Nanodegree-Programm

Entwickle Robotik-Software

Programmiere ROS, Kinematik, Kontrolle, Computer Vision, KI und Reinforcement Learning

Fertigung, Landwirtschaft, Gesundheits-, Bau- oder Transportwesen: Roboter werden unsere Welt sicherer und produktiver gestalten. Durch die Spezialisierung auf die Software-Entwicklung für Robotik lernst du innerhalb dieses Online-Kurses, Roboter zu programmieren. Das erlangte Wissen wendest du in praxisnahen Projekten auf unterschiedliche KI-Herausforderungen an.

  • Kursdauer
    2 x 4 Monate

    Lerne 15 Std/Woche, um in 8 Monaten abzuschließen

  • Classroom öffnet
    28. August 2018
  • Voraussetzungen
    Analysis, Statistik & Python

    Detaillierte Voraussetzungen ansehen

  • Sprache
    Englisch

    Lernmaterialien und Kurskommunikation in englischer Sprache

In Zusammenarbeit mit
  • Nvidia
  • Electric Movement
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Was spricht für ein Lernprogramm zur Roboterprogrammierung?

Die Robotik transformiert derzeit etliche Industrien. Von Fertigung und Gesundheitswesen über Landwirtschaft bis hin zu Bau- und Transportwesen trägt sie zur Produktivität und Sicherheit bei. Durch solche Automatisierungstechnik gewinnt der Mensch an Freiheit, um anspruchsvollere, also kreative oder intellektuelle Ziele zu verfolgen. Die Robotik eröffnet unglaubliche Möglichkeiten, erfordert allerdings auch besondere Qualifikationen.

In diesem Programm erlangst du das Wissen und die praktischen Fähigkeiten, um robotische Softwaresysteme zu entwickeln und Grundsätze künstlicher Intelligenz auf Robotik anzuwenden. So lernst du etwa Robot Operating System (ROS), Kinematik, Kontrolle, simultane Lokalisierung und Mapping (SLAM) kennen. Durch unsere Partnerschaft mit NVIDIAs Deep Learning Institut können wir dir außerdem die Innovationstechnik des Deep Reinforcement Learning vermitteln.


Was spricht für ein Lernprogramm zur Roboterprogrammierung?

€127 Mrd.
Ausgaben für Robotik und damit verbundene Dienstleistungen bis 2019

Erstklassige Partner, erstklassiger Kursplan

Erstklassige Partner, erstklassiger Kursplan

Um die Expertise so umfassend wie möglich und eine bahnbrechende Lernerfahrung aufzustellen, greifen wir auf die jahrelange praktische Erfahrung von NVIDIA und Electric Movement zurück. Die beiden Tech-Größen haben den Lehrplan mitkonzipiert, Mitarbeiter stehen euch im Programm als Ansprechpartner und zur Entwicklung eurer Projekte zur Verfügung.

Karriere in der Robotik

Karriere in der Robotik

Viele Nanodegree-Programme legen Grundlagen oder bilden eine partikuläre Fähigkeit aus. AbsoventInnen dieses Programmes aber bezeichnen wir als "career-ready". Ein Portfolio ihrer erstellten Projekte bildet die perfekte Bewerbungsgrundlage, sie sind vollständig in der Lage, andere Robotik-Teams zu bereichern und eigenständig innovative Software-Lösungen zu entwickeln. Damit stellen sie eine Gruppe dar, die der Arbeitsmarkt bereits heftig nachfragt. Und der Bedarf steigt weiter…

Was du lernst

Kursplan herunterladen
Abschnitt 1

Robotik-Grundlagen, ROS, Wahrnehmung und Steuerung

Du betrittst die Robotik-Welt mit praktischen Übungen und über ROS-Frameworks (Robotic Operating System). Dabei verbindest du moderne Machine Learning-Prozesse mit klassischer Mechanik, um die Schlüsselfunktionen Wahrnehmung und Steuerung zu realisieren.

