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Machine Learning Algorithms


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 and Data Science-II programs 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: Regression Models - II (10 class hours; 24 lab hours)

  • Bias-Variance Tradeoff

  • Regularization
  • Support Vector Machines (SVM)
  • Kernel Tricks in SVMs and Regularization

Module 2: Classification Models - II (12 class hours; 30 lab hours)

  • Support Vector Machines

  • Decision Trees
  • Random Forests
  • Boosted Trees
  • XGBoost

Module 3: Unsupervised Learning Models (12 class hours; 30 lab hours)

  • Unsupervised Models
  • K-Means Clustering
  • Dimensionality Reduction
  • Hierarchical Clustering

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