Schedule
Asynchronous
Delivery method
Online
Data Analysis with Python
0 credit hours
Credits awarded upon completion
Self-Paced
Progress at your own speed
15.64 hours
Estimated learning time
About the Course
Description
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’ll 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’ll build linear, multiple, and polynomial regression models, construct data pipelines, and refine your models for better accuracy.
Through hands-on labs and projects, you’ll 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’ll not only develop strong data analysis skills but also earn a Coursera certificate and an IBM digital badge to showcase your achievement.
This Course is part of a program
You can only buy it along with program.
Sections
Deliverables
0 Credits
Academic Excellence
Earn necessary number of credit hours for completing this content
Hone Important Skills
Total Upgrade
Such as Regression Analysis, Scikit Learn (Machine Learning Library), Data Manipulation, Data Analysis, Pandas (Python Package), Descriptive Statistics, NumPy, Predictive Modeling, Exploratory Data Analysis, Data Wrangling, Matplotlib, Data Pipelines, Statistical Modeling, Feature Engineering, Data Cleansing, Data Import/Export, Supervised Learning, Data-Driven Decision-Making
