Programming3: Time Series, Streaming, and Signal Data Processing

Overview

This course focuses on practical skills for processing and analyzing time series, streaming, and signal data using popular data science tools such as:

• Jupyter Notebooks
• NumPy
• Pandas
• Bokeh

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Learning Outcomes

1. Data Loading and Cleaning

   • Techniques for importing and preparing streaming data for analysis.

2. Data Analysis

   • Exploratory Data Analysis (EDA) to uncover patterns and trends in time series and signal data.

3. Data Visualization

   • Creating effective visualizations to communicate insights using tools like Bokeh.

4. Maintainable Solutions

   • Writing reusable, maintainable code for real-world data processing pipelines.

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Key Outcomes

• Understand the complete data processing pipeline.
• Be able to handle diverse types of streaming data.
• Conduct exploratory data analysis with confidence.
• Create effective visualizations to present your findings.
• Build a strong foundation for future research and exploration in time series and signal analysis.

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Tools Used

You will work with the following tools throughout this course:

• Jupyter Notebooks
• NumPy
• Pandas
• Bokeh

Contact

• m.zamani.fard@st.hanze.nl