Wilmington, DE – Regus at Brandywine Building

1000 North West Street, Suite 1200, Wilmington, United States, 19801

The venue is located in the prominent Brandywine Building in downtown Wilmington, easily reachable by car via I‑95 or I‑395, with several public parking garages nearby. Visitors arriving from Baltimore/Washington International Airport (BWI), about 25 miles southwest, can expect a taxi or rideshare ride of approximately 30–35 minutes via I‑95 North. Public transit is also an option: Wilmington Train Station is within a 5–10 minute walk, and local DART First State buses stop along Market and King Streets just steps from the entrance.

Dover, Delaware

101 W Loockerman St, Dover, United States, 19904

The venue at 101 W Loockerman Street is in downtown Dover, one block from Route 13, with convenient street and municipal parking. From Wilmington or Philadelphia, drive south via I‑95 to US‑13 and enter downtown; travel time is about 1 to 1½ hours. Public transit options include DART First State buses (routes 101 and 301) with stops near Loockerman Street, placing the venue a short walk away for attendees without a car.

Explore Our Courses

Large Language Models (LLMs) and Reinforcement Learning (RL)

 21 Hours

This instructor-led, live training in Delaware (online or onsite) is aimed at intermediate-level data scientists who wish to gain a comprehensive understanding and practical skills in both Large Language Models (LLMs) and Reinforcement Learning (RL).

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

  • Understand the components and functionality of transformer models.
  • Optimize and fine-tune LLMs for specific tasks and applications.
  • Understand the core principles and methodologies of reinforcement learning.
  • Learn how reinforcement learning techniques can enhance the performance of LLMs.
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Fine-Tuning with Reinforcement Learning from Human Feedback (RLHF)

 14 Hours

This instructor-led, live training in Delaware (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to apply RLHF to fine-tune large AI models for superior performance, safety, and alignment.

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

  • Understand the theoretical foundations of RLHF and why it is essential in modern AI development.
  • Implement reward models based on human feedback to guide reinforcement learning processes.
  • Fine-tune large language models using RLHF techniques to align outputs with human preferences.
  • Apply best practices for scaling RLHF workflows for production-grade AI systems.
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Reinforcement Learning with Google Colab

 28 Hours

This instructor-led, live training in Delaware (online or onsite) is aimed at advanced-level professionals who wish to deepen their understanding of reinforcement learning and its practical applications in AI development using Google Colab.

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

  • Understand the core concepts of reinforcement learning algorithms.
  • Implement reinforcement learning models using TensorFlow and OpenAI Gym.
  • Develop intelligent agents that learn through trial and error.
  • Optimize agents' performance using advanced techniques such as Q-learning and deep Q-networks (DQNs).
  • Train agents in simulated environments using OpenAI Gym.
  • Deploy reinforcement learning models for real-world applications.
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Deep Reinforcement Learning with Python

 21 Hours

This instructor-led, live training in Delaware (online or onsite) is aimed at developers and data scientists who wish to learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent.

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

  • Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning.
  • Apply advanced Reinforcement Learning algorithms to solve real-world problems.
  • Build a Deep Learning Agent.
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Fundamentals of Reinforcement Learning

 21 Hours

This instructor-led, live training in Delaware (online or onsite) is aimed at data scientists who wish to go beyond traditional machine learning approaches to teach a computer program to figure out things (solve problems) without the use of labeled data and big data sets.

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

  • Install and apply the libraries and programming language needed to implement Reinforcement Learning.
  • Create a software agent that is capable of learning through feedback instead of through supervised learning.
  • Program an agent to solve problems where decision making is sequential and finite.
  • Apply knowledge to design software that can learn in a way similar to how humans learn.
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Upcoming Courses

Large Language Models (LLMs) and Reinforcement Learning (RL)

2025-09-22 9:30 am
21 hours
Wilmington, DE – Regus at Brandywine Building
$ 4054 (Online)
$ 4054 (Classroom)

Fine-Tuning with Reinforcement Learning from Human Feedback (RLHF)

2025-10-06 9:30 am
14 hours
Wilmington, DE – Regus at Brandywine Building
$ 2703 (Online)
$ 2703 (Classroom)

Fundamentals of Reinforcement Learning

2025-10-20 9:30 am
21 hours
Wilmington, DE – Regus at Brandywine Building
$ 4054 (Online)
$ 4054 (Classroom)

Fundamentals of Reinforcement Learning

2025-11-03 9:30 am
21 hours
Wilmington, DE – Regus at Brandywine Building
$ 4054 (Online)
$ 4054 (Classroom)

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