Data Science 🐍 Python Course

Python 🐍 Data Science with the TCLab

As with the beginning course, this course has video tutorials for each exercise if you have questions along the way. One of the unique things about this course is that you work on basic elements and then test your knowledge with real data exercises with a heat transfer design project. You will see your Python code have a real impact by designing the materials for a new product.

One of the best ways to start or review a programming language is to work on a project. These exercises are designed to teach data science Python programming skills. Data science applications are found across almost all industries where raw data is transformed into actionable information that drives scientific discovery, business innovations, and development. This project is to determine the thermal conductivity of several materials. Thermal conductivity is how well a material conducts or insulates against heat transfer. The specific heat transfer project shows how to apply data science to solve an important problems with methods that are applicable to many different applications.

Objective: Collect and analyze data from the TCLab to determine the thermal conductivity of three materials (metal, plastic, and cardboard) that are placed between two temperature sensors. Create a digital twin that predicts heat transfer and temperature.

To make the problem more applicable to a real situation, suppose that you are designing a next-generation cell phone. The battery and processor on the cell phone generate a lot of heat. You want to make sure that the material between them will prevent over-heating of the battery by the processor. This study will help you answer questions about material properties for predicting the temperature of the battery and processor.

Topics

1. Data Science 🐍 Course Overview
2. Data Science 🐍 Import / Export
3. Data Science 🐍 Analyze
4. Data Science 🐍 Visualize
5. Data Science 🐍 Prepare Data
6. Data Science 🐍 Regression
7. Data Science 🐍 Features
8. Data Science 🐍 Classification
9. Data Science 🐍 Interpolation
10. Data Science 🐍 Solve Equations
11. Data Science 🐍 Differential Equations
12. Data Science 🐍 Time Series
Data Science 🐍 Final Project

[abdulia]

I have been noticing a lot of hype over data science and I am quite surprise you are making a course on it. I think ill give it a try. Is it possible to apply data science in any chemical engineering related process plant other than just temperature control?

[arneg]

Thanks for the resources. Will you be going over each part of the course here on YouTube? This is great for me to find more data analysis skills in the real world.

[haeuptling]

Thank you for your great videos! Might it be possible to avoid the picture of a real snake as a thumbnail? Seeing the picture in the thumbnail and during the intro puts me in a panic and stress situation. Maybe others have the same issue and avoid your videos because of that.

[osvaldoillescas]

Hi there! Sorry for bringing another topic, but do you know how to install/use APOPT with Pyomo? I don't understand how to use it, and I want to try it.

[johncarlosmora]

Regards, excuse my question, I am a beginner, I want to start handling astrophysics data, some people using versions of python 2.7 and others 3.7, my question is, should I start learning Python 3.7? I will not have problems using the programs made with python 2.7? What do you recommend me ??? thanks for your time

[j]

Hellow sir I’m thinking that taking chemical engineering was a wrong decision recently and I read some topics on it and I’m unable to cope with it.Can you tell me was it a bad selection?