Python Regression & Forecasting: Data Science Guide
Master regression analysis and time series forecasting using Python. Learn advanced techniques for data preprocessing, modeling, and prediction.
Master regression analysis and time series forecasting using Python. Learn advanced techniques for data preprocessing, modeling, and prediction.
This comprehensive course equips data scientists with essential skills in regression analysis and forecasting using Python. Through four detailed modules, students master time-series analysis, forecasting techniques, and linear regression modeling. The curriculum covers everything from data preprocessing to advanced model creation, including ARIMA models, seasonal forecasting, and feature engineering. Designed for intermediate-level learners, the course combines theoretical knowledge with hands-on Python programming to enable data-driven decision-making in real-world scenarios.
4.7
(28 ratings)
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What you'll learn
Develop expertise in time series analysis and forecasting
Analyze techniques for exploratory data analysis
Understand various time-series models using Python
Prepare and preprocess data for regression modeling
Build and interpret linear regression models
Master seasonal forecasting techniques
Skills you'll gain
This course includes:
347 Minutes PreRecorded video
21 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
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There are 4 modules in this course
This course provides comprehensive training in regression analysis and forecasting techniques using Python. Through four modules, students learn time-series analysis, forecasting methods, data preprocessing, and linear regression modeling. The curriculum progresses from basic concepts to advanced applications, covering topics such as ARIMA models, seasonal forecasting, feature engineering, and model evaluation. Participants gain hands-on experience with real-world datasets, learning to build and validate predictive models for various business applications.
Time-Series Analysis and Forecasting
Module 1 · 3 Hours to complete
Time-Series Models
Module 2 · 3 Hours to complete
Linear Regression - Data Preprocessing
Module 3 · 2 Hours to complete
Linear Regression - Model Creation
Module 4 · 2 Hours to complete
Fee Structure
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Instructor
Empowering Learners through Skill-Based Education
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4.7 course rating
28 ratings
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