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Monterrey - Oficinas en el Parque

Boulevard Díaz Ordaz 140, , Monterrey, Mexico, 64650

The Monterrey Officinas en el Parque Center is in a tall, dark glass-faced building surrounded by landscaped grounds with fountains and lakes, and located on Boulevard Constitucion, at the west end of the most important east to west arterial road in the city.

Monterrey - El Milagro

Apodaca 1350, El Milagro , Monterrey, Mexico, 66637

Forge connections with clients across North America, Canada, Latin America, Asia, and Europe via direct flights from Monterrey International Airport, conveniently located just 11km away. Broaden your professional horizons throughout the Monterrey Metro Area utilizing the city’s exceptional road network, frequent local bus services, and extensive Metro system. Relax after a day's work with a delightful meal at one of the many local restaurants. Enjoy a leisurely stroll through Arroyo Park or cheer on Real Apodaca F.C. at the Estadio Municipal de Apodaca, a mere 4km away.

Subcategories (5)

Stable Diffusion

Stable Diffusion
TensorFlow

TensorFlow
Neural Networks

Neural Networks
TensorFlow Lite

TensorFlow Lite
AlphaFold

AlphaFold

Explore Our Courses

Edge AI with TensorFlow Lite

 14 Hours

This instructor-led, live training in Monterrey (online or onsite) targets intermediate-level developers, data scientists, and AI practitioners seeking to leverage TensorFlow Lite for Edge AI applications.

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

  • Comprehend the fundamentals of TensorFlow Lite and its role in Edge AI.
  • Develop and optimize AI models using TensorFlow Lite.
  • Deploy TensorFlow Lite models on various edge devices.
  • Utilize tools and techniques for model conversion and optimization.
  • Implement practical Edge AI applications using TensorFlow Lite.
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Computer Vision with Google Colab and TensorFlow

 21 Hours

This live, instructor-led training in Monterrey (delivered online or onsite) is tailored for advanced professionals seeking to refine their knowledge of computer vision and utilize TensorFlow’s capabilities to build sophisticated vision models via Google Colab.

Upon completion, participants will be equipped to:

  • Construct and train convolutional neural networks (CNNs) with TensorFlow.
  • Utilize Google Colab to facilitate scalable and efficient cloud-based model development.
  • Apply image preprocessing techniques tailored for computer vision tasks.
  • Deploy computer vision models for practical, real-world use cases.
  • Employ transfer learning strategies to boost the performance of CNN models.
  • Visualize and analyze the outcomes of image classification models.
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Deep Learning with TensorFlow in Google Colab

 14 Hours

This instructor-led, live training in Monterrey (online or onsite) is designed for intermediate-level data scientists and developers aiming to understand and implement deep learning techniques using the Google Colab environment.

Upon completing this training, participants will be capable of:

  • Setting up and navigating Google Colab for deep learning initiatives.
  • Grasping the core concepts of neural networks.
  • Developing deep learning models using TensorFlow.
  • Training and assessing deep learning models.
  • Leveraging advanced TensorFlow features for deep learning.
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Deep Learning for NLU: Beyond NLP Models

 21 Hours

This instructor-led, live training in Monterrey (online or in-person) is designed for advanced professionals who want to specialize in cutting-edge deep learning techniques for NLU.

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

  • Understand the key differences between NLU and NLP models.
  • Apply advanced deep learning techniques to NLU tasks.
  • Explore deep architectures such as transformers and attention mechanisms.
  • Leverage future trends in NLU for building sophisticated AI systems.
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Explainability in Deep Learning: Demystifying Black-Box Models

 21 Hours

This instructor-led, live training in Monterrey (online or onsite) targets advanced-level professionals who wish to explore cutting-edge XAI techniques for deep learning models, focusing on the creation 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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Advanced Stable Diffusion: Deep Learning for Text-to-Image Generation

 21 Hours

This instructor-led live training in Monterrey (online or onsite) is aimed at intermediate to advanced data scientists, machine learning engineers, deep learning researchers, and computer vision experts who wish to expand their knowledge and skills in deep learning for text-to-image generation.

