Data-Driven Engineering Schedule
Data engineering is the process of collecting and refining data. Clean and accessible data is an important preparatory step for many use cases that extract information and value from data. Data engineering is foundational to visualization, clustering, classification, regression, and other machine learning methods. This introductory course is on science and engineering applications of data science with particular emphasis on practical applications and specific examples. The course is 5 days with 7-9 learning activities each day. Each module is designed to be completed in about 1 hour or less.
Day 1 (Time) | Data-Driven Engineering with Python |
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9:45 AM | Log-in and System Check |
10 AM |
Course Overview
Python for Data-Driven Engineering Install Python Install Packages |
11 AM | 1️⃣ Basics |
11:30 AM | 2️⃣ Tuple |
12 PM | Lunch Break |
12:45 PM | 3️⃣ List |
1:30 PM | 4️⃣ Set |
1:50 PM | Break |
2 PM | 5️⃣ Dictionary |
2:30 PM | 6️⃣ NumPy |
3 PM | 7️⃣ Pandas |
3:30 PM | Knowledge Assessment and Review |
4 PM | Conclude Day 1 |
Day 2 | Data Access with Python |
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10 AM | Data Access Overview |
10:30 AM | 1️⃣ Text 🗒 |
11:30 AM | 2️⃣ Audio 🔊 |
12 PM | Lunch Break |
12:45 PM | 3️⃣ Video 🎥 |
1:20 PM | 4️⃣ Database 🗃 |
1:50 PM | 5️⃣ Sensors 💻 |
2:20 PM | Break |
2:30 PM | 6️⃣ Cloud ⛅ |
3:00 PM | 7️⃣ Web Scraping 🌐 |
3:30 PM | Knowledge Assessment and Review |
4 PM | Conclude Day 2 |
Day 3 | Data-Engineering with Python |
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10 AM | Data Engineering Overview |
10:15 AM | 1️⃣ Gather Data |
11 AM | 2️⃣ Statistics |
11:30 AM | 3️⃣ Visualize |
12 PM | Lunch Break |
12:45 AM | 4️⃣ Cleanse |
1:15 PM | 5️⃣ Features |
1:45 PM | 6️⃣ Balance |
2:15 PM | Break |
2:30 PM | 7️⃣ Scale |
2:50 PM | 8️⃣ Split |
3:10 PM | 9️⃣ Deploy |
3:30 PM | Knowledge Assessment and Review |
4 PM | Conclude Day 3 |
Day 4 | Data Streams and Time Series with Python |
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10 AM | Data Transfer Overview |
10:30 AM | 1️⃣ MODBUS |
11 AM | 2️⃣ MQTT |
11:30 AM | 3️⃣ OPC UA |
12 PM | Lunch Break |
12:45 PM | 4️⃣ WebSocket |
1:30 PM |
Time-Series Data
1️⃣ Pandas |
2:15 PM | Break |
2:30 PM | 2️⃣ ARX Model |
3 PM | 3️⃣ State Space |
3:30 PM | Knowledge Assessment and Review |
4 PM | Conclude Day 4 |
Day 5 | Self-Guided Project or TCLab Project |
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10 AM | Individual / Group Project Introduction |
12 PM | Lunch Break |
2:15 PM | Break |
2:30 PM | Presentations |
3:30 PM | Summarize Course and Certificates |
4 PM | Conclude Day 5 |