Experimentation (A/B) Analyst

SQL Course

The SQL course Basics to Advance provides learners with a strong foundation in querying and managing product and user data stored in relational databases. Participants learn SQL syntax, database concepts, SELECT statements, filtering, sorting, joins, aggregate functions, grouping, subqueries, views, and basic data manipulation techniques. Through hands-on exercises and SaaS product datasets, learners develop practical skills to retrieve, organize, and analyze user behavior, conversion, and engagement data, supporting effective A/B testing and product experimentation.

Python/R Course

The Python/R Course Basics to Advance equips learners with advanced analytical and statistical programming skills for experimentation and product analytics. Participants learn data preprocessing, statistical testing, hypothesis validation, A/B test analysis, regression techniques, probability distributions, visualization, automation, and performance optimization using Python or R. Through real-world SaaS experimentation projects, the course prepares learners to analyze experimental results, validate product changes, and make data-driven product decisions.

Experimentation Platforms Course

The Experimentation Platforms Course Basics to Advance focuses on designing, executing, and monitoring controlled experiments using modern A/B testing platforms. Participants learn experiment design, randomization, audience segmentation, traffic allocation, feature flagging, success metrics, statistical significance, experiment monitoring, result interpretation, and rollout strategies. Through practical product scenarios, the course develops the skills required to run reliable experiments that optimize product performance, user engagement, and conversion rates.

Microsoft Excel Course

The Microsoft Excel Course Basics to Advance provides comprehensive training in organizing, analyzing, and presenting experimentation data using advanced spreadsheet techniques. Participants learn advanced formulas, PivotTables, PivotCharts, lookup functions, conditional formatting, Power Query, dashboards, What-If Analysis, statistical functions, and reporting automation. Through hands-on A/B testing projects and product datasets, the course enables learners to summarize experiment outcomes, visualize key metrics, and generate professional reports that support product strategy and business decision-making.