Data Analytics & Engineering
This training begins with the foundations of data and a method for framing an analytics project. You will then explore the use of Python and the Pandas library to manipulate and analyze your datasets. The program covers applied statistics, with a focus on descriptive analysis, correlations, and regressions. You will also study star schema modeling, ETL/ELT processes, and the medallion architecture. In addition, the session presents the different Azure data services across relational, non-relational, and analytical environments. Finally, you will learn to present your results with Power BI, while completing a capstone project and preparing for the DP-900 mock exam.
Objectives
Understand the foundations of data and how to frame an analytics project methodically. Use Python and the Pandas library to manipulate, clean, and analyze datasets. Apply descriptive statistics, correlation analysis, and regression models to real data. Design a star schema data model and implement ETL/ELT pipelines. Understand and apply the medallion architecture (Bronze, Silver, Gold). Identify and use Azure data services across relational, non-relational, and analytical workloads. Restitute analytical results effectively with Power BI. Prepare for the DP-900 certification exam through a corrected mock exam.
Target audience
Aspiring and practicing data analysts, data engineers, and BI professionals looking to master the end-to-end data pipeline — from ingestion and transformation to modeling and reporting.
Prerequisites
Basic knowledge of spreadsheets and information systems recommended. No prior programming experience strictly required, but familiarity with Python is a plus.
Target certification
This course prepares you for the DP-900 — Microsoft Azure Data Fundamentals. certification.
Instructors
Original Name
Updated bio.
Upcoming sessions
No session scheduled yet. Contact us to hear about the next cohort.
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