Boston, MA – Regus at Federal Street

101 Federal St, Suite 1900, Boston, United States, 02110

The venue is located in the heart of Boston’s Financial District on Federal Street, easily accessible by car via I‑90, I‑93, and I‑95 with numerous nearby parking garages. From Logan International Airport (BOS), a taxi or rideshare takes approximately 20–25 minutes via I‑93 North. Public transit is seamless: the 15th Street and South Station – Financial District stops on MBTA's Red, Orange, and Silver lines are within a few minutes’ walk, and multiple bus routes traverse Federal and Congress Streets.

Burlington, MA – Regus at The District

1500 District Avenue, Burlington, United States, 01803

The venue is located within The District business campus at 1500 District Avenue, easily accessed by car via I‑89 or US‑3 with free on-site parking and additional municipal lots. From Boston’s Logan International Airport (BOS), approximately 15 miles southeast, a taxi or rideshare takes 25–30 minutes via I‑93 North and I‑95 North. Public transit is served by MBTA commuter rail to South Burlington, with the Campus Parkway #2 bus running directly past the entrance—placing the venue within a short walk for attendees without cars.

Cambridge, MA – Regus at Harvard Square

One Mifflin Place, Suite 400, Cambridge, United States, 02138

The venue is ideally situated in the heart of Harvard Square at One Mifflin Place, easily accessed by car via Route 2, MA‑2A, or Memorial Drive, with pay-to-park garages and metered street spaces nearby. From Boston Logan International Airport (BOS), taxis or rideshares take approximately 25–30 minutes via I‑90 West and Cambridge Street. Alternatively, public transit offers seamless connections: take the MBTA Red Line to Harvard station, and the entrance is a 3-minute walk from the square, providing effortless access for attendees without cars.

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.

Explore Our Courses

Federated Learning and Edge AI

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at advanced-level AI researchers, data scientists, and security specialists who wish to implement federated learning techniques for training AI models across multiple edge devices while preserving data privacy.

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

  • Understand the principles and benefits of federated learning in Edge AI.
  • Implement federated learning models using TensorFlow Federated and PyTorch.
  • Optimize AI training across distributed edge devices.
  • Address data privacy and security challenges in federated learning.
  • Deploy and monitor federated learning systems in real-world applications.
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Federated Learning for Secure AI Collaboration

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level AI and data professionals who wish to understand and implement federated learning techniques for privacy-preserving machine learning and collaborative AI solutions across distributed data sources.

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

  • Understand the core concepts and benefits of federated learning.
  • Implement distributed training strategies for AI models.
  • Apply federated learning techniques to secure data-sensitive collaborations.
  • Explore case studies and practical examples of federated learning in healthcare and finance.
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Federated Learning in IoT and Edge Computing

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

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

  • Understand the principles and benefits of Federated Learning in IoT and edge computing.
  • Implement Federated Learning models on IoT devices for decentralized AI processing.
  • Reduce latency and improve real-time decision-making in edge computing environments.
  • Address challenges related to data privacy and network constraints in IoT systems.
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Federated Learning for Finance

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning techniques to enhance data privacy and collaborative AI in the financial industry.

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

  • Understand the principles and benefits of Federated Learning in finance.
  • Implement Federated Learning models for privacy-preserving financial applications.
  • Analyze financial data collaboratively without compromising privacy.
  • Apply Federated Learning to real-world financial scenarios, such as fraud detection and risk management.
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Federated Learning for Healthcare

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to healthcare scenarios, ensuring data privacy and effective collaboration across institutions.

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

  • Understand the role of Federated Learning in healthcare.
  • Implement Federated Learning models while ensuring patient data privacy.
  • Collaborate on AI model training across multiple healthcare institutions.
  • Apply Federated Learning to real-world healthcare case studies.
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Advanced Federated Learning Techniques

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at advanced-level professionals who wish to master cutting-edge Federated Learning techniques and apply them to large-scale AI projects.

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

  • Optimize Federated Learning algorithms for improved performance.
  • Handle non-IID data distributions in Federated Learning.
  • Scale Federated Learning systems for large-scale deployments.
  • Address privacy, security, and ethical considerations in advanced Federated Learning scenarios.
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Federated Learning for Privacy-Preserving AI

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level professionals who wish to understand and apply Federated Learning to ensure data privacy in AI development.

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

  • Understand the principles and benefits of Federated Learning.
  • Implement privacy-preserving machine learning models using Federated Learning techniques.
  • Address the challenges of data privacy in decentralized AI training.
  • Apply Federated Learning in real-world scenarios across various industries.
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Introduction to Federated Learning

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at beginner-level professionals who wish to learn the fundamentals of Federated Learning and its practical applications.

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

  • Understand the principles of Federated Learning.
  • Implement basic Federated Learning algorithms.
  • Address data privacy concerns using Federated Learning.
  • Integrate Federated Learning into existing AI workflows.
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Upcoming Courses

Federated Learning for Finance

2025-08-13 9:30 am
14 hours
Burlington, MA – Regus at The District
$ 2703 (Online)
$ 3703 (Classroom)

Federated Learning for Finance

2025-08-27 9:30 am
14 hours
Burlington, MA – Regus at The District
$ 2703 (Online)
$ 3703 (Classroom)

Advanced Federated Learning Techniques

2025-09-10 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

Federated Learning in IoT and Edge Computing

2025-09-24 9:30 am
14 hours
Burlington, MA – Regus at The District
$ 2703 (Online)
$ 3703 (Classroom)

Advanced Federated Learning Techniques

2025-10-08 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

Federated Learning for Healthcare

2025-10-22 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

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