Data Analytics
Data Analytics: Foundations to Practice
A 14-module, in-depth data analytics course written to the standard of a FAANG-level internal training program: deep frameworks, named sources, real trade-offs, and common failure modes for each topic. This course is entirely conceptual and tool-agnostic — no programming language, SQL, or specific software syntax is taught — focusing instead on how to think rigorously about data, regardless of which tool eventually executes the analysis.
14 modules — log in to enroll and track your progress.
Log inModules
- 1.Foundations of Data Analytics4 chapters
- 2.Types and Sources of Data4 chapters
- 3.Descriptive Statistics Fundamentals4 chapters
- 4.Data Cleaning and Preparation4 chapters
- 5.Data Visualization Principles4 chapters
- 6.Correlation, Relationships, and Causation4 chapters
- 7.Statistical Inference Basics4 chapters
- 8.A/B Testing and Experimentation4 chapters
- 9.Business Metrics and KPIs4 chapters
- 10.Trend Analysis and Forecasting Concepts4 chapters
- 11.Segmentation and Cohort Analysis4 chapters
- 12.Data Storytelling and Communication4 chapters
- 13.Data Ethics, Privacy, and Bias4 chapters
- 14.Tools Landscape and Career Paths4 chapters