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Exploratory Data Analytics in Health (Batch 2)


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Course Level


Total Hour


Video Tutorials


Course content


Week 01

Lesson 02 Why Do We Need Data Analysis

Week 02

Week 03

Week 04

Week 05

Week 06

Week 07

Week 08 (Face to Face)

course resources

About Course

This course will teach how to handle data using exploratory strategies. These strategies are often used prior to the start of formal modeling and can aid in the construction of more complex statistical models. Exploratory procedures are also useful for modifying various type of data for prediction, classification, recommendation algorithms. We’ll go through the plotting systems in Python in depth, as well as some of the fundamental ideas of data visualization. We’ll also implement some of the most common multivariate statistical approaches for visualizing data with a lot of dimensions.

Learning Outcomes of this Course:

After completion of this course participants are expected to be able to:

  • learn about the related tools and techniques the Data Analytics in Health.
  • know about basic Python programming and libraries.
  • Use basic data analysis techniques.
  • Implement basic algorithms using processed data.

This course has been developed with the support of the Commonwealth of learning, Canada

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What to learn?

Basic Python programming. Analytic graphics and the base plotting system in Python. Make graphical representations of data with a lot of dimensions. Apply basic algorisms for classification and prediction


  • Basic computer knowledge
  • Conditions and logics of programming
  • Basic mathematics


  • University students
  • College students
  • Tech professionals
  • Start-up owner
  • Business initiator
  • E-commerce owner
  • Researchers


Md. Sanzidul Islam
5.00 /5

2 Courses

Md. Sanzidul Islam Lecturer, Dept. of CSE Convener, DIU NLP & ML Lab Daffodil International University Email;  [email protected]
Dr. S. M. Aminul Haque
5.00 /5

2 Courses

Dr. S. M. Aminul Haque Associate Professor and Associate Head Department of CSE Daffodil International University Email: [email protected]

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