Inference Courses and Certifications

Stanford Seminar - Theories of Inference for Visual Analysis

Explore theories of visual inference, including uncertainty visualization, effect size judgments, and Bayesian cognition. Learn how visualizations support causal inference and model checks in data analysis.

• YouTube
• 1 hour
• On-Demand
• Free Online Course

Bayesian Networks 1 - Inference - Stanford CS221: AI

Explore Bayesian networks for AI, covering probabilistic inference, modeling, and applications in object tracking, language modeling, and document classification.

• YouTube
• 1 hour 22 minutes
• On-Demand
• Free Online Course

Machine Learning and AI Foundations: Causal Inference and Modeling

136 ratings at LinkedIn Learning

Learn about the modeling techniques and experimental designs that allow you to establish causal inference, and how to use them.

• LinkedIn Learning
• 2 hours 51 minutes
• On-Demand
• Free Trial Available

Learn the Basics of Causal Inference with R

20 ratings at Codecademy

Learn conceptual foundations and practical techniques for determining causal relationships in data. Master matching, weighting, instrumental variables, and difference-in-differences methods to uncover why things happen.

• Codecademy
• 4 hours
• On-Demand
• Free Trial Available

Difference in Differences for Causal Inference

20 ratings at Codecademy

Estimate causal effects by analyzing trends over time. Learn to implement Difference in Differences technique, mimic experiments, and solve real-world problems using existing data.

• Codecademy
• 1 hour
• On-Demand
• Free Trial Available

Potential Outcomes Framework for Causal Inference

13 ratings at Codecademy

Learn to estimate unmeasurable outcomes using the Potential Outcomes Framework for causal inference. Develop counterfactual thinking and a formal language to determine why things happen.

• Codecademy
• 1 hour
• On-Demand
• Free Trial Available

Causal Inference with Survey Data

12 ratings at LinkedIn Learning

Explore the concepts of causal inference in survey data, learn some of the underlying theory of causality, and focus on empirical methods to identify causality in data.

• LinkedIn Learning
• 2 hours 9 minutes
• On-Demand
• Free Trial Available

Learn techniques for balancing data, estimating treatment effects, and maximizing sparse datasets in causal analysis. Master matching, weighting, propensity scores, and stratification to prepare data and estimate unobserved outcomes.

• Codecademy
• 2 hours
• On-Demand
• Free Trial Available

Microcredential

Data Scientist: Inference Specialist

Master statistical inference, A/B testing, and causal analysis using Python, SQL, and R to become an expert at drawing meaningful conclusions from data experiments.

• Codecademy
• 85 hours
• On-Demand
• Free Trial Available

NIeCer 201: Causal Inference from Observational Studies [CAUSIT]

Gain insights into causal inference from observational studies, covering principles, study designs, statistical methods, validity threats, and causal diagrams for health researchers.

• Swayam
• On-Demand
• Free Online Course

IIT Kanpur;  NPTEL

Essentials of Data Science With R Software-1: Probability and Statistical Inference

Any data analysis is incomplete without statistics. After getting the data, the statistical tools aims to extract the information hidden inside the data.

• Swayam
• 12 weeks
• On-Demand
• Free Online Course

Using BigQuery Machine Learning for inference

Explore BigQuery ML for inference, create and manage ML models, and learn practical applications like movie poster analysis and wildlife image classification.

• Google Skills
• 3 hours
• On-Demand
• Paid Course

Cloud Run for AI Inference

AI inference is the process of using a trained machine learning model to make predictions on new, unseen data by applying learned patterns. This course is designed for developers, data scientists, and ML engineers interested in quickly deploying AI infer…

• Google Skills
• 1 hour 15 minutes
• On-Demand
• Free Online Course

Stanford Seminar - Multi-Sensory Neural Objects: Modeling, Inference, and Applications in Robotics

Exploring multi-sensory neural object representations for robotics, focusing on object-centric modeling, dataset creation, parameter inference, and manipulation applications.

• YouTube
• 1 hour 6 minutes
• On-Demand
• Free Video

Richard McElreath

Science Before Statistics - Causal Inference

Comprehensive workshop on causal inference, covering key concepts like causal design, graph analysis, and Bayesian inference. Equips researchers with tools to navigate complex causal relationships in data analysis.

• YouTube
• 3 hours 2 minutes
• On-Demand
• Free Video