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Robotics Courses

Robotics courses can help you learn programming for robot control, sensor integration, and mechanical design principles. You can build skills in automation, system troubleshooting, and algorithm development for tasks like navigation and object recognition. Many courses introduce tools such as ROS (Robot Operating System), CAD software for design, and simulation platforms that allow you to test your robotic systems in virtual environments.


Popular Robotics Courses and Certifications


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    Coursera

    Robot Localization with Python and Particle Filters

    Skills you'll gain: Spatial Data Analysis, Robotics, Artificial Intelligence, Data Manipulation, Simulations, NumPy

    4.5
    Rating, 4.5 out of 5 stars
    ·
    25 reviews

    Advanced · Guided Project · Less Than 2 Hours

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    Coursera

    Basic Image Classification with TensorFlow

    Skills you'll gain: Model Evaluation, Keras (Neural Network Library), Tensorflow, Image Analysis, Artificial Neural Networks, Deep Learning, Computer Vision, Machine Learning, Classification Algorithms

    4.6
    Rating, 4.6 out of 5 stars
    ·
    847 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Object Localization with TensorFlow

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Data Synthesis, Convolutional Neural Networks, Image Analysis, Computer Vision, Artificial Neural Networks, Model Evaluation, Applied Machine Learning, Deep Learning, Machine Learning, Python Programming

    4.3
    Rating, 4.3 out of 5 stars
    ·
    117 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Medical Insurance Premium Prediction with Machine Learning

    Skills you'll gain: Data Visualization, Keras (Neural Network Library), Data Preprocessing, Artificial Neural Networks, Interactive Data Visualization, Predictive Modeling, Tensorflow, Applied Machine Learning, Feature Engineering, Data Science, Predictive Analytics, Data Manipulation, Machine Learning, Model Evaluation, Regression Analysis, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    26 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Hyperparameter Tuning with Keras Tuner

    Skills you'll gain: Keras (Neural Network Library), Artificial Neural Networks, Applied Machine Learning, Deep Learning, Python Programming, Performance Tuning, Machine Learning Algorithms, Machine Learning

    4.6
    Rating, 4.6 out of 5 stars
    ·
    70 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Create a Superhero Name Generator with TensorFlow

    Skills you'll gain: Tensorflow, Natural Language Processing, Python Programming, Machine Learning Methods, Recurrent Neural Networks (RNNs), Data Preprocessing, Artificial Neural Networks, Machine Learning, Deep Learning

    4.7
    Rating, 4.7 out of 5 stars
    ·
    38 reviews

    Intermediate · Guided Project · Less Than 2 Hours

What brings you to Coursera today?

  • C

    Coursera

    Visualizing Filters of a CNN using TensorFlow

    Skills you'll gain: Tensorflow, Convolutional Neural Networks, Image Analysis, Python Programming, Jupyter, Artificial Neural Networks, Deep Learning, Software Visualization, Machine Learning

    4.4
    Rating, 4.4 out of 5 stars
    ·
    84 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Diabetes Disease Detection with XG-Boost and Neural Networks

    Skills you'll gain: Artificial Neural Networks, Data Visualization, Exploratory Data Analysis, Data Presentation, Applied Machine Learning, Classification Algorithms, Machine Learning Methods, Predictive Modeling, Deep Learning, Classification And Regression Tree (CART), Data Analysis, Predictive Analytics, Machine Learning Algorithms, Model Evaluation, Machine Learning, Feature Engineering, Python Programming

    4.9
    Rating, 4.9 out of 5 stars
    ·
    10 reviews

    Beginner · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Deep Learning with PyTorch : Siamese Network

    Skills you'll gain: Embeddings, PyTorch (Machine Learning Library), Artificial Neural Networks, Image Analysis, Deep Learning, Applied Machine Learning, Convolutional Neural Networks, Computer Vision

    4.7
    Rating, 4.7 out of 5 stars
    ·
    49 reviews

    Advanced · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Deep-Dive into Tensorflow Activation Functions

    Skills you'll gain: Tensorflow, Keras (Neural Network Library), Artificial Neural Networks, Deep Learning, Machine Learning Methods, Python Programming

    4.7
    Rating, 4.7 out of 5 stars
    ·
    7 reviews

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    CNNs with TensorFlow: Basics of Machine Learning

    Skills you'll gain: Tensorflow, Convolutional Neural Networks, Keras (Neural Network Library), Matplotlib, Artificial Neural Networks, Image Analysis, Deep Learning, Applied Machine Learning, Python Programming, Model Evaluation, Adaptability, Problem Solving

