About Course
Overview
The Predictive Analytics with Python course is designed to equip learners with the knowledge and hands-on skills needed to build predictive models using Python programming. Predictive analytics helps organizations forecast outcomes, identify trends, and make data-driven decisions by applying statistical modeling, machine learning, and data analysis techniques.
This course covers everything from data preprocessing and feature engineering to building, evaluating, and deploying predictive models using Python libraries like scikit-learn, pandas, NumPy, and matplotlib. By the end, you will be able to apply predictive analytics to solve real-world business problems.
Course Details
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Duration: 6–8 weeks (self-paced / instructor-led)
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Mode: Online / Classroom / Blended
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Prerequisites:
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Basic understanding of Python programming
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Familiarity with statistics and probability
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Knowledge of data analysis concepts
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Course Content
Module 1: Introduction to Predictive Analytics
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What is predictive analytics?
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Applications across industries (finance, healthcare, retail, etc.)
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Predictive modeling process
Module 2: Python for Data Analysis
Module 3: Data Preprocessing and Feature Engineering
Module 4: Regression Models
Module 5: Machine Learning for Predictive Analytics
Module 6: Model Evaluation and Validation
Module 7: Time Series Forecasting
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