When will I receive my Course Certificate?

If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.

Why can’t I audit this course?

This course is currently available only to learners who have paid or received financial aid, when available.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Artificial Intelligence for Robotics

Développez vos compétences avec Coursera Plus pour 239 $/an (habituellement 399 $). Économisez maintenant.

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

Nous sommes actuellement en train de le traduire dans plus de langues.

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 : Convolutional Neural Networks
Catégorie : Computer Vision
Catégorie : Systems Engineering
Catégorie : Reinforcement Learning
Catégorie : Robotics
Catégorie : Natural Language Processing
Catégorie : Artificial Intelligence
Catégorie : Artificial Neural Networks
Catégorie : Automation
Catégorie : Machine Learning
Catégorie : Algorithms
Catégorie : Image Analysis

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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logos de Petrobras, TATA, Danone, Capgemini, P&G et L'Oreal

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 vidéos Total 2 minutes

Course Overview 1 minute
The Foundation of Robotics and Artificial Intelligence - Overview Video 1 minute

9 lectures Total 90 minutes

Introduction 10 minutes
Are Recent Developments in AI Anything New 10 minutes
The Basics of Robotics 10 minutes
When Do You Need AI for Your Robot 5 minutes
Introducing the Robot and Our Development Environment 10 minutes
Software Components (ROS, Python, and Linux) 10 minutes
Using Control Loops 10 minutes
Types of Control Loops 5 minutes
Running a Control Loop 20 minutes

1 devoir Total 10 minutes

Exploring the Foundations of Robotics and AI 10 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 vidéo Total 1 minute

Recognizing Objects Using Neural Networks and Supervised Learning - Overview Video 1 minute

5 lectures Total 70 minutes

Introduction 20 minutes
Artificial Neurons 10 minutes
Using YOLOv8 An Object Recognition Model 10 minutes
Understanding How to Train Our Toy Detector 20 minutes
Building the Toy Detector 10 minutes

1 devoir Total 10 minutes

Fundamentals of Object Recognition with Neural Networks 10 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 vidéo Total 1 minute

Picking Up and Putting Away Toys Using Reinforcement Learning and Genetic Algorithms - Overview Video 1 minute

8 lectures Total 125 minutes

Introduction 10 minutes
Designing the Software 10 minutes
Setting Up the Solution 5 minutes
How Do We Pick Actions 5 minutes
Creating the Interface to the Arm 30 minutes
Introducing Q-Learning for Grasping Objects 30 minutes
Introducing GAs 5 minutes
Building a GA Process 30 minutes

1 devoir Total 10 minutes

Learning from Feedback and Evolution in Robotics 10 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 vidéo Total 1 minute

Teaching a Robot to Listen - Overview Video 1 minute

7 lectures Total 85 minutes

Introduction 10 minutes
Listening for the Wake Word 10 minutes
Clarifying the Intent 10 minutes
Adding Skills 5 minutes
Cleaning up the toys 20 minutes
Telling Jokes 20 minutes
Receiving Jokes 10 minutes

1 devoir Total 10 minutes

Robot Listening and Speech Recognition Fundamentals 10 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 vidéo Total 1 minute

Teaching the Robot to Navigate and Avoid Stairs - Overview Video 1 minute

7 lectures Total 60 minutes

Introduction 10 minutes
Understanding the SLAM Methodology 10 minutes
Exploring Alternative Navigation Techniques 10 minutes
Implementing Neural Networks 5 minutes
Processing the image 5 minutes
Training the Neural Network for Navigation 10 minutes
CNN Robot Control Implementation 10 minutes

1 devoir Total 10 minutes

Understanding Robot Navigation and Sensor Use 10 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 vidéo Total 1 minute

Putting Things Away - Overview Video 1 minute

8 lectures Total 105 minutes

Introduction 10 minutes
What Do We Mean by Pruning? 5 minutes
Creating Self-Classifying Decision Trees 30 minutes
Understanding Entropy 20 minutes
Random Forests 10 minutes
Developing a Map Based on Our Knowledge 10 minutes
Introducing the A* Algorithm 10 minutes
Introducing the D (D-star or Dynamic A) Algorithm 10 minutes

1 devoir Total 10 minutes

Navigating Algorithms and Data Structures 10 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 vidéo Total 1 minute

Giving the Robot an Artificial Personality - Overview Video 1 minute

10 lectures Total 80 minutes

Introduction 10 minutes
A Brief Introduction to the (Obsolete) Turing Test, Chatbots, and Generative AI 5 minutes
The Art and Science of Simulation 10 minutes
An Emotion State Machine 5 minutes
Playing the Emotion Game 5 minutes
Creating a Model of Human Behavior 5 minutes
Constructing a Personality 10 minutes
Adding Context 10 minutes
Developing the Robot Emotion Engine 10 minutes
Creating Human Information Storage 10 minutes

1 devoir Total 10 minutes

Robot Emotion and Artificial Personality 10 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 vidéo Total 1 minute

Conclusions and Reflections - Overview Video 1 minute

6 lectures Total 40 minutes

Introduction 5 minutes
Careers in Robotics 5 minutes
Exploring the Current State of AI 5 minutes
Is AI Phobia Reasonable? 5 minutes
Comparing the Needs of Humans and AI 10 minutes
Understanding Risk in AI 10 minutes

1 devoir Total 10 minutes

Reflections on Technology and Human Interaction 10 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

1 566 Cours 441 543 apprenants

Offert par

Packt

En savoir plus sur Software Development

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

Felipe M.

Étudiant(e) depuis 2018

’Pouvoir suivre des cours à mon rythme à été une expérience extraordinaire. Je peux apprendre chaque fois que mon emploi du temps me le permet et en fonction de mon humeur.’

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