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Amaryllis2021 / Analysis_using_Python_Workshop_WIMTACH_CentennialCollege-

Detailed AGENDA of the workshop 1. Discuss the needs and applications of data analytics in the healthcare industry and give a description of the most recent trends in this field; Introduce Python, its features and use for data preprocessing and analyses. Explain Python libraries (Pandas, Numpy, Scipy, Statsmodels, Scikit-Learn, Matplotlib, Seaborn, Scrapy etc.) and their applications (1 hour). 2. Break (10 minutes). 3. Demonstration: Installing Python, Loading/importing data (CSV, Excel), selecting and filtering data, deleting columns, data cleaning, sorting, merging etc.(1.15 hours). 4. Break (10 minutes) 5. Demonstration continues Basic visualizations (Bar chart, Line chart, Scatter plot etc.)., and basic analysis: measures of central tendency(mean, median, mode)Correlation, Chi-Square and t-test. (1.15 hour). 7. Questions and Answers (10 minutes).

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Analysis_using_Python_Workshop_WIMTACH_CentennialCollege-

Detailed AGENDA of the workshop

  1. Discuss the needs and applications of data analytics in the healthcare industry and give a description of the most recent trends in this field; Introduce Python, its features and use for data preprocessing and analyses. Explain Python libraries (Pandas, Numpy, Scipy, Statsmodels, Scikit-Learn, Matplotlib, Seaborn, Scrapy etc.) and their applications (1 hour).

  2. Break (10 minutes).

  3. Demonstration: Installing Python, Loading/importing data (CSV, Excel), selecting and filtering data, deleting columns, data cleaning, sorting, merging etc.(1.15 hours).

  4. Break (10 minutes)

  5. Demonstration continues Basic visualizations (Bar chart, Line chart, Scatter plot etc.)., and basic analysis: measures of central tendency(mean, median, mode)Correlation, Chi-Square and t-test. (1.15 hour).

  6. Questions and Answers (10 minutes).

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Detailed AGENDA of the workshop 1. Discuss the needs and applications of data analytics in the healthcare industry and give a description of the most recent trends in this field; Introduce Python, its features and use for data preprocessing and analyses. Explain Python libraries (Pandas, Numpy, Scipy, Statsmodels, Scikit-Learn, Matplotlib, Seaborn, Scrapy etc.) and their applications (1 hour). 2. Break (10 minutes). 3. Demonstration: Installing Python, Loading/importing data (CSV, Excel), selecting and filtering data, deleting columns, data cleaning, sorting, merging etc.(1.15 hours). 4. Break (10 minutes) 5. Demonstration continues Basic visualizations (Bar chart, Line chart, Scatter plot etc.)., and basic analysis: measures of central tendency(mean, median, mode)Correlation, Chi-Square and t-test. (1.15 hour). 7. Questions and Answers (10 minutes).

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