Artificial Intelligence Lab (Spring 21)

Section outline

• Select section Artificial Intelligence Lab - Python

  Artificial Intelligence Lab - Python

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  • Select activity Announcements

    

    Announcements Forum
  • Select activity Welcome Message:Are you wondering about the future...

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    Welcome Message:

    Are you wondering about the future world? Yes, of course, Artificial Intelligence is going to rule in industries all over the world. Not only that, but it will play its role in household works also. This course aims to introduce yourself to the world of Artificial Intelligence. The focus of this lab course will include Intelligent agents, Solving problems by searching, Game playing, basics knowledge of python, ML algorithm, and neural network. These will be some of the essential fundamental knowledge for every computer scientist in the future.

    You are welcome to browse the page.

    Hope we will have a memorable journey together.

    
    

  • Select activity Instructor's InformationName Md. Zabirul IslamDesi...

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    Instructor's Information

    
    

    

    Name Md. Zabirul Islam
    

    Designation: Lecturer, Dept of CSE
    Email: zabirul.cse@diu.edu.bd
    Cell: 01521-307471 
    

  • Select activity Profile Link   

    Profile Link

       
    

  • 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 Book: 1)Hands on Machine Learning w...

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    Reference Book: 

    1)Hands on Machine Learning with Scikit Learn and Tensorflow.pdf

    2) Python 3 Pdf - Tutorialspoint

    
    

    
    

    
    

  • Select activity Welcome Vedio:

    Welcome Vedio:

    
    

  • Select activity Class link -Wednedday-(8:30am-11:30am)

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    Class link -Wednedday-(8:30am-11:30am)

• Select section Forum

  Forum

  • Select activity Basics of Python

    

    Basics of Python Forum

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    View
• Select section Week 1

  Week 1

  • Select activity Session I: Basics of PythonIntended Learning Outco...

    Session I: Basics of Python

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

    • Discuss the three basics of Python

    – Syntax

    – Variables and data types

    – List, tuples, dictionaries

    - Conditions and Loops

  • Select activity Lab Video 1 (Based on ML introduction )(10-2-2021)

    

    Lab Video 1 (Based on ML introduction )(10-2-2021) URL

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  • Select activity Additional Links:

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    Additional Links:

  • Select activity Python Tutorial

    

    Python Tutorial URL

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  • Select activity Label

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• Select section Week 2

  Week 2

  • Select activity Session II: Basics of PythonAim of this lecture: ...

    Session II: Basics of Python

    Aim of this lecture:

      • The following topics will be discussed in the class

    – Condition and Loops

    - Function

    - Class and Objects

    
    

  • Select activity Lab Video 2 (17-2-2021)

    

    Lab Video 2 (17-2-2021) URL

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  • Select activity Additional Links: (copy)

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    Additional Links:

  • Select activity Resource Link (List)

    

    Resource Link (List) URL

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  • Select activity Resource Link (Tuples)

    

    Resource Link (Tuples) URL

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  • Select activity Label

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• Select section Week 3

  Week 3

  • Select activity Session II: Basics of PythonAim of this lecture: ...

    Session II: Basics of Python

    Aim of this lecture:

      • The following topics will be discussed in the class

    – Sets and Dictionary

    
    

  • Select activity Lab Video 3 (Sets and dictionary ) (24-2-2021)

    

    Lab Video 3 (Sets and dictionary ) (24-2-2021) URL

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  • Select activity Additional Links: (copy) (copy)

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    Additional Links:

  • Select activity Resource Link (Sets)

    

    Resource Link (Sets) URL

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  • Select activity Resource Link (Dictionary)

    

    Resource Link (Dictionary) URL

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  • Select activity Python Tutorial - Python for Beginners

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    Python Tutorial - Python for Beginners
    
    
• Select section Week 4

  Week 4

  • 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 Lab video 4 (3-3-2021)

    

    Lab video 4 (3-3-2021) URL

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  • Select activity Resource Link (Numpy)

    

    Resource Link (Numpy) URL

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  • Select activity Additional Links: (copy) (copy) (copy)

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    Additional Links:

  • Select activity Numpy Tutorial   

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    Numpy Tutorial
    
       
  • 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

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  • Select activity Class video on Pandas (24-3-2021)

    

    Class video on Pandas (24-3-2021) URL

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  • Select activity Resource Link 1 (pandas)

    

    Resource Link 1 (pandas) URL

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  • Select activity Resource Link 2 (pandas)

    

    Resource Link 2 (pandas) URL

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  • Select activity Complete Python Pandas Data Science Tutorial! (Rea...

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    Complete Python Pandas Data Science Tutorial! (Reading CSV/Excel files, Sorting, Filtering, Groupby)
    
    
    
     Python Pandas Tutorial | Data Analysis with Python Pandas | Python Training | Edureka
    
    
    
     Data Analysis with Python - Full Course for Beginners (Numpy, Pandas, Matplotlib, Seaborn)
    
    
    
      Python Pandas Tutorial 1. What is Pandas python? Introduction and Installation
    
    
• Select section Week 5

  Week 5

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

    Session I: 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 Class Video on ML Algorithm - Regression (28-3-2021)

    

    Class Video on ML Algorithm - Regression (28-3-2021) URL

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  • Select activity Python Machine Learning Tutorial (Data Science)

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    Python Machine Learning Tutorial (Data Science)
    
    
• Select section Home Task (ML)

  Home Task (ML)

  Machine Learning A-Z™ Hands-On Python & R In Data Science

  
  
• Select section Week 8

  Week 8

  • Select activity Session III: Machine Learning Algorithm (KNN algor...

    Session III: Machine Learning Algorithm (KNN algorithm)

    Aim of this lecture:

    –  Discussion on KNN
    –  Apply KNN on Datasets   

    
    

    
    

  • Select activity Session VIII: Machine Learning Algorithm (Support ...

    Session VIII: Machine Learning Algorithm (Support Vector Machine)

    Aim of this lecture:

    –  Discussion on SVM
    –  Apply SVM on Datasets  
    

    
    

  • Select activity Session VII: Machine Learning Algorithm (Naive Bay...

    Session VII: Machine Learning Algorithm (Naive Bayes)

    Aim of this lecture:

    –  Discussion on Baive Bayes
    –  Apply Naive Bayes on Datasets  
    

    
    

  • Select activity Class Video on ML Algorithm -Classification (31-3-2021)

    

    Class Video on ML Algorithm -Classification (31-3-2021) URL

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• Select section Assignment

  Assignment

  Assignment 

  • Select activity Assignment on Python

    

    Assignment on Python

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    Submit your notebook link here 

• Select section Lab Test

  Lab Test

  Lab Test

  • Select activity Labtest on ML

    

    Labtest on ML Assignment

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  • Select activity Submit your answer in this form

    

    Submit your answer in this form URL

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• Select section Week 12

  Week 12

  

  • Select activity Submit your project and project report here

    

    Submit your project and project report here Assignment

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    Project report  content :

    1.Introduction,

    2. Dataset description

    3. Algorithm description

    4.Code,

    5.Conclusion

    
    

• Select section Week 14

  Week 14

  
  

  
  

  • Select activity Quiz

    

    Quiz URL

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• Select section Topic 13

  Topic 13

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• Select section Topic 14

  Topic 14

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• Select section Topic 15

  Topic 15

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• Select section Topic 16

  Topic 16

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