- Data Cleansing
- Data Analysis
- Jupyter
- Data Science
- Pandas (Python Package)
- Data Manipulation
- Pivot Tables And Charts
- Probability & Statistics
- Programming Principles
- Numpy
- Statistical Analysis
- Data Import/Export
Introduction to Data Science in Python
Completed by Sung-yeon LIM
November 15, 2017
30 hours (approximately)
Sung-yeon LIM's account is verified. Coursera certifies their successful completion of Introduction to Data Science in Python
What you will learn
Understand techniques such as lambdas and manipulating csv files
Describe common Python functionality and features used for data science
Query DataFrame structures for cleaning and processing
Explain distributions, sampling, and t-tests
Skills you will gain
