BYTE SIZE CLASS: Data Engineering & AI: From Data to Deployment
Go beyond theory. Work with real data, build machine learning models, and deploy AI systems using practical tools and guided instruction.
BYTE SIZE CLASS: Data Engineering & AI: From Data to Deployment
Duration: 3 hours
Format: In-person
Audience: Beginner to Intermediate (18+)
Materials Needed:
- Laptop (Python installed or access to Google Colab)
- Basic familiarity with Python (helpful, not required)
- Pen and notebook for notes
Step into the engine behind AI. In this hands-on workshop, you’ll explore how raw data becomes intelligent systems through real-world data engineering and machine learning workflows.
Designed to feel practical and accessible, this session blends guided instruction with a live mini-project—so you don’t just learn concepts, you apply them.
If you’re curious about how AI actually works behind the scenes, this is your entry point.
What You’ll Explore Along the Way:
📊 The Data Lifecycle — Understand how data moves from collection to actionable insights
🔄 Data Engineering Foundations — Learn pipelines, ETL processes, and batch vs. streaming systems
⚡ Real-Time Data with Kafka — See how high-volume data is processed in real time
🧠 Preparing Data for AI — Clean, transform, and engineer features for machine learning
🤖 Model Development — Train and evaluate a classification model using real-world data
🚀 Deployment — Launch your model with an API and test it in action
Hands-On Experience
You’ll work through a guided mini-project focused on digital marketing use cases, where you will:
- Load and explore real-world data
- Clean and preprocess datasets
- Engineer features using industry techniques
- Train and evaluate a machine learning model
- Deploy your model using FastAPI
Skills You’ll Build:
- Data pipeline design and workflow thinking
- ETL and data preprocessing techniques
- Feature engineering fundamentals
- Machine learning model training and evaluation
- Real-time vs. batch processing concepts
- Practical coding experience with Python and SQL
Why This Workshop Matters
AI doesn’t work without data—and strong data workflows are what separate theory from real-world impact. This session breaks down complex systems into clear, practical steps so you can understand how AI is built, deployed, and scaled.
Whether you’re exploring a career in tech, strengthening your current skillset, or building your first AI project, you’ll leave with both knowledge and a working solution to build on.
Go beyond theory. Work with real data, build machine learning models, and deploy AI systems using practical tools and guided instruction.
BYTE SIZE CLASS: Data Engineering & AI: From Data to Deployment
Duration: 3 hours
Format: In-person
Audience: Beginner to Intermediate (18+)
Materials Needed:
- Laptop (Python installed or access to Google Colab)
- Basic familiarity with Python (helpful, not required)
- Pen and notebook for notes
Step into the engine behind AI. In this hands-on workshop, you’ll explore how raw data becomes intelligent systems through real-world data engineering and machine learning workflows.
Designed to feel practical and accessible, this session blends guided instruction with a live mini-project—so you don’t just learn concepts, you apply them.
If you’re curious about how AI actually works behind the scenes, this is your entry point.
What You’ll Explore Along the Way:
📊 The Data Lifecycle — Understand how data moves from collection to actionable insights
🔄 Data Engineering Foundations — Learn pipelines, ETL processes, and batch vs. streaming systems
⚡ Real-Time Data with Kafka — See how high-volume data is processed in real time
🧠 Preparing Data for AI — Clean, transform, and engineer features for machine learning
🤖 Model Development — Train and evaluate a classification model using real-world data
🚀 Deployment — Launch your model with an API and test it in action
Hands-On Experience
You’ll work through a guided mini-project focused on digital marketing use cases, where you will:
- Load and explore real-world data
- Clean and preprocess datasets
- Engineer features using industry techniques
- Train and evaluate a machine learning model
- Deploy your model using FastAPI
Skills You’ll Build:
- Data pipeline design and workflow thinking
- ETL and data preprocessing techniques
- Feature engineering fundamentals
- Machine learning model training and evaluation
- Real-time vs. batch processing concepts
- Practical coding experience with Python and SQL
Why This Workshop Matters
AI doesn’t work without data—and strong data workflows are what separate theory from real-world impact. This session breaks down complex systems into clear, practical steps so you can understand how AI is built, deployed, and scaled.
Whether you’re exploring a career in tech, strengthening your current skillset, or building your first AI project, you’ll leave with both knowledge and a working solution to build on.
Good to know
Highlights
- 3 hours
- ages 18+
- In person
- Free parking
- Doors at 5:30 PM
Refund Policy
Location
CodeCrew HQ
460 S. Highland Street
Memphis, TN 38111
How do you want to get there?
