Augusta AI/ML Data Engineering Meetup Group

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Augusta, GA, US

About us

Welcome to the Augusta AI/ML Data Engineering Meetup Group! This group is for data enthusiasts, engineers, and machine learning/AI professionals interested in sharing knowledge, networking, and collaborating on projects related to data engineering. Whether you're a beginner just starting to learn about AI and ML, or a seasoned professional looking to share your expertise, this group provides a supportive and inclusive community for all. Join us for discussions, workshops, and hands-on coding sessions to explore the latest trends and technologies in data engineering. Let's build a strong data engineering community in Augusta together!

Upcoming events

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Week 1 Data Engineering: Source Systems & Ingestion
Sun, Mar 22 · 11:00 AM EDT
·
Online
Online
## 12 to 16 Week Data Engineering Course

## Textbook and Readings

The most effective way to teach Data Engineering is in the order that mirrors real, on‑the‑job data engineering work structuring the 16‑week sequence around the actual lifecycle of a production data platform.
In industry, data engineers don’t learn concepts in isolation—they learn them while building, breaking, fixing, and scaling real pipelines.
Therefore, I will follow this instructional flow:
1. Start with how data is generated and moves (Source Systems & Ingestion)
2. How engineers think and collaborate (Intro to DE)
3. Where data lives and how it’s queried (Storage & Queries)
4. How data is modeled, transformed, and served (Modeling & Serving)
6 attendees
Week 1 Data Engineering: Source Systems & Ingestion
Sun, Mar 29 · 11:00 AM EDT
·
Online
Online
## 12 to 16 Week Data Engineering Course

## Textbook and Readings

The most effective way to teach Data Engineering is in the order that mirrors real, on‑the‑job data engineering work structuring the 16‑week sequence around the actual lifecycle of a production data platform.
In industry, data engineers don’t learn concepts in isolation—they learn them while building, breaking, fixing, and scaling real pipelines.
Therefore, I will follow this instructional flow:
1. Start with how data is generated and moves (Source Systems & Ingestion)
2. How engineers think and collaborate (Intro to DE)
3. Where data lives and how it’s queried (Storage & Queries)
4. How data is modeled, transformed, and served (Modeling & Serving)
2 attendees
Week 1 Data Engineering: Source Systems & Ingestion
Sun, Apr 5 · 11:00 AM EDT
·
Online
Online
## 12 to 16 Week Data Engineering Course

## Textbook and Readings

The most effective way to teach Data Engineering is in the order that mirrors real, on‑the‑job data engineering work structuring the 16‑week sequence around the actual lifecycle of a production data platform.
In industry, data engineers don’t learn concepts in isolation—they learn them while building, breaking, fixing, and scaling real pipelines.
Therefore, I will follow this instructional flow:
1. Start with how data is generated and moves (Source Systems & Ingestion)
2. How engineers think and collaborate (Intro to DE)
3. Where data lives and how it’s queried (Storage & Queries)
4. How data is modeled, transformed, and served (Modeling & Serving)
2 attendees
Week 1 Data Engineering: Source Systems & Ingestion
Sun, Apr 12 · 11:00 AM EDT
·
Online
Online
## 12 to 16 Week Data Engineering Course

## Textbook and Readings

The most effective way to teach Data Engineering is in the order that mirrors real, on‑the‑job data engineering work structuring the 16‑week sequence around the actual lifecycle of a production data platform.
In industry, data engineers don’t learn concepts in isolation—they learn them while building, breaking, fixing, and scaling real pipelines.
Therefore, I will follow this instructional flow:
1. Start with how data is generated and moves (Source Systems & Ingestion)
2. How engineers think and collaborate (Intro to DE)
3. Where data lives and how it’s queried (Storage & Queries)
4. How data is modeled, transformed, and served (Modeling & Serving)
1 attendee