Exploratory Data Analysis and Visualization
Session with George Anadiotis (Founder, Principal Consultant, Linked Data Orchestration)
About this Session
Uncovering Hidden Patterns in Data
Transform raw data into actionable insights through the power of exploratory analysis and visualization. This session reveals how to uncover the stories hidden within datasets before applying complex algorithms.
We learn how to analyze single variables to understand distributions, examine relationships between pairs of variables, navigate multidimensional data, and use visualization to transforms complex findings into visual narratives that drive decision-making. We'll also introduce hypothesis testing, showing how to validate your discoveries with statistical rigor.
Ideal for professionals who want to understand how data scientists separate signal from noise and communicate findings that drive strategic advantage in the age of AI.
- Outline
- Introduction
- Univariate Analysis
- Bivariate Analysis
- Multivariate Analysis
- Principal Component Analysis (PCA)
- Multidimensional Scaling
- t-Distributed Stochastic Neighbor Embedding
- Data Visualization
- Hypothesis Testing
- Format
- This session is lecture-based.
- Level
- Beginner
- Prerequisite Knowledge
- Data Science and Statistical Analysis
- Learning Outcomes
- Knowledge of key statistical data analysis and visualization techniques
