Python Programming Made Easy for Engineers | AIChE

Python Programming Made Easy for Engineers

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’ll master data engineering principles, including data collection and analysis, predictive analytics, and data visualization. You’ll prepare to apply them in your workplace to improve the quality and efficiency of engineering systems and make better decisions. And, you’ll be ready to take additional courses on machine learning, control and optimization.

Engineering-specific learning brings the content to life  

You’ll learn by doing throughout the course. You’ll dive into case studies that provide an intuition for data engineering solutions. You’ll also participate in a hands-on group project focused on engineering problems and theory. In no time, you’ll 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—including text, audio, video, databases, sensors, and web scraping—and 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)

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

1️ Basics

11:30 AM

2️ Tuple

12 PM

Lunch Break

12:45 PM

3️ List

1:30 PM

4️ Set

1:50 PM

Break

2 PM

5️ Dictionary

2:30 PM

6️ NumPy

3 PM

7️ 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

1️ Text

11:30 AM

2️ Audio

12 PM

Lunch Break

12:45 PM

3️ Video

1:20 PM

4️ Database

1:50 PM

5️ Sensors

2:20 PM

Break

2:30 PM

6️ Cloud

3:00 PM

7️ 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

1️ Gather Data

11 AM

2️ Statistics

11:30 AM

3️ Visualize

12 PM

Lunch Break

12:45 AM

4️ Cleanse

1:15 PM

5️ Features

1:45 PM

6️ Balance

2:15 PM

Break

2:30 PM

7️ Scale

2:50 PM

8️ Split

3:10 PM

9️ 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

1️ MODBUS

11 AM

2️ MQTT

11:30 AM

3️ OPC UA

12 PM

Lunch Break

12:45 PM

4️ WebSocket

1:30 PM

Time-Series Data

1️ Pandas

2:15 PM

Break

2:30 PM

2️ ARX Model

3 PM

3️ 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

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  • Course ID:
    CH271
  • Source:
    AIChE
  • Language:
    English
  • Skill Level:
    Basic
  • Duration:
    5 days
  • CEUs:
    2.40
  • PDHs:
    24.00
  • Accrediting Agencies:
    Florida
    New Jersey
    New York
    RCEP