- NumPy
- Regression Analysis
- Statistical Analysis
- Scikit Learn (Machine Learning Library)
- Data Visualization
- Pandas (Python Package)
- Data-Driven Decision-Making
- Data Manipulation
- Data Science
- Matplotlib
- Predictive Modeling
- Data Import/Export
Data Analysis with Python
Completed by Emmanuel Orololuwa Awolusi
July 20, 2020
17 hours (approximately)
Emmanuel Orololuwa Awolusi's account is verified. Coursera certifies their successful completion of Data Analysis with Python
What you will learn
Construct Python programs to clean and prepare data for analysis by addressing missing values, formatting inconsistencies, normalization, and binning
Analyze real-world datasets through exploratory data analysis (EDA) using libraries such as Pandas, NumPy, and SciPy to uncover patterns and insights
Apply data operation techniques using dataframes to organize, summarize, and interpret data distributions, correlation analysis, and data pipelines
Develop and evaluate regression models using Scikit-learn, and use these models to generate predictions and support data-driven decision-making
Skills you will gain
