Software Project-I (Spring 21)

Section outline

• Select section Welcome to Software Project 1

  Welcome to Software Project 1

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  • Select activity Announcements

    

    Announcements Forum

    Welcome Message:
    

    In this Software Project I lab, we will introduce a new term, which is Artificial Intelligence(AI). 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 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.

    

     Name Md. Zabirul Islam
     Lecturer, Dept of CSE

     Daffodil International University
     Email: zabirul.cse@diu.edu.bd
     Cell: 01521-307471 

     
    
    

     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
    

    
    

    Assessment Policies:

    Class Attendance	10
    Labtest	25
    Lab Quiz	25
    Lab Project	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

    
    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    
    

    Reference Book: 

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

    2) Python 3 Pdf - Tutorialspoint

    
    
  • Select activity Welcome vedio:

    Completion

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    Mark as done

    Welcome vedio:

  • Select activity Profile Link   

    Profile Link

       
    

• Select section Forum

  Forum

  • Select activity Basics of Python

    

    Basics of Python Forum

    Completion

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    1. Discuss the basics of Python.

    2. Why it is important for Machine learning?

    3 . Ask questions if you have.

  • Select activity Basics of Numpy

    

    Basics of Numpy Forum

    Completion

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    1. Discuss the basics of numpy.

    2. Why it is important for Machine learning?

    3 . Ask questions if you have.

    
    

  • Select activity Basic of Pandas

    

    Basic of Pandas Forum

    Completion

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    1. Discuss the basics of Pandas.

    2. Why it is important for Machine learning?

    3 . Ask questions if you have.

    
    

• Select section Week 1

  Week 1

  Introductory class with students

  • Select activity Class Video 1 (Introductory class) (25-1-2021)

    

    Class Video 1 (Introductory class) (25-1-2021) URL

    Completion

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• Select section Week 2

  Week 2

  Session I: Introduction to Machine Learning

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

  – know what is machine learning

  – know why we use it

  – know the real-life example

  
  

  • Select activity Introduction to ML (30-1-2021)

    

    Introduction to ML (30-1-2021) File

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  • Select activity Class Video 2 (Introduction to ML) 1st part (30-1-2021)

    

    Class Video 2 (Introduction to ML) 1st part (30-1-2021) URL

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  • Select activity Class Video 2 (Introduction to ML) 2nd part

    

    Class Video 2 (Introduction to ML) 2nd part URL

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  • Select activity Label

    Completion

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• Select section Week 3

  Week 3

  Session II: 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 Class video 3 (Introduction to Python)(13-2-2021)

    

    Class video 3 (Introduction to Python)(13-2-2021) URL

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  • Select activity Python tutorial (website link)

    

    Python tutorial (website link) URL

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  • Select activity Additional links: (copy)

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    Additional links:

  • Select activity Python Tutorial - Python for Beginners

    Completion

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    Python Tutorial - Python for Beginners
    
• Select section Week 4

  Week 4

  Session II: 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 Class Video 4 (Python )

    

    Class Video 4 (Python ) URL

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  • Select activity Additional links: (copy)

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    Additional links:

  • Select activity Resource Link

    

    Resource Link URL

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  • Select activity Label

    Completion

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• Select section Week 5

  Week 5

  Session III: Data Processing
  

  Aim of the Session:

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

  
  

  
  

  • Select activity Class vedio 5 (Numpy) (27-2-2021)

    

    Class vedio 5 (Numpy) (27-2-2021) URL

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  • Select activity Resource Link (Numpy)

    

    Resource Link (Numpy) URL

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  • Select activity Numpy Tutorial   

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    Numpy Tutorial
    
       
  • Select activity Class Video on Pandas (20-3-2021)

    

    Class Video on Pandas (20-3-2021) 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 Resource Link 3 (pandas)

    

    Resource Link 3 (pandas) URL

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  • Select activity Resource Link 4 (pandas)

    

    Resource Link 4 (pandas) URL

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

    Completion

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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 activity Additional links:

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    Additional links:

  • Select activity Python Machine Learning Tutorial (Data Science)

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    Python Machine Learning Tutorial (Data Science)
    
    
• Select section Week 6

  Week 6

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

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    Data Visualization
    

    Aim of the Session:

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

    
    

  • Select activity Label

    Completion

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• 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

  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  

  Session II: Machine Learning Algorithm (Support Vector Machine)

  Aim of this lecture:

  –  Discussion on SVM
  –  Apply SVM on Datasets  

  
  

  
  

  • Select activity Class Video on ML Algorithm - Regression (27-3-2021)

    

    Class Video on ML Algorithm - Regression (27-3-2021) URL

    Completion

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  • Select activity Additional Links

    Completion

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    Additional Links

  • Select activity Machine Learning with Python Tutorial

    

    Machine Learning with Python Tutorial URL

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  • Select activity Machine Learning With Python

    Completion

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    Machine Learning With Python
    
    
• Select section Week 9

  Week 9

  Session III: Machine Learning Algorithm (KNN algorithm)

  Aim of this lecture:

  –  Discussion on KNN
  –  Apply KNN on Dataset

  Session IV: 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 (5-4-2021)

    

    Class Video on ML Algorithm - Classification (5-4-2021) URL

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  • Select activity Additional links

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    Additional links

  • Select activity Machine Learning

    

    Machine Learning URL

    Completion

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• Select section Week 11

  Week 11

  Assignment

  • Select activity Assignment on Python

    

    Assignment on Python

    Completion

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    Submit your kaggle notebook link here

  • Select activity Assignment on Numpy and Pandas

    

    Assignment on Numpy and Pandas

    Completion

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    Mark as done

    Submit your kaggle notebook link here

• Select section Week 10

  Week 10

  Labtest

  • 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

    Completion

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    Project report  content :

    1.Introduction,

    2. Dataset description

    3. Algorithm description

    4.Code,

    5.Conclusion 
    

• Select section Week 13

  Week 13

  
  

  • Select activity Quiz

    

    Quiz URL

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    No of Question: 20

    Marks: 25

    Time: 30 min

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