Course 2: Data Science Syllabus

Course Objectives

• To learn how to work with tabular data using the pandas library

• To learn the basics of digital signal processing with time-series data using the numpy and scipy libraries

• To learn the basics of image processing with image data using the opencv library

• To learn how to generate useful visualizations using the matplotlib library

Lectures 1 & 2: Tabular Data

• Motivation 
• Numpy
• Pandas

Lectures 3 & 4: Time Series Data – Time Domain

• Motivation
• Matplotlib
• Handling Time
• Data Sampling
• Data Windowing
• Time-Domain Features

Lectures 5 & 6: Time Series Data – Frequency Domain

• Motivation
• Trigonometry
• Fast Fourier Transform
• Spectrograms
• Frequency-Domain Features
• Signal Noise
• Digital Filters

Lectures 7 & 8: Image Data

• Motivation
• Colors
• Shapes
• Image Manipulation
• Image Kernels
• Thresholding
• Outlines

Lectures 9 & 10: Exploring Real Datasets

• Exploring a Time-Series Dataset: Parkinsonian Gait
• Exploring an Image Dataset: Skin Cancer

Register for the course