LinkedIn – Python: Working with Predictive Analytics 2025-3

Python: Working with Predictive Analytics. This course teaches programmers how to use Python and predictive analytics techniques to identify future patterns in data and extract valuable information for business decisions. In this course, you will learn, along with data scientist Esil Berkun, the steps of data preparation, including filling in missing values, normalizing features, and using Python libraries such as pandas and NumPy to build and evaluate predictive models. You will also learn how to choose the right models for different projects and how to apply them in practice. The course includes interactive coding challenges with CoderPad, which allow you to hone your skills with hands-on exercises and immediate feedback. By participating in this course, you will be able to use data to predict future trends and improve business decisions.

What you will learn:

• How to predict data in Python
• Distinguishing between data types
• Using Python libraries and importing data
• Handling missing values ​​in data
• Converting categorized data to numbers
• Splitting data into training and testing sets
• Performing Feature Scaling to improve model performance
• Introduction to different forecasting models
• Using Linear Regression for Prediction
• Using Polynomial Regression to Model Nonlinear Relationships
• Introduction to Support Vector Regression (SVR)
• Using Decision Tree Regression for Tree-Based Predictions
• Using Random Forest Regression to Improve Prediction Accuracy
• Evaluating forecasting models using different criteria
• Performing Hyperparameter Optimization to tune models

Who is this course suitable for?

• Programmers who want to work with Predictive Analytics in Python.
• Data analysts who are looking to learn how to predict future trends and patterns.
• Data science enthusiasts who want to use Python to build predictive models.
• Anyone who wants to learn how to prepare data and evaluate predictive models.

Python: Working with Predictive Analytics Course Details

• Publisher: LinkedIn
• Instructor: Isil Berkun
• Education level: Intermediate
• Training duration: 2 hours and 13 minutes

Course topics

Python: Working with Predictive Analytics course images

Sample course video

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256 MB