Paro Classroom

near Le Méridien Riverfront, thimphu hwy, Shaba, Paro, Bhutan, 12001

Set in Paro, this classroom is well located near Paro-Thimphu Highway around 4 km from the airport, and 7 km from Rinpung Dzong, and possess all amenities and WiFi.

For Sales Enquires and Meetings

All our centres have batches running on weekdays and weekends hence, please note that, in most cases, usually we are not able to organise ad hoc sales meetings, especially on our classrooms as they are all occupied with ongoing training sessions . Please contact us by e-mail or phone at least one day earlier to make an appointment with one of our consultants at our corporate offices.

Subcategories (2)

Random Forest

Random Forest
AdaBoost

AdaBoost

Explore Our Courses

LightGBM for Machine Learning

 21 Hours
This instructor-led, live training in Paro (online or onsite) is aimed at beginner to intermediate-level developers and data scientists who wish to learn the basics of LightGBM and explore advanced techniques. By the end of this training, participants will be able to:
  • Install and configure LightGBM.
  • Understand the theory behind gradient boosting and decision tree algorithms
  • Use LightGBM for basic and advanced machine learning tasks.
  • Implement advanced techniques such as feature engineering, hyperparameter tuning, and model interpretation.
  • Integrate LightGBM with other machine learning frameworks.
  • Troubleshoot common issues in LightGBM.
Read more...

AdaBoost Python for Machine Learning

 14 Hours
This instructor-led, live training in Paro (online or onsite) is aimed at data scientists and software engineers who wish to use AdaBoost to build boosting algorithms for machine learning with Python. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building machine learning models with AdaBoost.
  • Understand the ensemble learning approach and how to implement adaptive boosting.
  • Learn how to build AdaBoost models to boost machine learning algorithms in Python.
  • Use hyperparameter tuning to increase the accuracy and performance of AdaBoost models.
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Machine Learning with Random Forest

 14 Hours
This instructor-led, live training in Paro (online or onsite) is aimed at data scientists and software engineers who wish to use Random Forest to build machine learning algorithms for large datasets. By the end of this training, participants will be able to:
  • Set up the necessary development environment to start building machine learning models with Random forest.
  • Understand the advantages of Random Forest and how to implement it to resolve classification and regression problems.
  • Learn how to handle large datasets and interpret multiple decision trees in Random Forest.
  • Evaluate and optimize machine learning model performance by tuning the hyperparameters.
Read more...

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Upcoming Courses

AdaBoost Python for Machine Learning

2025-06-09 09:30
14 hours
Paro Classroom
168661 BTN (Online)
186459 BTN (Classroom)

Machine Learning with Random Forest

2025-06-23 09:30
14 hours
Paro Classroom
168661 BTN (Online)
186459 BTN (Classroom)

AdaBoost Python for Machine Learning

2025-07-07 09:30
14 hours
Paro Classroom
168661 BTN (Online)
186459 BTN (Classroom)

Machine Learning with Random Forest

2025-07-21 09:30
14 hours
Paro Classroom
168661 BTN (Online)
186459 BTN (Classroom)

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Consulting

Ensemble Learning Consulting
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