Statsmodels Courses and Certifications

Introduction to Regression with statsmodels in Python

3026 ratings at DataCamp

Use Python statsmodels For Linear and Logistic Regression Linear regression and logistic regression are two of the most widely used statistical models.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Intermediate Regression with statsmodels in Python

596 ratings at DataCamp

Linear regression and logistic regression are the two most widely used statistical models and act like master keys, unlocking the secrets hidden in datasets.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

ARIMA Models in Python

423 ratings at DataCamp

Fit ARMA, ARIMA, ARMAX and seasonal ARIMA models in Python with statsmodels: test stationarity, pick orders using ACF/PACF and AIC/BIC, and forecast stock prices.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Derek Banas

Linear Regressions with StatsModels - Data Science Tutorial

Create linear regressions with StatsModels, using Python data-science libraries and example datasets to examine professor ratings and tipping.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Regression Analysis – Fundamentals & Practical Applications

90 ratings at Corporate Finance Institute

Explore the Essentials of Linear Regression: Building and Applying Models in Excel and Python for Real-World Data Analysis Delve into the core principles of linear regression analysis and its significance in understanding variable relationships

• Corporate Finance Institute
• 2 hours 29 minutes
• Self-Paced
• Paid Course

Time-Series Forecasting

Forecast time series with spreadsheets, BI tools, classical models, neural networks, and foundation models while evaluating uncertainty and business trade-offs.

• Udacity
• 16 hours
• Self-Paced
• Paid Course

Inferential Statistical Analysis with Python

938 ratings at Coursera

Estimate population parameters and test hypotheses in Python: construct confidence intervals for five parameter types, analyze categorical and quantitative data with Statsmodels, Pandas, and Seaborn.

• Coursera
• 4 weeks, 5 hours a week
• Self-Paced
• Paid Course

NPTEL-NOC IITM

Hands-on Python: Fitting Regression Models with Sklearn and Statsmodels - Part 3

Fit regression models using sklearn and statsmodels in Python. Learn model setup, evaluation, and implementation techniques.

• YouTube
• 13 minutes
• Self-Paced
• Free Video

Fitting Statistical Models to Data with Python

718 ratings at Coursera

Fit statistical models to data in Python: linear and logistic regression, generalized linear models, multilevel and marginal models, and Bayesian inference using Statsmodels, Pandas and Seaborn.

• Coursera
• 4 weeks, 4 hours a week
• Self-Paced
• Paid Course

Python for Time Series Data Analysis

9117 ratings at Udemy

Learn how to use Python , Pandas, Numpy , and Statsmodels for Time Series Forecasting and Analysis!

• Udemy
• 15 hours 21 minutes
• Self-Paced
• Paid Course

Time Series Analysis in Python

2857 ratings at Udemy

Time Series Analysis in Python: Theory, Modeling: AR to SARIMAX, Vector Models, GARCH, Auto ARIMA, Forecasting

• Udemy
• 7 hours 21 minutes
• Self-Paced
• Paid Course

NPTEL-NOC IITM

Hands-on with Python for Regression Coefficient Estimation - Part 1

Gain insights into estimating regression coefficients in Python and implementing regression models with the statsmodel package.

• YouTube
• 13 minutes
• Self-Paced
• Free Video