Python-Training-Course

Printout of training materials will be available for the attendees.

Python Training Courses for Data Analysis The training will consist of following sections.

Part 1: Python Variable
- Definition of variable
- How to create Python variable
- Variable type : String & Number
- List
- Tuple
- Dictionary
- Data Variable
Part 2: Basic Data Wrangling and Function/Class
- Boolean Class
- Conditional Statement
- For Statement
- While Statement
- Function
- Lambda
- Class
- Import function/class
Part 3: Numpy and Pandas
- Numpy
- Pandas
  - Series
  - DataFrame
Part 4: Reading and Writing files
- Text files
- CSV files
- Excel(.xlsx) files
- JSON files
- Numpy files
- HDF5 files
- SAS files (sas7bdat, xpt)
Part 5: Advanced DAta Analysis
- Merging
- Reshaping (concatenating, transposing)
- Metadata Analysis
- Statistical Analysis
  - Descriptive Statistics
  - Frenquency
  - Pair t-test
  - Fisher Exact Test
  - Survival Analysis - Log Rank Test
Part 6: Data Visualization
- matplotlib
- Scatter Plot
- Sub plot
Part 7: Machine Learning
- Logistic Regression
- SVM
- DNN
- CNN
Part 8: SDTM DM Creation
- import demographic, randomization, exposure, disposition data from the local drive
- merge and prepare data
- write CDISC DM.xpt to local drive

For those who have never used Jupyter notebook, there is a document of "Instruction of Anaconda Installation" for Window.

Name		Name	Last commit message	Last commit date
Latest commit History 59 Commits
data		data
Comparison of two datasets just like SAS PROC COMPARE.ipynb		Comparison of two datasets just like SAS PROC COMPARE.ipynb
Instruction of Anaconda Installation and ML algorithms import v2.pdf		Instruction of Anaconda Installation and ML algorithms import v2.pdf
Part 1 - Python Variables.ipynb		Part 1 - Python Variables.ipynb
Part 2 - Basic Data Wrangling, Functions and Classes.ipynb		Part 2 - Basic Data Wrangling, Functions and Classes.ipynb
Part 3 - Numpy and Pandas.ipynb		Part 3 - Numpy and Pandas.ipynb
Part 4 - Reading and writing files.ipynb		Part 4 - Reading and writing files.ipynb
Part 5 - Advanced Data Analysis.ipynb		Part 5 - Advanced Data Analysis.ipynb
Part 6 - Data Visualization.ipynb		Part 6 - Data Visualization.ipynb
Part 7 - Image Classification using Machine Learning (LR, SVM, DNN, CNN).ipynb		Part 7 - Image Classification using Machine Learning (LR, SVM, DNN, CNN).ipynb
Part 7 - Reading MNIST image from local drive.ipynb		Part 7 - Reading MNIST image from local drive.ipynb
Part 8 - SDTM DM creation.ipynb		Part 8 - SDTM DM creation.ipynb
README.md		README.md
TS dataset creation using Python.ipynb		TS dataset creation using Python.ipynb
utility.py		utility.py