGWhMgkZGj1qFkVBeGg2weWisflx

    
    

• Select section Week 3

  Week 3

  • Select activity Session III: Data ProcessingAim of the Session:–  ...

    Session III: Data Processing

    Aim of the Session:

    –  Introduce NumPy and Panda
    –  Hands on work with data using NumPy or Panda
    

  • Select activity Discussion on Week 3's Topic

    

    Discussion on Week 3's Topic Forum
  • Select activity Reading Material on NumPy

    

    Reading Material on NumPy File
  • Select activity Dataset - Starbucks

    

    Dataset - Starbucks File
  • Select activity Lecture Content Link1.    &nbs...

    Completion

    Students must

    

    Mark as done

    Lecture Content Link

    1.        https://colab.research.google.com/drive/1opPedB4mSqwwChKD0fhJi9scOaJ2xTSE#scrollTo=CsnsqMPsWn6m

    2.         https://colab.research.google.com/drive/1A595l-UcytBkCuH25a-CyfFwVcBcFyHF

    
    

  • Select activity Lecture Recorded Video

    

    Lecture Recorded Video Lesson

    Completion

    Students must

    

    Mark as done
• Select section Week 4

  Week 4

  • Select activity Session IV: Data VisualizationAim of the Session:–...

    Session IV: Data Visualization

    Aim of the Session:

    –  Introduce data visualization libraries
    –  Hands on work for data visualization using different datasets

  • Select activity Discussion on Week 4's Topic

    

    Discussion on Week 4's Topic Forum
  • Select activity Download - Reading material data visualization

    

    Download - Reading material data visualization File
  • Select activity Download Dataset - 1 (Irish)

    

    Download Dataset - 1 (Irish) File
  • Select activity Download Dataset - 2 (Winemag)

    

    Download Dataset - 2 (Winemag) File
  • Select activity Lecture Video

    

    Lecture Video Lesson

    Completion

    Students must

    

    Mark as done
• Select section Week 5

  Week 5

  • Select activity Session V: Machine Learning Algorithm (Linear and ...

    Session V: Machine Learning Algorithm (Linear and Logistic Regression)

    Aim of this lecture:

    –  Discuss on Linear Regression
    –  Discuss on Logistic Regression
    –  Apply Linear and Logistic Regression on Datasets  
    
    

  • Select activity Discussion on 5th Week's Topic

    

    Discussion on 5th Week's Topic Forum
  • Select activity Linear Regression

    

    Linear Regression File
  • Select activity Logistic Regression

    

    Logistic Regression File
  • Select activity Dataset for Logistic Regression

    

    Dataset for Logistic Regression File
  • Select activity Dataset for Linear Regression

    

    Dataset for Linear Regression File
  • Select activity Lecture Video

    

    Lecture Video Lesson

    Completion

    Students must

    

    Mark as done
• Select section Week 6

  Week 6

  • Select activity Session VI: Machine Learning Algorithm (KNN algori...

    Session VI: Machine Learning Algorithm (KNN algorithm)

    Aim of this lecture:

    –  Discussion on KNN
    –  Apply KNN on Datasets  
    

    
    

  • Select activity Discussion on 6th Week's Topic

    

    Discussion on 6th Week's Topic Forum
  • Select activity Download - Reading material for KNN

    

    Download - Reading material for KNN File
  • Select activity Dataset for KNN

    

    Dataset for KNN File
  • Select activity Lecture Vedio

    

    Lecture Vedio Lesson

    Completion

    Students must

    

    Mark as done
• Select section Week 7

  Week 7

  Midterm Exam

  LAB Evaluetion

  • Select activity Lab Evaluation(PC C)

    

    Lab Evaluation(PC C) Assignment

    Completion

    Students must

    

    Mark as done
• Select section Week 8

  Week 8

  Not available
• Select section Week 9

  Week 9

  Not available
• Select section Week 10

  Week 10

  Not available
• Select section Week 11

  Week 11

  Not available
• Select section Week 12

  Week 12

  Project Presentation

  • Select activity Submit your project presentation here

    

    Submit your project presentation here Assignment

    Completion

    Students must

    

    Mark as done
• Select section Week 14

  Week 14

  Final Exam

  Exam will Be held on 12 august 2021

  Syllabus:

   Syntax

  – Variables and data types

  – List, tuples, dictionaries, sets

  - Conditions and Loops

  - functions

  -Numpy Array

  -Data Visualization

  • Select activity Lab Final Exam(PC C)

    

    Lab Final Exam(PC C) Assignment

    Completion

    Students must

    

    Mark as done