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Porto

NobleProg Porto, Av. da Boavista 1466, Porto, portugal, 4100-114

Our Venue is located on the city center of Porto, well connect by public transportation, with easy access by car with many options of parking places around the area. Surrounded by a large number of restaurants and commercial centres.

Four Points by Sheraton Matosinhos

188, Rua Sousa Aroso 188, 4450-286 Matosinhos, Matosinhos, Portugal, 4450-286 Matosinhos

Whether you travel for business, leisure or bleisure, Four Points by Sheraton Matosinhos welcomes you with four-star comfort, outstanding service and an ideal location in the city. The hotel offers a wide variety of facilities and services including a business center. Matosinhos beach is only 5 minutes walking distance from the hotel, perfect for surfing and other water sports. As a fishing area, local restaurants offer you the most wonderful fresh fishes and sea food for your delight.

Holiday Inn Porto - Gaia

220, Rua Diogo Macedo, 220, Vila Nova de Gaia 4400-107 , Gaia, Portugal

From Porto by Metro

If you're coming from Porto city centre:

  1. Take the Metro Line D (yellow line) toward Vila d’Este.
  2. Get off at João de Deus.
  3. From João de Deus, walk about 13 minutes to:
    Rua Diogo Macedo 220, 4400-107 Vila Nova de Gaia.

From Vila Nova de Gaia train station

If by “local train station” you mean Vila Nova de Gaia-Devesas:

  • The address is approximately 12 minutes walking from Vila Nova de Gaia station according to the accommodation's location information.
  • You can therefore walk directly rather than taking the metro.

Hotel Central Parque

83, Av. Visc. de Barreiros 83, 4470-151 Maia, Maia, Portugal, 4470-151 Maia

Hotel Central Parque **** is located in the center of the city of Maia, due to its proximity to Francisco Sá Carneiro Airport, Zona Industrial da Maia, Exponor Matosinhos, the metro station and the main highways, it becomes the place ideal for your stay.

Explore Our Courses

Explainability in Deep Learning: Demystifying Black-Box Models

 21 Hours

This instructor-led, live training in Porto (online or onsite) is targeted at advanced-level professionals who wish to investigate cutting-edge XAI techniques for deep learning models, focusing on the development of interpretable AI systems.

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

  • Understand the challenges of explainability in deep learning.
  • Implement advanced XAI techniques for neural networks.
  • Interpret decisions made by deep learning models.
  • Evaluate the trade-offs between performance and transparency.
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Applied AI from Scratch in Python

 28 Hours
This hands-on training in Porto empowers programmers to construct AI models from the ground up using Python. Participants will gain proficiency in supervised learning, neural networks, and unsupervised techniques by leveraging scikit-learn and Apache Spark. The programme emphasises practical Jupyter exercises focused on solving real-world problems.
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Deep Reinforcement Learning with Python

 21 Hours
This live, instructor-led training in Porto explores both the theoretical basis and practical execution of Deep Reinforcement Learning using Python. Attendees will learn to construct and train DRL agents with TensorFlow or PyTorch, applying critical algorithms such as DQN and PPO to address intricate real-world challenges.
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Artificial Intelligence (AI) Overview

 7 Hours
An introductory course on Porto that delves into the principles of AI, ranging from intelligent agents to machine learning. This training empowers executives and architects to evaluate emerging AI trends, integrate practical solutions, and enhance business agility through automated strategies.
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Artificial Intelligence (AI) in Automotive

 14 Hours
Discover how Machine Learning and Deep Learning are reshaping the automotive industry. This Porto course explores fundamental concepts, progressing from simple automation to autonomous decision-making, and includes insights into neural networks as well as practical TensorFlow examples for real-world implementation.
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Artificial Neural Networks, Machine Learning, Deep Thinking

 21 Hours
This three-day program in Porto provides a comprehensive exploration of the theoretical and practical aspects of Artificial Neural Networks, Machine Learning, and Deep Learning. Participants will examine various network architectures, learning mechanisms, and underlying mathematical foundations, progressing from fundamental perceptrons to sophisticated deep learning methodologies.
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Pattern Recognition

 21 Hours

This instructor-led, live training in Porto (online or onsite) provides an introduction into the field of pattern recognition and machine learning. It touches on practical applications in statistics, computer science, signal processing, computer vision, data mining, and bioinformatics.

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

  • Apply core statistical methods to pattern recognition.
  • Use key models like neural networks and kernel methods for data analysis.
  • Implement advanced techniques for complex problem-solving.
  • Improve prediction accuracy by combining different models.
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Introduction to the Use of Neural Networks

 7 Hours
This introductory module outlines the core concepts of neural networks within Porto, covering AI fundamentals, neuron mechanics, activation functions, and network architecture. Learners will acquire knowledge of backpropagation, training methodologies, and real-world use cases, including stock market forecasting.
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Understanding Deep Neural Networks

 35 Hours
This 35-hour course on Porto explores the fundamentals of deep neural networks, including CNNs, RNNs, and generative models such as GANs. Participants will gain practical experience with Theano and TensorFlow, learning to build, train, and deploy production-grade deep learning models for real-world applications.
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Testimonials (4)

Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.

Matthew Gay - Tarsus Pharmaceuticals

Course - Artificial Intelligence (AI) Overview

Working from first principles in a focused way, and moving to applying case studies within the same day

Maggie Webb - Department of Jobs, Regions, and Precincts

Course - Artificial Neural Networks, Machine Learning, Deep Thinking

It felt like we were going through directly relevant information at a good pace (i.e. no filler material)

Maggie Webb - Department of Jobs, Regions, and Precincts

Course - Introduction to the use of neural networks

That it was applying real company data. Trainer had a very good approach by making trainees participate and compete

Jimena Esquivel - Zaklad Uslugowy Hakoman Andrzej Cybulski

Course - Applied AI from Scratch in Python

Provisional Upcoming Courses (Contact Us For More Information)

Understanding Deep Neural Networks

2026-11-18 09:30
35 hours
Porto

Explainability in Deep Learning: Demystifying Black-Box Models

2026-12-02 09:30
21 hours
Porto

Explainability in Deep Learning: Demystifying Black-Box Models

2026-12-16 09:30
21 hours
Porto

Artificial Neural Networks, Machine Learning, Deep Thinking

2026-12-30 09:30
21 hours
Porto

Applied AI from Scratch in Python

2027-01-13 09:30
28 hours
Porto

Explainability in Deep Learning: Demystifying Black-Box Models

2027-01-27 09:30
21 hours
Porto

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