Robots in the work place can perform hazardous or even 'impossible' tasks; e.g., toxic waste clean-up, desert and space exploration, and more. AI researchers are also interested in the intelligent processing involved in moving about and manipulating objects in the real world.
Industrial robots are primarily known from the automotive industry's production lines. The goal of this class is to present robots instead as multifunctional and flexible interfaces between the digital and the physical world that can be used for anything from innovative, large-scale fabrication to immersive virtual reality (VR) simulators. This extension beyond the robots' initial scope is enabled by new software developments that facilitate a seamless workflow from design to machine through Dynamo software and KUKA prc. Utilizing parametric design tools lets us use robots for mass customization and small lot sizes, rather than mass fabrication. The class will provide an overview on how to utilize industrial robots through Dynamo and Fusion 360 software, and present realized projects by both small to medium-size enterprises as well as international corporations.
Whether you you need guidance on learning to code or you are a seasoned machine learning practitioner, Google is here to help. The search engine giant has come up with a new course -- 'Learn with Google AI' -- that acts as a practical introduction to machine learning to all users for free. Machine learning (ML) is a branch of artificial intelligence (AI) and pertains to a computer's ability to execute certain tasks on its own without being programmed by a human being. Some examples of ML include self-driving cars, speech recognition, language translators, etc. Google's new machine learning crash course is designed to provide a fast-paced self-study guide for aspiring machine learning practitioners using high-level TensorFlow (TF) APIs. It features a series of video lessons with lectures from ML experts, real-world case studies and hands-on practice exercises to help users learning about key ML algorithms and frameworks.
After taking these robotics classes you can also get a robotics certification online. However, you can get robotics degree online from a lot of places other than Udemy like coursera, EDx, Futurelearn and so on. Open career opportunities and have fun to learn electronics focused on building robots/automation! Open doors to careers and hobbies and have fun while learning digital electronics! Description: An autonomous light-seeking an obstacle avoiding robot for Arduino Makers that want to learn the hard way.
Welcome to Tech Explorations Arduino Step by Step Getting Serious, where you will extend your knowledge of Arduino components and techniques and build up new skills in the largest, and the most comprehensive course on the Web! Arduino is the world's favorite electronics learning and prototyping platform. Millions of people from around the world use it to learn electronics, engineering, programming, and create amazing things, from greenhouse controllers to tree climbing robots remotely controlled lawnmowers. It is a gateway to a career in engineering, a tool for Science, Technology, Engineering, and Mathematics education, a vehicle for artistic and creative expression. The course is split into 40 sections and over 250 lectures spanning more than 30 hours of video content.
Autonomous driving is not one single technology but rather a complex system integrating many technologies, which means that teaching autonomous driving is a challenging task. Indeed, most existing autonomous driving classes focus on one of the technologies involved. This not only fails to provide a comprehensive coverage, but also sets a high entry barrier for students with different technology backgrounds. In this paper, we present a modular, integrated approach to teaching autonomous driving. Specifically, we organize the technologies used in autonomous driving into modules. This is described in the textbook we have developed as well as a series of multimedia online lectures designed to provide technical overview for each module. Then, once the students have understood these modules, the experimental platforms for integration we have developed allow the students to fully understand how the modules interact with each other. To verify this teaching approach, we present three case studies: an introductory class on autonomous driving for students with only a basic technology background; a new session in an existing embedded systems class to demonstrate how embedded system technologies can be applied to autonomous driving; and an industry professional training session to quickly bring up experienced engineers to work in autonomous driving. The results show that students can maintain a high interest level and make great progress by starting with familiar concepts before moving onto other modules.
Some of the niche subjects that will find place in the new syllabus include robotics, artificial intelligence, and automation. Students enrolling for postgraduate programmes offered by Mahatma Gandhi University (MGU) from the 2018-19 academic year have something to cheer about. The varsity had carried out syllabus and curriculum revision for its undergraduate courses in the academic year 2017-18. The syllabus revision will also take into account the research possibilities that students could undertake after postgraduation," he said. The revision of syllabus for postgraduate programmes was previously carried out in 2012.
Machine Learning is one of the most popular approaches in Artificial Intelligence. Over the past decade, Machine Learning has become one of the integral parts of our life. It is implemented in a task as simple as recognizing human handwriting or as complex as self-driving cars. It is also expected that in a couple of decades, the more mechanical repetitive task will be over. With the increasing amounts of data becoming available there is a good reason to believe that Machine Learning will become even more prevalent as a necessary element for technological progress. There are many key industries where ML is making a huge impact: Financial services, Delivery, Marketing and Sales, Health Care to name a few. However, here we will discuss the implementation and usage of Machine Learning in trading.
Emerging anxieties pertaining to the rapid advancement and sophistication of artificial intelligence appear to be on a collision course with historic models of human exceptionality and individuality. Yet it is not just objective, technical sophistication in the development of AI that seems to cause this angst. It is also the linguistic treatment of machine "intelligence." But what is really at stake? Are we truly concerned that we will be surpassed in our capacities as human beings?
This class is an introduction to the practice of deep learning through the applied theme of building a self-driving car. It is open to beginners and is designed for those who are new to machine learning, but it can also benefit advanced researchers in the field looking for a practical overview of deep learning methods and their application.