The crash courses cover various subjects at the pre-introductory and introductory level in computational engineering. The crash courses will include programming languages, fundamental numerical methods, parallel programming, high performance computing, machine learning, cloud computing etc. A list of our past crash courses can be found below.

### Introduction to Data Science

Description: this short course covers basic topics in data science.

Exercises: Jupyter Notebook examples

Case Studies

Slides(PDF)

### Introduction to Graph Analytics

Description: this short course covers basic topics in graph analytics and NetworkX.

Exercises: Jupyter Notebook examples

Case Studies

Slides(PDF)

### Exploratory Data Analysis with pandas and matplotlib

Description: this short course covers basic procedures to carry out exploratory data analysis with pandas and matplotlib.

Exercises: Jupyter Notebook examples

Case Studies

Slides(PDF)

### Introduction to Machine Learning with scikit-learn

Description: this short course introduces the basic concepts of machine learning and some widely used machine learning algorithms with scikit-learn.

Exercises: Jupyter Notebook examples

Case Studies

Slides(PDF)

### Introduction to Deep Learning with Keras

Description: this short course introduces the basic concepts of deep learning algorithm with Keras.

Exercises: Jupyter Notebook examples

Case Studies

Slides(PDF)