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Foundations of Machine Learning


Data Science is a rapidly evolving field where you can train computers to make sense of data, reveal patterns and help predict the future. You will get to solve interesting and world changing problems, tinker with some of the amazing algorithms and learn to create solutions that know how to learn on their own. Python has become one of the most sought-after skills for a Data Scientist. You will learn and master Data Science with Python. Beginning from data frames to underpinnings of linear algebra to data visualization to Natural Language processing, you will become proficient applying data science in real-world projects.


  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 Science - I program or equivalent; alternatively, a proven relevant experience in the field
  3. Exposure to computer programming

8 weeks

Class meets 2 days/week

8:00 AM to 12:30 PM CST

6:30 PM to 9:30 PM CST


Module 1: Math & Statistics for Machine Learning (18 class hours; 45 lab hours)

  • Set Theory
  • Linear Algebra
  • Probability
  • Statistics
  • Measures of Central Tendency
  • Distributions and Associated Statistics
  • Outlier Analysis
  • Statistics Revisited
  • Prediction Models
Module 2: Regression Models - I (10 class hours; 20 lab hours)
  • Supervised Models and Linear Regression
  • Gradient Descent
  • Polynomial Regression
  • Cross Validation

Module 3: Classification Models - I (6 class hours; 9 lab hours)

  • Logistic Regression
  • Multiclass Logistic Regression
  • Naives Bayes Classifier

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