Data scientists are “big data” wranglers, gathering and analyzing large sets of structured and unstructured data. A data scientist’s role combines computer science, statistics, and mathematics. Data scientists are in high demand. They analyze, process, and model data then interpret the results to create actionable plans for companies and other organizations.
“Data scientists are anomaly spotters”, said Dr. Steven C. Lindo, Chairman & CEO of SpringBoard Incubators Inc. Meaning that they follow a technique for Exploratory Data Analysis (or EDA). This method uses data visualizations techniques to look for outliers in datasets.
At SpringBoard, our Data Science workshops use the Python programming language for data analysis. We use it natively or with platforms like Google Colab or Jupyter IPython.
Python is perfect for scientific computing, here are the main components you will learn to use at SpringBoard:
- Basic Python: Basic data types (Containers, Lists, Dictionaries, Sets, Tuples), Functions, Classes
- Numpy: Arrays, Array indexing, Datatypes, Array math, Broadcasting
- Matplotlib: Plotting, Subplots, Images
- Pandas: Data analysis methods and tools.
- IPython or Colab: Creating notebooks, Typical workflows
Our next blog in “A Data Science Story” will use these tools to provide insights into census data from surrounding villages in Nassau County.