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
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
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
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
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
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