Worcester, MA – Regus at Campus Square

370 Main Street, Worcester, United States, 01608

The venue is located in the LEED Gold–certified Campus Square building at 370 Main Street in the heart of Worcester, easily reachable by car via I‑290 or I‑90, with abundant on-site parking and municipal garages nearby. From Worcester Regional Airport (ORH), about 5 miles west, a taxi or rideshare takes 10–15 minutes via Airport Drive and Main Street. Public transit is seamless: multiple WRTA bus routes stop just outside the building, and Worcester Amtrak/MBTA train station is an easy 12-minute walk, allowing easy access without a car.

Subcategories (2)

Random Forest

Random Forest
AdaBoost

AdaBoost

Explore Our Courses

LightGBM for Machine Learning

 21 Hours

This instructor-led, live training in Worcester (online or onsite) is designed for government developers and data scientists at the beginner to intermediate level who wish to learn the fundamentals of LightGBM and explore advanced techniques.

By the end of this training, participants will be able to:

  • Install and configure LightGBM for government use.
  • Understand the theoretical foundations of gradient boosting and decision tree algorithms.
  • Utilize LightGBM for both basic and advanced machine learning tasks.
  • Implement advanced techniques, including feature engineering, hyperparameter tuning, and model interpretation.
  • Integrate LightGBM with other machine learning frameworks used in government applications.
  • Address common issues that arise when using LightGBM for government projects.
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AdaBoost Python for Machine Learning

 14 Hours

This instructor-led, live training in Worcester (online or onsite) is designed for data scientists and software engineers who wish to utilize AdaBoost to develop boosting algorithms for machine learning with Python.

By the end of this training, participants will be able to:

  • Establish the required development environment to begin building machine learning models with AdaBoost.
  • Gain a comprehensive understanding of the ensemble learning methodology and how to implement adaptive boosting techniques.
  • Acquire the skills to construct AdaBoost models to enhance machine learning algorithms in Python.
  • Apply hyperparameter tuning to optimize the accuracy and performance of AdaBoost models for government applications.
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Machine Learning with Random Forest

 14 Hours

This instructor-led, live training in Worcester (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to develop machine learning algorithms for large datasets.

By the end of this training, participants will be able to:

  • Configure the required development environment to initiate building machine learning models with Random Forest.
  • Comprehend the benefits of Random Forest and its application in addressing classification and regression challenges.
  • Manage large datasets and interpret multiple decision trees within the Random Forest framework.
  • Assess and enhance machine learning model performance through hyperparameter tuning, ensuring optimal results for government applications.
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Upcoming Courses

AdaBoost Python for Machine Learning

2026-01-19 09:30
14 hours
Worcester, MA – Regus at Campus Square
$ 2703 (Online)
$ 3903 (Classroom)

AdaBoost Python for Machine Learning

2026-02-02 09:30
14 hours
Worcester, MA – Regus at Campus Square
$ 2703 (Online)
$ 3903 (Classroom)

AdaBoost Python for Machine Learning

2026-02-16 09:30
14 hours
Worcester, MA – Regus at Campus Square
$ 2703 (Online)
$ 3903 (Classroom)

AdaBoost Python for Machine Learning

2026-03-02 09:30
14 hours
Worcester, MA – Regus at Campus Square
$ 2703 (Online)
$ 3903 (Classroom)

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