Topic outline

  • WELCOME LETTER

    Dear Students

    Welcome to the Big Data and IoT Theory (CSE 412) &  Lab (CSE 413) courses, I,  Nasima Islam Bithi will be your co-pilot in this online journey of learning.

    I care about your success in these courses. I'm glad you are here.

    Nasima Islam Bithi
    Lecturer,
    Department of Computer Science and Engineering,

    Daffodil International University

    Basic Information:

    Course Code: CSE 412/413
    Course Title: Big Data and IoT
    Program: B.Sc in Computer Science and Engineering
    Faculty: Science and Information Technology
    Semester: Fall; Year: 2023
    Credit: Theory (1Cr) and Lab (3Cr); 
    Course Category: Core Engineering

    Course Instructor:

    Nasima Islam Bithi
    Lecturer
    Office: Room # 505, AB04 Building, Daffodil Smart City
    Cell Number# +880 1629665310

    Email: bithi.cse@diu.edu.bd

    Course Rationals

    Big Data refers to a massive set of data that no conventional data management tool can handle. Big Data is therefore a concept that allows access to gigantic databases in real time. Big Data's main objectives are to improve a company's or system's responsiveness to a large amount of data collected, increase productivity and refine knowledge of customer behavior, so that it can offer personalized offers or advertisements and create new trends.

    The Internet of Things (IoT) is a concept that connects physical or virtual objects to the internet. The technology very often used is the sensor, allowing to link a physical object such as a watch, a drone or even a speaker, to the internet. If for a long time the few objects connected to the Internet were the telephone and the computer, this is no longer the case today and every year new types of objects incorporating IOT technology are born. IOT is one of the greatest technological revolutions of our era and its potential for exploitation is immense. IOT could have a huge impact on the cars of the future or on the new versions of smart-cities, an urban space connected to the Internet, thus significantly improving the lives of users, while reducing the negative impact of these on the planet. 

    Assessment Plan

    Final Exam
    40
    Mid-term Exam
    25
    3 Class Tests
    15
    Attendance
    07
    Presentation
    08
    Total
    100
  • Week 1

    Introduction

    • Due: Tuesday, 29 August 2023, 11:59 PM
      View
    • Opened: Wednesday, 30 August 2023, 12:00 AM
      Due: Thursday, 31 August 2023, 12:00 AM
    • Due: Tuesday, 29 August 2023, 11:59 PM
      View
  • Topic 4

    Week 2

    Lab: Installtion of PySpark

  • Week 3

    Introduction to Hadoop

    • Due: Tuesday, 29 August 2023, 11:59 PM
      View
  • Topic 6

    Week 3

    Lab: Introduction to pyspark programming

    • Due: Tuesday, 29 August 2023, 11:59 PM
      View
  • Week 4: Map Reduce and Yarn

    Week 4

    Map Reduce and Yarn

  • Topic 8

    Week 4

    Lab: Introduction to RDD and DataFrame

    • Due: Tuesday, 29 August 2023, 11:59 PM
      View
  • Week 5: Hadoop cluster and ecosystem

    Week 5

    Hadoop cluster and ecosystem

  • Topic 10

    Week 5

    LAb: DataFrames and Spark SQL

  • Week 6: Mid Term

    Week 6

    MIDTERM

    • Opened: Thursday, 14 September 2023, 11:03 AM
      Closed: Thursday, 14 September 2023, 12:40 PM
  • Week 8: Apache Sqoop, Hive and Pig

    Week 8

    Apache sqoop, hive and pig

    • Due: Monday, 4 September 2023, 5:30 AM
    • Opened: Thursday, 7 September 2023, 11:00 AM
      Due: Thursday, 14 September 2023, 11:59 PM
  • Lab-Week 8: IoT Lab

    Week 8

    IoT Lab

  • Week 9: Introduction to IoT

    Week 9

    Introduction to IoT

  • Lab-Week 9-10: Implementing to IoT - 2


  • Week 10: IOT

    Week 10

    M2M and IoT

    • Opened: Thursday, 9 November 2023, 9:10 PM
      Closed: Thursday, 9 November 2023, 10:15 PM
  • Week 12: Presentation


  • Week 13: Review Class

    Topic of Discussion

             Review on the topics of Week 8, Week 9, Week 10, Week 11 and Week 12.




    • Assignment

    • Project Report

    • others

    • Topic 22


      Presentation


      Present any Deep Learning model architecture.

      Mark: 8                
      Time: 5-7min
      Number of Slides: 10-13
      Slides must be eye catching.

      Rubric of presentation (out of 100):

      • getup & outfit : formal/semi formal (10%)
      • Body language 10%
      • Communication style : bangla/ english 10%
      • eye contact 10%
      • knowledge 40%
      • Handling Ques/Ans 20%

      • Opened: Monday, 25 September 2023, 12:00 AM
        Due: Monday, 2 October 2023, 12:00 AM
      • Opened: Monday, 25 September 2023, 12:00 AM
        Due: Monday, 2 October 2023, 12:00 AM
    • Project

    • Topic 24

      week 9 Apache Sqoop, Pig and Hive

      Topics of Discussion:

      • Apache Sqoop
      • Apache Flume
      • Apache Pig
      • Apache Hive

      Expected Learning Outcomes:

      • Understanding the features and working principle of Apache Sqoop, Flume, Pig and Hive

      Resources of Learning:


    • Topic 25

      week 10 Introduction to IoT

      Topics of Discussion:

      • What is IoT ?
      • Element and characteristics of IoT
      • Sensor and actuator
      • Embedded system vs IoT system
      • Different types of IoT level
      • Green field vs Brown field of IoT
      • Future factory concept and smart objects

        Expected Learning Outcomes:

        • Understanding the concepts of IoT to implement in real world scenario.

        Resources of Learning:


      • Topic 26

        week 11 IoT protocol & communication model

        Topics of Discussion:

        • IoT protocols
        • Communication models in IoT
        • IoT enabling technologies
        • Advantages and disadvantages of IoT

          Expected Learning Outcomes:

          • Understanding the concepts of protocols and communication models in IoT enabling technologies.

          Resources of Learning:


        • Topic 27

          week 12 M2M and IoT

          Topics of Discussion:

          • What is IoT ?

            Expected Learning Outcomes:

            • Understanding the concepts of IoT to implement in real world scenario.

            Resources of Learning:


          • Topic 28

            Online class recording

          • Topic 29


            Final

            Final Syllabus:

            Updated outline for final exam
            1. 1. Apache Sqoop, Apache Pig & Apache Hive
            2. Introduction to IoT

            3.  IoT_Part2

            4. M2M and IOT


            Assessment Plan

            Total Marks: 40


            End of the Semester.



            • Topic 30

              Lab evaluation

              Mark: 30

              Dataset: KMNIST

              Perform the following operation on the given dataset:
              1. Load the data, check whether GPU is available and shape of the data (5)
              2. Design the CNN model (The model has 5 convolution layers, 4 fully connected layer. Include dropout, batch normalization, pooling where needed) (10)
              3. Train the model for 2epochs (5)
              4. Test the model, calculate accuracy, and draw a confusion matrix for the model (5)

              5. Apply any pretratined model, calculate the accuracy (5)

              Time: 1:15 hr
              Don't share your code with others. Upload the code in python file format. Dont make it pdf. Rename the code by your name



            • Topic 31

              CT-03

              • Opened: Wednesday, 22 November 2023, 3:15 PM
                Due: Wednesday, 22 November 2023, 3:40 PM
              • Opened: Wednesday, 22 November 2023, 3:15 PM
                Due: Wednesday, 22 November 2023, 3:40 PM
            • Lab project