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

  • Understand advanced deep learning architectures and techniques for text-to-image generation.
  • Implement complex models and optimizations for high-quality image synthesis.
  • Optimize performance and scalability for large datasets and complex models.
  • Tune hyperparameters to improve model performance and generalization.
  • Integrate Stable Diffusion with other deep learning frameworks and tools.
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AI-Driven Drug Discovery and Development

 21 Hours

This instructor-led, live training in Monterrey (online or onsite) is designed for advanced professionals who want to use AI techniques to revolutionize drug discovery and development processes.

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

  • Understand the role of AI in drug discovery and development.
  • Apply machine learning techniques to predict molecular properties and interactions.
  • Use deep learning models for virtual screening and lead optimization.
  • Integrate AI-driven approaches into the clinical trial process.
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AlphaFold: AI-Driven Protein Structure Prediction and Interpretation

 7 Hours

This instructor-led, live training in Monterrey (online or in-person) is aimed at biologists who wish to understand how AlphaFold works and use AlphaFold models as guides in their experimental studies.

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

  • Understand the basic principles of AlphaFold.
  • Learn how AlphaFold works.
  • Learn how to interpret AlphaFold predictions and results.
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Introduction to Large Language Models (LLMs)

 14 Hours

This instructor-led, live training session in Monterrey (online or onsite) targets beginner to intermediate-level developers who wish to utilize Large Language Models for a range of natural language tasks.

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

  • Set up a development environment that includes a popular LLM.
  • Create a basic LLM and fine-tune it on a custom dataset.
  • Use LLMs for different natural language tasks such as text summarization, question answering, text generation, and more.
  • Debug and evaluate LLMs using tools such as TensorBoard, PyTorch Lightning, and Hugging Face Datasets.
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Introduction to Stable Diffusion for Text-to-Image Generation

 21 Hours

This instructor-led, live training (available online or onsite) is aimed at data scientists, machine learning engineers, and computer vision researchers who wish to leverage Stable Diffusion to generate high-quality images for a variety of use cases.

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

  • Understand the principles of Stable Diffusion and how it works for image generation.
  • Build and train Stable Diffusion models for image generation tasks.
  • Apply Stable Diffusion to various image generation scenarios, such as inpainting, outpainting, and image-to-image translation.
  • Optimize the performance and stability of Stable Diffusion models.
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Advanced Machine Learning with Python

 21 Hours

During this instructor-led, live training in Monterrey, participants will learn the most relevant and cutting-edge machine learning techniques in Python by building a series of demo applications that involve image, music, text, and financial data.

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

  • Implement machine learning algorithms and techniques for solving complex problems.
  • Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
  • Push Python algorithms to their maximum potential.
  • Use libraries and packages such as NumPy and Theano.
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Applied AI from Scratch in Python

 28 Hours
This hands-on training in Monterrey guides programmers in constructing AI models from scratch using Python. Participants will gain proficiency in supervised learning, neural networks, and unsupervised techniques through the use of scikit-learn and Apache Spark. The course emphasizes practical Jupyter notebook exercises designed to solve real-world problems.
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Deep Reinforcement Learning with Python

 21 Hours
This instructor-led training in Monterrey covers the theoretical foundations and practical implementation of Deep Reinforcement Learning using Python. Participants will build and train DRL agents with TensorFlow or PyTorch, applying key algorithms like DQN and PPO to solve complex real-world problems.
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Artificial Intelligence (AI) Overview

 7 Hours
A beginner-friendly course on Monterrey that covers the basics of AI, ranging from intelligent agents to machine learning. It prepares leaders and architects to evaluate new AI trends, implement effective solutions, and boost business agility through strategic automation.
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Artificial Intelligence (AI) in Automotive

