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Data Science in Health Care. Basic statistical analysis.

BeginnerGuided Project

ELISA is a commonly used laboratory test to detect antibodies in the blood. An antibody is a protein produced by the body's immune system when it detects harmful substances, called antigens. In this project you will learn how to download, prepare and make statistical analysis of ELISA tests and collected information about IgG and IgM, vaccination influenza, vaccination tuberculosis and other diseases and blood groups.

4.5 (170 Reviews)

Language

  • English

Topic

  • Data Analysis

Industries

  • Healthcare

Enrollment Count

  • 2.41K

Skills You Will Learn

  • Data Science, Machine Learning, Artificial Intelligence

Offered By

  • IBM

Estimated Effort

  • 30 minutes

Platform

  • SkillsNetwork

Last Update

  • May 19, 2024
About This Guided Project
This project will give you a practical introduction to basics of analyzing ELISA test data using readily available data science tools. You will download a real ELISA dataset, prepare it for statistical analysis, and analysis of information about IgG and IgM antibodies as they apply to the influenza and tuberculosis vaccination.

 Learning Objectives

 After completing this project you will be able to: 
  • Download test datasets (Excel files .xlsx) to use them in Python
  • Automatically clean and prepare data in dataset
  • Transform the table
  • Visualize data with Pandas and Seaborn, two very popular data analysis and visualization libraries 
You will be able to create basic statistical analysis of the ELISA data deriving:
  • Minimum and maximum values
  • Averages
  • Quarters
  • and create pivot tables

Instructors

Yaroslav Vyklyuk

Full Professor, Doctor of Computer Science, PhD

Dr. Yaroslav Vyklyuk is a full professor at the Lviv Polytechnic National University, Department of Artificial Intelligence Systems. He is an author of over 210 scientific works, 10 monographs, and books, a member of the Editorial Board of 6 international scientific journals, member of the Academic Councils on protection Ph.D. and DrSc thesis in "Mathematical modeling and computational methods". Research Interests: Data Science, Applied System Analysis, Mathematical Modeling, and Decision Making of Complex Dynamic Systems (socio-economic, geographical, tourist, and crisis systems) using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, Econometrics, Econophysics and other Advanced Mathematical Methods with implementation into information, WEB, and geographic information systems.

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Kateryna Hazdiuk

PhD of Software Engineering

I am an assistant professor at the Yuriy Fedcovych Chernivtsi National University, Software of Computer Systems Department; an author of over 40 scientific works and 10 training manuals. Research Interests: Mathematical Modeling of Complex Dynamic Systems (bio-like systems, socio-economic, geographical systems), Data Science, Decision Making using Artificial Intelligence Technology, DataMining, Big Data, Parallel Calculations, Statistics, and other methods.

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