Microsoft Data Engineering Certificate

Certificate Description

This comprehensive certification track demonstrates mastery across multiple domains in data management, programming, data science, and cloud engineering. It equips professionals with the skills needed to handle real-world data challenges and implement cutting-edge solutions.

Certifications Overview

Microsoft SQL Essentials (24 Hours):

Mastered foundational SQL concepts and techniques, including database querying, manipulation, and optimization for business intelligence and data analytics.

Implementing a SQL Data Warehouse (39 Hours):

Gained expertise in designing and implementing modern data warehouses using advanced SQL tools and methodologies to support scalable and efficient data storage solutions.

Python Programming Fundamentals (27 Hours):

Acquired proficiency in Python programming, focusing on core concepts, scripting, and automation, serving as a foundation for data-driven applications.

Data Science with Python (12 Hours):

Leveraged Python's libraries like Pandas, NumPy, and Matplotlib to analyze, visualize, and model data, enabling data-driven decision-making processes.

Azure Data Fundamentals (12 Hours):

Demonstrated understanding of cloud-based data solutions with Azure, including data storage, analytics, and relational/non-relational data models.

ML Ops Tools: MLflow and Hugging Face (12 Hours):

Developed skills in deploying and monitoring machine learning models using MLflow and Hugging Face frameworks, emphasizing real-world applications of MLOps.

Azure Data Engineer Associate (33 Hours):

Attained certification as a Data Engineer Associate, showcasing the ability to design and implement data solutions, including pipelines, storage, and security on Microsoft Azure.

This credential solidifies expertise in leveraging tools and technologies that power modern data solutions, making it ideal for data professionals, engineers, and analysts striving for excellence.