 14 Hours
Discover how Machine Learning and Deep Learning are reshaping the automotive industry. This Monterrey module explores fundamental concepts, spanning from basic automation to autonomous decision-making, while covering neural networks and practical TensorFlow examples for real-world use cases.
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Artificial Neural Networks, Machine Learning, Deep Thinking

 21 Hours
This three-day program in Monterrey explores both the theoretical and practical aspects of Artificial Neural Networks, Machine Learning, and Deep Learning. Participants will investigate network architectures, learning mechanisms, and the underlying mathematical principles, progressing from fundamental perceptrons to sophisticated deep learning techniques.
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Pattern Recognition

 21 Hours

This instructor-led, live training in Monterrey (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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Fundamentals of Deep Learning

 8 Hours

This instructor-led, live training in Monterrey (online or on-site) is targeted at software developers, data analysts, and technical professionals who aim to use TensorFlow 2.x and Keras to build, train, and deploy deep learning models for computer vision, natural language processing, and multimodal applications.

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Fraud Detection with Python and TensorFlow

 14 Hours

This instructor-led live training in Monterrey (online or onsite) is designed for data scientists interested in using TensorFlow to analyze potential fraud data.

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

  • Develop a fraud detection model using Python and TensorFlow.
  • Build linear regression models to predict fraud.
  • Create an end-to-end AI application for analyzing fraud data.
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Matlab for Deep Learning

 14 Hours

In this instructor-led, live training, participants will learn how to use Matlab to design, build, and visualize a convolutional neural network for image recognition.

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

  • Build a deep learning model
  • Automate data labeling
  • Work with models from Caffe and TensorFlow-Keras
  • Train data using multiple GPUs, the cloud, or clusters

Audience

  • Developers
  • Engineers
  • Domain experts

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice
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Deep Learning with TensorFlow 2

 21 Hours

This instructor-led, live training in Monterrey (delivered online or on-site) targets developers and data scientists who intend to utilize TensorFlow 2.x for building predictors, classifiers, generative models, neural networks, and more.

By the end of this program, participants will be capable of:

  • Installing and configuring TensorFlow 2.x.
  • Understanding the benefits of TensorFlow 2.x over previous iterations.
  • Constructing deep learning models.
  • Implementing an advanced image classifier.
  • Deploying deep learning models to the cloud, mobile, and IoT devices.
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Understanding Deep Neural Networks

 35 Hours
This 35-hour course in Monterrey explores the fundamentals of deep neural networks, covering CNNs, RNNs, and generative models such as GANs. Participants gain hands-on 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 (5)

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

The training was organized and well-planned out, and I come out of it with systematized knowledge and a good look at topics we looked at

Magdalena - Samsung Electronics Polska Sp. z o.o.

Course - Deep Learning with TensorFlow 2

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

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

In-depth coverage of machine learning topics, particularly neural networks. Demystified a lot of the topic.

Sacha Nandlall

Course - Python for Advanced Machine Learning

Upcoming Courses

Computer Vision with Google Colab and TensorFlow

2026-11-26 09:30
21 hours
Monterrey - Oficinas en el Parque
109,890 MXN (Online)
139,890 MXN (Classroom)

Computer Vision with Google Colab and TensorFlow

2026-12-10 09:30
21 hours
Monterrey - El Milagro
109,890 MXN (Online)
139,890 MXN (Classroom)

Matlab for Deep Learning

2026-12-24 09:30
14 hours
Monterrey - Oficinas en el Parque
76,450 MXN (Online)
96,450 MXN (Classroom)

AI-Driven Drug Discovery and Development

2027-01-07 09:30
21 hours
Monterrey - El Milagro
109,890 MXN (Online)
139,890 MXN (Classroom)

Applied AI from Scratch in Python

2027-01-21 09:30
28 hours
Monterrey - Oficinas en el Parque
146,300 MXN (Online)
186,300 MXN (Classroom)

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These courses are also available in other countries

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