NobleProg Training Place, City Bismarck, ND - Juniper Workantile

Bismarck, ND - Juniper Workantile

122 North 4th St., Bismarck, United States, 58501

The venue is located in historic downtown Bismarck at 122 North 4th Street, easily accessible by car via I‑94 or US‑83 with street and nearby garage parking available. From Bismarck Municipal Airport (BIS), take Highway 83 South into town—a taxi or rideshare typically takes about 10 minutes. Public transit users can take Bis‑Man Transit bus routes stopping within a block on 4th Street, followed by a short walk to the venue.
NobleProg Training Place, City Fargo, ND - Regus - Brandt Office Park

Fargo, ND - Regus - Brandt Office Park

3523 45th Street South, Suite 100, Fargo, United States, 58104

The venue is located just off I‑29 in Fargo’s well-connected Brandt Office Park, easily accessible by car via exit 65 on I‑29; free on-site parking is available for all attendees. From Hector International Airport (FAR), take I‑29 South, exit at 45th Street, and drive approximately 5 minutes—taxi or rideshare options are plentiful. Public transit is also convenient with local MATBUS routes stopping near 45th Street South, followed by a short walk into the business park.
NobleProg Training Place, City Fargo, ND - Railyard Offices NobleProg Training Place, City Fargo, ND - Railyard Offices

Fargo, ND - Railyard Offices

1630 1st Avenue North, Suite B, Fargo, United States,  58102

The venue is situated in the midst of downtown Fargo at 1630 1st Avenue North, conveniently accessible by car via I‑94 or I‑29 with exits onto 1st Avenue North; public parking is available nearby. From Hector International Airport, take I‑94 East to exit toward downtown, then follow signs to 1st Avenue North—approximately a 15‑minute taxi or rideshare ride. Public transit riders can use MATBUS routes that stop within walking distance, and the venue is located in a pedestrian-friendly area.

Explore Our Courses

Federated Learning and Edge AI

 21 Hours

This instructor-led, live training in North Dakota (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 North Dakota (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 North Dakota (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 North Dakota (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 North Dakota (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 North Dakota (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

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This instructor-led, live training in North Dakota (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 North Dakota (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.
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Upcoming Courses

Federated Learning for Finance

2025-08-13 9:30 am
14 hours
Fargo, ND - Regus - Brandt Office Park
$ 2703 (Online)
$ 2703 (Classroom)

Federated Learning for Finance

2025-08-27 9:30 am
14 hours
Fargo, ND - Regus - Brandt Office Park
$ 2703 (Online)
$ 2703 (Classroom)

Advanced Federated Learning Techniques

2025-09-10 9:30 am
21 hours
Fargo, ND - Regus - Brandt Office Park
$ 4054 (Online)
$ 4054 (Classroom)

Federated Learning in IoT and Edge Computing

2025-09-24 9:30 am
14 hours
Fargo, ND - Regus - Brandt Office Park
$ 2703 (Online)
$ 2703 (Classroom)

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