- Statistical Modeling
- Data Collection
- Data Presentation
- Machine Learning Methods
- Data Wrangling
- Data-Driven Decision-Making
- Exploratory Data Analysis
- Web Scraping
- Pandas (Python Package)
- Data Science
- Predictive Modeling
- GitHub
Applied Data Science Capstone
Completed by KITAEK LEE
June 2, 2020
13 hours (approximately)
KITAEK LEE's account is verified. Coursera certifies their successful completion of Applied Data Science Capstone
What you will learn
Demonstrate proficiency in data science and machine learning techniques using a real-world data set and prepare a report for stakeholdersÂ
Apply your skills to perform data collection, data wrangling, exploratory data analysis, data visualization model development, and model evaluation
Write Python code to create machine learning models including support vector machines, decision tree classifiers, and k-nearest neighbors
Evaluate the results of machine learning models for predictive analysis, compare their strengths and weaknesses and identify the optimal modelÂ
Skills you will gain

