Data Science

Data mining, analysis, visualization, and extracting insights from data.

Data Preprocessing

Cleaning, transforming, and preparing raw data for analysis and modeling.

Feature Engineering

Creating, selecting, and transforming features to improve model performance.

Exploratory Data Analysis

Visualization, statistical summaries, and discovering patterns in data.

Pattern discovery, association rules, and knowledge extraction at scale.

Data Visualization

Charts, dashboards, and visual storytelling with data.

Statistical Testing

Hypothesis testing, A/B testing, p-values, and significance analysis.

Spark, Hadoop, distributed computing, and processing data at scale.

Data Collection

Web scraping, APIs, survey design, and building quality datasets.

Experiment Design

Sampling strategies, randomized experiments, and statistical study design.