Ementorhub

What you'll learn

Leverage various generative AI tools and techniques in data engineering processes across industries

Implement various data engineering processes such as data generation, augmentation, and anonymization using generative AI tools

Practice generative AI skills in hands-on labs and projects for data warehouse schema design and infrastructure setup

Evaluate real-world case studies showcasing the successful application of Generative AI for ETL and data repositories

Skills you'll gain

Query Languages

Database Design

Data Mining

Data Ethics

Data Warehousing

Data Synthesis

Artificial Intelligence

Snowflake Schema

Generative AI

Data Pipelines

Data Quality

Extract, Transform, Load

Star Schema

Data Architecture

Data Analysis

Data Infrastructure

There are 3 modules in this course

Data engineering is responsible for building strong data pipelines, managing data infrastructure, and ensuring high-quality data evaluation. This course is suitable for existing and aspiring data engineers, data warehousing specialists, and other data professionals such as data analysts, data scientists and BI analysts. You will learn how to use and apply generative models for tasks such as architecture design, database querying, data warehouse schema design, data augmentation, data pipelines, ETL workflows, data analysis and mining, data lakehouse, and data repositories. You will also explore challenges and ethical considerations associated with using Generative AI. Demonstrate your new generative AI skills in a hands-on data engineering project that you can apply in your real-life profession. Then, complete your final quiz to earn your certificate. You can share both your project and certificate with your current or prospective employers.

Use of Generative AI for Data Engineering

Final Project and Exam