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Python and Data Handling


The course builds proficiency through hands-on learning in mathematics, statistics, computer programming, key data science concepts and Python.


  1. A High School Diploma or equivalent such as a General Education Diploma (GED) from an institution of higher education accredited by an accrediting association recognized by the US Department of Education.
  2. Completion of Colaberry Data Analytics program or equivalent.

8 weeks

Class meets 2 days/week

2:00 PM CST to 5:00 PM CST

6:30 PM CST to 9:30 PM CST


Module 1: The Process of Data Science
(2 class hours)

  • What is Data Science?
  • Thinking Through Data Science Problems

Module 2: Python for Data Scientists
(24 class hours; 48 lab hours)

  • Python and Jupyter Notebooks
  • Data Structures in Python
  • Dealing with Strings and Dates
  • Decision Statements and Loops
  • Libraries and Functions
  • Computations with Numpy
  • Data Analysis with Pandas
  • Data Visualization with Matplotlib and Plotly
  • Statsmodels in Python
  • scikit-learn

Module 3: Data Handling for Data Scientists
(24 class hours; 48 lab hours)

  • Data and Data Formats
  • Relational Data
  • SQL in Python
  • Working with a Variety of File Formats in Python
  • File I/O in Python
  • Data Imports Using APIs
  • Web Scraping Using Python
  • Merging Data from Various Sources
  • Data Cleaning

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