    Intermediate · Guided Project · Less Than 2 Hours

  • C

    Coursera

    Machine Learning with ChatGPT: Image Classification Model

    Skills you'll gain: Model Evaluation, ChatGPT, Keras (Neural Network Library), Applied Machine Learning, Tensorflow, Data Preprocessing, Image Analysis, Machine Learning Methods, Data Import/Export, Machine Learning, Python Programming, Performance Tuning, Artificial Neural Networks

    4.4
    Rating, 4.4 out of 5 stars
    ·
    34 reviews

    Intermediate · Guided Project · Less Than 2 Hours

Searches related to robotics

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modern robotics, course 1: foundations of robot motion
12

In summary, here are 10 of our most popular robotics courses

  • Robot Localization with Python and Particle Filters: Coursera
  • Basic Image Classification with TensorFlow: Coursera
  • Object Localization with TensorFlow: Coursera
  • Medical Insurance Premium Prediction with Machine Learning: Coursera
  • Hyperparameter Tuning with Keras Tuner: Coursera
  • Create a Superhero Name Generator with TensorFlow: Coursera
  • Visualizing Filters of a CNN using TensorFlow: Coursera
  • Diabetes Disease Detection with XG-Boost and Neural Networks: Coursera
  • Deep Learning with PyTorch : Siamese Network: Coursera
  • Deep-Dive into Tensorflow Activation Functions: Coursera

Skills you can learn in Software Development

Programming Language (34)
Google (25)
Computer Program (21)
Software Testing (21)
Web (19)
Google Cloud Platform (18)
Application Programming Interfaces (17)
Data Structure (16)
Problem Solving (14)
Object-oriented Programming (13)
Kubernetes (10)
List & Label (10)

Frequently Asked Questions about Robotics

Robotics is a multidisciplinary field that combines engineering, computer science, and technology to design, build, and operate robots. These machines can perform tasks autonomously or semi-autonomously, making them invaluable in various industries. The importance of robotics lies in its ability to enhance productivity, improve safety, and reduce human error in tasks ranging from manufacturing to healthcare. As automation continues to evolve, understanding robotics becomes essential for adapting to technological advancements and improving operational efficiency.‎

A career in robotics can lead to various job opportunities across multiple sectors. Positions such as robotics engineer, automation technician, and research scientist are common. Additionally, roles in programming, system integration, and maintenance of robotic systems are in high demand. Industries such as manufacturing, healthcare, and logistics are increasingly relying on robotics, creating a wealth of opportunities for those skilled in this area.‎

To succeed in robotics, you need a blend of technical and soft skills. Key technical skills include programming languages like Python and C++, knowledge of control systems, and an understanding of mechanical design. Familiarity with sensors, actuators, and artificial intelligence is also beneficial. Soft skills such as problem-solving, teamwork, and effective communication are essential, as robotics often involves collaboration across various disciplines.‎

There are numerous online courses available for those interested in robotics. Some of the best options include the Modern Robotics: Mechanics, Planning, and Control Specialization and the Introduction to Robotics with Webots Specialization. These programs cover foundational concepts and practical applications, making them suitable for learners at different levels.‎

Yes. You can start learning robotics on Coursera for free in two ways:

  1. Preview the first module of many robotics courses at no cost. This includes video lessons, readings, graded assignments, and Coursera Coach (where available).
  2. Start a 7-day free trial for Specializations or Coursera Plus. This gives you full access to all course content across eligible programs within the timeframe of your trial.

If you want to keep learning, earn a certificate in robotics, or unlock full course access after the preview or trial, you can upgrade or apply for financial aid.‎

Learning robotics involves a structured approach. Start by gaining foundational knowledge through online courses or textbooks. Engage in hands-on projects to apply what you've learned, such as building simple robots or programming simulations. Joining online communities or forums can also provide support and resources. As you progress, consider specializing in areas like AI for robotics or automation systems to deepen your expertise.‎

Robotics courses typically cover a range of topics, including robot design, kinematics, dynamics, control systems, and programming. You may also explore artificial intelligence applications in robotics, sensor integration, and real-world case studies. These subjects provide a comprehensive understanding of how robots operate and interact with their environments.‎

For training and upskilling employees in robotics, courses like the Fundamentals of Robotics & Industrial Automation and the Collaborative Robotics in Industry Specialization are excellent choices. These programs focus on practical applications and industry-relevant skills, making them ideal for workforce development.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

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