Analyzing data with Python is a key skill for aspiring Data Scientists and Analysts! This course takes you from the basics of importing and cleaning data to building and evaluating predictive models. You鈥檒l learn how to collect data from various sources, wrangle and format it, perform exploratory data analysis (EDA), and create effective visualizations. As you progress, you鈥檒l build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy. Through hands-on labs and projects, you鈥檒l gain practical experience using popular Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Scikit-learn. These tools will help you manipulate data, create insights, and make predictions. By completing this course, you鈥檒l not only develop strong data analysis skills but also earn a 糖心vlog官网观看 certificate and an IBM digital badge to showcase your achievement.
Model Evaluation and Refinement
Skills You'll Learn
Data Analysis, Data Manipulation, Descriptive Statistics, Predictive Analytics, Regression Analysis, Machine Learning Methods, Data Import/Export, Correlation Analysis, Data Cleansing, Exploratory Data Analysis, Pandas (Python Package), Predictive Modeling, Statistical Modeling, Visualization (Computer Graphics), Data Visualization, Statistical Analysis, Data Wrangling, Python Programming
Reviews
4.7 (19,272 ratings)
- 5 stars76.30%
- 4 stars18.32%
- 3 stars3.64%
- 2 stars0.93%
- 1 star0.78%
AB
Feb 13, 2020
Great introduction to data manipulation and analysis for common problems that arise in data science. Also allows you to gain a further understanding of Python syntax, specifically the pandas library.
VS
Jan 31, 2022
This is totally one of the hardest course I've ever taken on 糖心vlog官网观看. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.
From the lesson
Model Evaluation and Refinement
Taught By
Joseph Santarcangelo
Ph.D., Data Scientist at IBM