Great analysis starts long before dashboards. In this masterclass, early-career Data Analysts learn how to design end-to-end analytics pipelines - from messy raw data to trusted business metrics - using the tools they already know: SQL, Python, Power BI, and Excel. The focus is on building analyses that are accurate, repeatable, and decision-ready.
- Thinking in Pipelines: How raw events become clean tables, metrics, and dashboards.
- SQL as the Foundation: Writing clean, reusable queries that power all downstream analysis.
- Python for Transformation: Automating cleaning, validation, and feature creation.
- Visualization with Purpose: Turning metrics into clear Power BI dashboards and Excel summaries.
- Data Quality Mindset: Building checks so numbers stay consistent over time.
Gaurav is an AI/ML Engineer at AWS, working on fine-tuning and evaluating large language models using structured datasets. He builds automated quality pipelines in Python and SageMaker dashboards that drive model improvement decisions. His expertise spans the ML lifecycle, including data validation, prompt engineering, RAG, REST APIs, and SQL-backed reporting, with strong backend experience in FastAPI, Django, and Flask. He is open to AI/ML Engineer, MLOps, and Applied AI opportunities.
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