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Artificial Intelligence for Robotics

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Artificial Intelligence for Robotics

Instructeur : Packt - Course Instructors

Inclus avec

11 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

2 semaines à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

11 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

2 semaines à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Apply AI and ML techniques to enhance robot perception and decision-making
Implement object recognition and navigation strategies using neural networks and algorithms
Integrate natural language processing to enable voice and personality features in robots

Compétences que vous acquerrez

Catégorie : Reinforcement Learning
Catégorie : Convolutional Neural Networks
Catégorie : Image Analysis
Catégorie : Artificial Intelligence and Machine Learning (AI/ML)
Catégorie : Computer Vision
Catégorie : Model Training
Catégorie : Artificial Neural Networks
Catégorie : Natural Language Processing
Catégorie : AI Integrations
Catégorie : Robotics
Catégorie : Algorithms
Catégorie : Automation
Catégorie : Artificial Intelligence
Catégorie : Machine Learning

Outils que vous découvrirez

Catégorie : Python Programming

Détails à connaître

Certificat partageable

Ajouter à votre profil LinkedIn

Récemment mis à jour !

mars 2026

Évaluations

11 devoirs

Enseigné en Anglais

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Il y a 11 modules dans ce cours

This course dives deep into the integration of artificial intelligence and machine learning within robotics. You will learn to build intelligent robots capable of performing real-world tasks using ROS 2, Python, OpenCV, and advanced AI/ML techniques. By focusing on neural networks, computer vision, and natural language processing, this course will help you enhance robot functionality for complex tasks.

Throughout the course, you will improve your skills in applying AI and ML techniques, implementing object recognition systems, and navigating robots. The content is designed for hands-on learning, allowing you to work on practical problems while developing a real-world understanding of intelligent robotics systems. What sets this course apart is its unique combination of theory and practical application. The course integrates state-of-the-art AI/ML concepts into the design and development of robotics projects, equipping you with the tools to work on intelligent robot systems. The hands-on approach makes the theoretical knowledge more accessible and applicable in real-life scenarios. This course is perfect for robotics engineers, AI/ML enthusiasts, and students with a background in Python and electronics. If you're looking to create smarter, more capable robots, this course will help you take your skills to the next level.

In this section, we explore integrating AI into robotics, focusing on decision-making, learning, and autonomy. Key concepts include neural networks, reinforcement learning, and autonomous behavior design.

Inclus

2 vidéos9 lectures1 devoir

2 vidéosTotal 2 minutes

Course Overview1 minute
The Foundation of Robotics and Artificial Intelligence - Overview Video1 minute

9 lecturesTotal 90 minutes

Introduction10 minutes
Are Recent Developments in AI Anything New10 minutes
The Basics of Robotics10 minutes
When Do You Need AI for Your Robot5 minutes
Introducing the Robot and Our Development Environment10 minutes
Software Components (ROS, Python, and Linux)10 minutes
Using Control Loops10 minutes
Types of Control Loops5 minutes
Running a Control Loop20 minutes

1 devoirTotal 10 minutes

Exploring the Foundations of Robotics and AI10 minutes

In this section, we explore robot anatomy, subsumption architecture, and ROS 2 setup to enable practical robotic system development through structured hardware and software configuration.

Inclus

1 vidéo5 lectures1 devoir

In this section, we explore systems engineering principles for robot design, focusing on use cases, storyboards, and hardware/software requirements to guide practical robotic task development.

Inclus

1 vidéo5 lectures1 devoir

In this section, we explore using convolutional neural networks (CNNs) and YOLOv8 for object recognition, focusing on image processing, supervised learning, and real-world applications in robotics and AI.

Inclus

1 vidéo5 lectures1 devoir

1 vidéoTotal 1 minute

Recognizing Objects Using Neural Networks and Supervised Learning - Overview Video1 minute

5 lecturesTotal 70 minutes

Introduction20 minutes
Artificial Neurons10 minutes
Using YOLOv8 An Object Recognition Model10 minutes
Understanding How to Train Our Toy Detector20 minutes
Building the Toy Detector10 minutes

1 devoirTotal 10 minutes

Fundamentals of Object Recognition with Neural Networks10 minutes

In this section, we explore training robots using reinforcement learning and genetic algorithms. Key concepts include Q-learning for grasping and GA-based path planning for autonomous manipulation.

Inclus

1 vidéo8 lectures1 devoir

1 vidéoTotal 1 minute

Picking Up and Putting Away Toys Using Reinforcement Learning and Genetic Algorithms - Overview Video1 minute

8 lecturesTotal 125 minutes

Introduction10 minutes
Designing the Software10 minutes
Setting Up the Solution5 minutes
How Do We Pick Actions5 minutes
Creating the Interface to the Arm30 minutes
Introducing Q-Learning for Grasping Objects30 minutes
Introducing GAs5 minutes
Building a GA Process30 minutes

1 devoirTotal 10 minutes

Learning from Feedback and Evolution in Robotics10 minutes

In this section, we explore robot speech recognition using NLP, STT, and TTS, and implement command processing with Mycroft to enhance natural language understanding and response generation.

Inclus

1 vidéo7 lectures1 devoir

1 vidéoTotal 1 minute

Teaching a Robot to Listen - Overview Video1 minute

7 lecturesTotal 85 minutes

Introduction10 minutes
Listening for the Wake Word10 minutes
Clarifying the Intent10 minutes
Adding Skills5 minutes
Cleaning up the toys20 minutes
Telling Jokes20 minutes
Receiving Jokes10 minutes

1 devoirTotal 10 minutes

Robot Listening and Speech Recognition Fundamentals10 minutes

In this section, we explore robot navigation strategies without SLAM, focusing on AI-driven obstacle avoidance and sensor-based movement for efficient task execution.

