Get in Touch
 Duration 21 hours

Course Outline

Introduction to Autonomous Systems

  • Overview of autonomous systems and their applications
  • Key components: sensors, actuators, and control systems
  • Challenges in autonomous system development

AI Techniques for Autonomous Decision-Making

  • Machine learning models for decision-making
  • Deep learning approaches for perception and control
  • Real-time processing and inference for autonomous systems

Autonomous Navigation and Control

  • Path planning and obstacle avoidance
  • Control algorithms for stable and responsive navigation
  • Integration of AI with control systems for autonomous vehicles

Safety and Reliability in Autonomous Systems

  • Safety protocols and fail-safe mechanisms
  • Testing and validation of autonomous systems
  • Compliance with industry standards and regulations

Case Studies and Practical Applications

  • Self-driving cars: AI algorithms and real-world implementations
  • Drones: Autonomous flight control and navigation
  • Industrial robots: AI-driven automation in manufacturing

Future Trends in AI-Powered Autonomous Systems

  • Advancements in AI and their impact on autonomy
  • Emerging technologies in autonomous system development
  • Exploring future directions and opportunities in the field

Summary and Next Steps

Requirements

  • Experience in robotics or AI development
  • Understanding of machine learning and real-time systems
  • Familiarity with control systems and safety protocols

Audience

  • Robotics engineers
  • AI developers
  • Automation specialists

Custom Corporate Training

Training solutions designed exclusively for businesses.

  • Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
  • Flexible Schedule: Dates and times adapted to your team's agenda.
  • Format: Online (live), In-company (at your offices), or Hybrid.
Investment

Price per private group, online live training, starting from 3900 € + VAT*

Contact us for an exact quote and to hear our latest promotions

(*The final price may vary depending on the technical specialization of the course, the level of customization, the method of delivery and the number of learners)

Need help picking the right course?
info@nobleprog.pt or +351 30 050 9666

Testimonials (2)

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

Provisional Upcoming Courses (Contact Us For More Information)

AI-Powered Autonomous Systems

2026-10-14 09:30
21 hours
Hotel Tivoli Coimbra

AI-Powered Autonomous Systems

2026-10-28 09:30
21 hours
Évora Hotel

AI-Powered Autonomous Systems

2026-11-11 09:30
21 hours
Hotel Faro & Beach Club

AI-Powered Autonomous Systems

2026-11-25 09:30
21 hours
Holiday Inn Porto - Gaia

AI-Powered Autonomous Systems

2026-12-09 09:30
21 hours
Hotel Central Parque

AI-Powered Autonomous Systems

2026-12-23 09:30
21 hours
Four Points by Sheraton Matosinhos

Related Courses

Artificial Intelligence (AI) in Automotive

 14 Hours
Discover how Machine Learning and Deep Learning are reshaping the automotive industry. This Portugal 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.
Read more...

Artificial Intelligence (AI) Overview

 7 Hours
An introductory course on Portugal 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.
Read more...

Artificial Neural Networks, Machine Learning, Deep Thinking

 21 Hours
This three-day program in Portugal 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.
Read more...

Applied AI from Scratch in Python

 28 Hours
This hands-on training in Portugal 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.
Read more...

Creating Custom Chatbots with Google AutoML

 14 Hours

This instructor-led, live training in Portugal (online or onsite) is designed for participants with varying levels of expertise who want to use Google's AutoML platform to build custom chatbots for various applications.

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

  • Understand the fundamentals of chatbot development.
  • Navigate the Google Cloud Platform and access AutoML.
  • Prepare data for training chatbot models.
  • Train and evaluate custom chatbot models using AutoML.
  • Deploy and integrate chatbots into various platforms and channels.
  • Monitor and optimise chatbot performance over time.
Read more...

Pattern Recognition

 21 Hours

This instructor-led, live training in Portugal (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.
Read more...

Deep Reinforcement Learning with Python

 21 Hours
This live, instructor-led training in Portugal 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.
Read more...

Edge AI with TensorFlow Lite

 14 Hours

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

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

  • Grasp 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.
Read more...

Kubeflow Essentials: Build, Train & Serve with Kubernetes

 14 Hours
This practical training in Portugal provides you with the proficiency necessary to build, train, and serve machine learning models on Kubernetes using Kubeflow. You will master navigating the ecosystem, designing scalable pipelines, and overseeing production-ready workloads while adhering to industry best practices.
Read more...

Kubeflow Fundamentals

 28 Hours

This instructor-led, live training in Portugal (online or onsite) is designed for developers and data scientists aiming to build, deploy, and manage machine learning workflows on Kubernetes.

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

  • Install and configure Kubeflow in on-premise and cloud settings.
  • Build, deploy, and manage ML workflows using Docker containers and Kubernetes.
  • Run entire machine learning pipelines across diverse architectures and cloud environments.
  • Use Kubeflow to create and manage Jupyter notebooks.
  • Develop ML training, hyperparameter tuning, and serving workloads across multiple platforms.
Read more...

Introduction to the Use of Neural Networks

 7 Hours
This introductory module outlines the core concepts of neural networks within Portugal, 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.
Read more...

Advanced Analytics with RapidMiner

 14 Hours

This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level data analysts who wish to learn how to use RapidMiner to estimate and project values and utilise analytical tools for time series forecasting.

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

  • Apply the CRISP-DM methodology, select suitable machine learning algorithms, and improve model construction and performance.
  • Utilise RapidMiner to estimate and project values, employing analytical tools for time series forecasting.
Read more...

Understanding Deep Neural Networks

 35 Hours
This 35-hour course on Portugal 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.
Read more...

Explainability in Deep Learning: Demystifying Black-Box Models

 21 Hours

This instructor-led, live training in Portugal (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.
Read more...

Related Categories

Machine Learning
Machine Learning