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Unclaimed ProfileThe landscape of data engineering is undergoing a massive shift with the integration of Generative AI and Large Language Models (LLMs). This course, led by industry expert Dan Sullivan, provides a comprehensive, hands-on introduction to leveraging GenAI technologies to streamline, automate, and optimize modern data workflows. Designed specifically for beginners, the curriculum bridges the gap between foundational data engineering principles and cutting-edge artificial intelligence. Students will discover how to use intelligent assistants to generate precise Python scripts, construct complex SQL queries, and author Bash automation scripts. The course places a heavy emphasis on practical, real-world scenarios, including automated data quality assessments, schema generation, and analytical data modeling. By mastering prompt engineering tailored specifically for data tasks, learners will be equipped to build robust data pipelines far more efficiently than using traditional manual coding methods alone. Whether you are an aspiring data professional or an established software developer, this program offers the essential skills needed to stay competitive in an AI-accelerated data industry.
About the creator
Dan Sullivan
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Dan Sullivan is a seasoned technology educator and consultant recognized for his ability to distill complex architectural concepts into actionable, real-world instruction. With a career deeply rooted in the evolution of cloud computing and data infrastructure, Dan has spent years navigating the shift from legacy on-premise systems to modern, scalable data pipelines. His professional journey is defined by a commitment to demystifying technical barriers, particularly as the industry transitions into the era of Generative AI. In his role as an instructor on AllPros, Dan brings a pragmatic approach to his curriculum, focusing on the intersection of traditional data engineering principles…Show more
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Program Overview
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Learning format
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What You'll Learn
- Leverage Large Language Models (LLMs) to automatically generate, debug, and optimize Python code for ETL and ELT data pipelines.
- Utilize generative AI tools to assess data quality, identify anomalies, and formulate automated cleaning rules for incoming datasets.
- Construct complex SQL scripts and design robust relational or analytical data models using AI-driven schema generation techniques.
- Write and execute Bash scripts created by generative assistants to automate repetitive file movements, server tasks, and system configurations.
- Prompt AI models effectively to convert unstructured or semi-structured data sources into structured formats suitable for data warehousing.
- Implement automated documentation processes for database schemas and data pipelines using AI-generated metadata.
Best For
- Data engineers and developers looking to accelerate their coding speed using AI assistants.
- IT professionals aiming to modernize their ETL/ELT pipeline workflows with Generative AI.
- Data analysts who want to leverage LLMs to generate complex SQL queries and schema designs.
- Technical professionals interested in automating routine data quality checks and documentation tasks.
Not For
- Individuals with zero prior knowledge of Python, SQL, or basic data modeling concepts.
- Experienced machine learning engineers looking for advanced model training or fine-tuning techniques.
- Learners seeking a deep dive into data architecture theory rather than practical, tool-based implementation.
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