Inclus

1 vidéo7 lectures1 devoir

1 vidéoTotal 1 minute

Teaching the Robot to Navigate and Avoid Stairs - Overview Video1 minute

7 lecturesTotal 60 minutes

Introduction10 minutes
Understanding the SLAM Methodology10 minutes
Exploring Alternative Navigation Techniques10 minutes
Implementing Neural Networks5 minutes
Processing the image5 minutes
Training the Neural Network for Navigation10 minutes
CNN Robot Control Implementation10 minutes

1 devoirTotal 10 minutes

Understanding Robot Navigation and Sensor Use10 minutes

In this section, we explore AI decision-making tools like decision trees, path planning, and expert systems for robotics.

Inclus

1 vidéo8 lectures1 devoir

1 vidéoTotal 1 minute

Putting Things Away - Overview Video1 minute

8 lecturesTotal 105 minutes

Introduction10 minutes
What Do We Mean by Pruning?5 minutes
Creating Self-Classifying Decision Trees30 minutes
Understanding Entropy20 minutes
Random Forests10 minutes
Developing a Map Based on Our Knowledge10 minutes
Introducing the A* Algorithm10 minutes
Introducing the D (D-star or Dynamic A) Algorithm10 minutes

1 devoirTotal 10 minutes

Navigating Algorithms and Data Structures10 minutes

In this section, we explore simulating artificial personality in robots using finite state machines and AI. Key concepts include behavior modeling and emotion simulation for practical robotic applications.

Inclus

1 vidéo10 lectures1 devoir

1 vidéoTotal 1 minute

Giving the Robot an Artificial Personality - Overview Video1 minute

10 lecturesTotal 80 minutes

Introduction10 minutes
A Brief Introduction to the (Obsolete) Turing Test, Chatbots, and Generative AI5 minutes
The Art and Science of Simulation10 minutes
An Emotion State Machine5 minutes
Playing the Emotion Game5 minutes
Creating a Model of Human Behavior5 minutes
Constructing a Personality10 minutes
Adding Context10 minutes
Developing the Robot Emotion Engine10 minutes
Creating Human Information Storage10 minutes

1 devoirTotal 10 minutes

Robot Emotion and Artificial Personality10 minutes

In this section, we examine when to stop in AI development, explore robotics career paths, and assess AI risks to support informed decision-making in real-world applications.

Inclus

1 vidéo6 lectures1 devoir

1 vidéoTotal 1 minute

Conclusions and Reflections - Overview Video1 minute

6 lecturesTotal 40 minutes

Introduction5 minutes
Careers in Robotics5 minutes
Exploring the Current State of AI5 minutes
Is AI Phobia Reasonable?5 minutes
Comparing the Needs of Humans and AI10 minutes
Understanding Risk in AI10 minutes

1 devoirTotal 10 minutes

Reflections on Technology and Human Interaction10 minutes

In this section, we will explore the foundational elements of robot communication and system design.

Inclus

3 lectures1 devoir

Instructeur

Packt - Course Instructors

Packt

1 763 Cours506 652 apprenants

Offert par

Packt

En savoir plus sur Software Development

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Étudiant(e) depuis 2018

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Jennifer J.

Étudiant(e) depuis 2020

’J'ai directement appliqué les concepts et les compétences que j'ai appris de mes cours à un nouveau projet passionnant au travail.’

Larry W.

Étudiant(e) depuis 2021

’Lorsque j'ai besoin de cours sur des sujets que mon université ne propose pas, Coursera est l'un des meilleurs endroits où se rendre.’

Chaitanya A.

’Apprendre, ce n'est pas seulement s'améliorer dans son travail : c'est bien plus que cela. Coursera me permet d'apprendre sans limites.’

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Foire Aux Questions

Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.

If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.

Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.

Plus de questions

Visitez le Centre d'Aide pour les Étudiants

Aide financière disponible,

Artificial Intelligence for Robotics

Ce cours n'est pas disponible en Français (France)

Artificial Intelligence for Robotics

Ce que vous apprendrez

Compétences que vous acquerrez

Outils que vous découvrirez

Détails à connaître

Découvrez comment les employés des entreprises prestigieuses maîtrisent des compétences recherchées

Il y a 11 modules dans ce cours

The Foundation of Robotics and Artificial Intelligence

Inclus

Setting Up Your Robot

Inclus

Conceptualizing the Practical Robot Design Process

Inclus

Recognizing Objects Using Neural Networks and Supervised Learning

Inclus

Picking Up and Putting Away Toys Using Reinforcement Learning and Genetic Algorithms

Inclus

Teaching a Robot to Listen

Inclus

Teaching the Robot to Navigate and Avoid Stairs

Inclus

Putting Things Away

Inclus

Giving the Robot an Artificial Personality

Inclus

Conclusions and Reflections

Inclus

Appendix

Inclus

Instructeur

Offert par

En savoir plus sur Software Development

AI for Autonomous Vehicles and Robotics

Robotics in High-Tech Manufacturing

Robotics Engineering & Applications

Master AI Tools & Robotics: Analyze, Automate, Innovate

Pour quelles raisons les étudiants sur Coursera nous choisissent-ils pour leur carrière ?

Felipe M.

Jennifer J.

Larry W.

Chaitanya A.

Ouvrez de nouvelles portes avec Coursera Plus

Faites progresser votre carrière avec un diplôme en ligne

Rejoignez plus de 3 400 entreprises mondiales qui ont choisi Coursera pour les affaires

Foire Aux Questions

Can I preview a course before enrolling?

When will I have access to the lectures and assignments?

What will I get when I enroll?

Plus de questions