Learn Python fundamentals you can start using right away to make better decisions and optimize engineering processes.
Proficiency in using Python is essential for engineers who manipulate and analyze data. And learning to master the fundamentals is easier than ever with help from this introductory course.
In five days, you鈥檒l master data engineering principles, including data collection and analysis, predictive analytics, and data visualization. You鈥檒l prepare to apply them in your workplace to improve the quality and efficiency of engineering systems and make better decisions. And, you鈥檒l be ready to take additional courses on machine learning, control and optimization.
Engineering-specific learning brings the content to life
You鈥檒l learn by doing throughout the course. You鈥檒l dive into case studies that provide an intuition for data engineering solutions. You鈥檒l also participate in a hands-on group project focused on engineering problems and theory. In no time, you鈥檒l gain a working fluency in state-of-the-art methods implemented in Python.
- Apply data engineering principles, including data collection, refining, cleansing, and preparation for various data science and engineering applications
- Become proficient using Python to manipulate and analyze data
- Access different types of data鈥攊ncluding text, audio, video, databases, sensors, and web scraping鈥攁nd work with diverse data sources
- Analyze time-dependent data patterns with time-series data and by applying techniques like ARX modeling and state space analysis
- Visualize data, perform statistical analysis, and create insights from data
Beginner level with no prior programming experience needed.
Times listed are Eastern Standard Time (EST)
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Day 1 (Time) |
Data-Driven Engineering with Python |
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9:45 AM |
Log-in and System Check |
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10 AM |
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11 AM |
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11:30 AM |
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12 PM |
Lunch Break |
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12:45 PM |
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1:30 PM |
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1:50 PM |
Break |
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2 PM |
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2:30 PM |
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3 PM |
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3:30 PM |
Knowledge Assessment and Review |
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4 PM |
Conclude Day 1 |
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Day 2 |
Data Access with Python |
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10 AM |
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10:30 AM |
1锔� Text |
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11:30 AM |
2锔� Audio |
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12 PM |
Lunch Break |
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12:45 PM |
3锔� Video |
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1:20 PM |
4锔� Database |
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1:50 PM |
5锔� Sensors |
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2:20 PM |
Break |
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2:30 PM |
6锔� Cloud |
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3:00 PM |
7锔� Web Scraping |
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3:30 PM |
Knowledge Assessment and Review |
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4 PM |
Conclude Day 2 |
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Day 3 |
Data-Engineering with Python |
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10 AM |
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10:15 AM |
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11 AM |
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11:30 AM |
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12 PM |
Lunch Break |
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12:45 AM |
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1:15 PM |
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1:45 PM |
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2:15 PM |
Break |
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2:30 PM |
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2:50 PM |
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3:10 PM |
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3:30 PM |
Knowledge Assessment and Review |
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4 PM |
Conclude Day 3 |
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Day 4 |
Data Streams and Time Series with Python |
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10 AM |
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10:30 AM |
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11 AM |
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11:30 AM |
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12 PM |
Lunch Break |
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12:45 PM |
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1:30 PM |
Time-Series Data |
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2:15 PM |
Break |
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2:30 PM |
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3 PM |
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3:30 PM |
Knowledge Assessment and Review |
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4 PM |
Conclude Day 4 |
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Day 5 |
Self-Guided Project or |
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10 AM |
Individual / Group Project Introduction |
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12 PM |
Lunch Break |
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2:15 PM |
Break |
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2:30 PM |
Presentations |
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3:30 PM |
Summarize Course and Certificates |
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4 PM |
Conclude Day 5 |
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