Betritt die Robotik-Welt über ROS-Frameworks (Robotic Operating System) und verbinde in praktischen Übungen moderne Machine Learning-Prozesse mit klassischer Mechanik.

Details anzeigen

Dauer: 4 Monate

Abschnitt 2

Lokalisierung, Mapping und Navigation

In zweiten Abschnitt arbeiten wir eng mit NVIDIA's Deep Learning Institut zusammen. Du lernst, probabilistische Algorithmen und Reinforcement Learning auf Herausforderungen der Lokalisierung, des Mappings und der Navigation anzuwenden.

Du lernst von und mit NVIDIA, probabilistische Algorithmen und Reinforcement Learning auf Herausforderungen in Lokalisierung, Mapping und Navigation anzuwenden.

Details anzeigen

Dauer: 4 Monate

“NVIDIA und Udacity eint eine Vision: Wir wollen eine Ausbildung bieten, die praktisch angelegt ist. Mit Lehrplänen, die Lernenden alles abverlangt, damit sie Kurs und Zertifikat in der Karriere anschließend wirklich weiterbringt. Aus dieser gemeinsamen Vision sind mehrere KI- und Deep Learning-Programme entstanden, die den Vorsprung unserer Entwickler, Forscher und Akademiker auf vielen Gebieten weiter ausbauen.”

— GREG ESTES, VICE PRESIDENT OF DEVELOPER PROGRAMS, NVIDIA

Von und mit den Besten lernen

Sebastian Thrun
Sebastian Thrun

Udacity, Präsident

Wissenschaftler. Lehrer. Erfinder. Unternehmer. Sebastian ist vieles, u.a. Tutor dieses Programms. Er leitete das Projekt Google X zum autonomen Auto und gründete Udacity mit der Vision, digitale Bildung weltweit für so viele Lernende wie möglich erschwinglich zu machen.

Dana Sheahen
Dana Sheahen

UDACITY, KURSLEITERIN

Dana ist Elektroingenieurin mit Georgia Tech Informatik M.A. und einigen Jahren Erfahrung in der Entwicklung von Embedded Systems für Motorola. Dabei erhielt sie u.a. ein Patent für ein integriertes Betriebssystem.

Ryan Keenan
Ryan Keenan

UDACITY, KURSLEITER

Ryan hat einen PhD in Astrophysik, lehrt und lernt leidenschaftlich und ist außerdem Tutor in den Self-Driving und Flying Car Nanodegree-Programmen. Wenn er nicht online ist, sucht ihn in den Bergen oder beim Surfen.

Anthony Navarro
Anthony Navarro

UDACITY, PRODUKTLEITER

Nach seiner Zeit in der US Army hat Anthony einen Computertechnik M.A. an der Colorado State gemacht und bei Lockheed Martin als Software-Entwickler für autonome Systeme gearbeitet. Ihr findet Anthony auch im Self-Driving Car-Programm.

Julia Chernushevich
Julia Chernushevich

UDACITY, INSTRUCTOR

Julia is an instructor of Mechatronics Engineering at the University of Waterloo. Her previous work experiences include designing electric vehicles for underground mines and leading a prestigious STEM enrichment program for gifted high-school students.

Karim Chamaa
Karim Chamaa

UDACITY, INSTRUCTOR

Karim started his early career as a Mechanical Engineer. He earned his M.S. in Mechatronics and Robotics Engineering from NYU. His specialties include Kinematics, Control, and Electronics.

NVIDIA
NVIDIA

TEAM

NVIDIAs Erfolg fußt auf Geist und bahnbrechender Forschung. NVIDIAs GPU Deep Learning hat eine neue Ära der Datenverarbeitung entfacht, in der der Prozessor als Gehirn von Computern, Robotern und selbstfahrenden Autos die Welt wahrnimmt und versteht.

ELECTRIC MOVEMENT
ELECTRIC MOVEMENT

TEAM

EM entwickelt Robotiksysteme, bringt also unschätzbare Einblicke, Expertise und Markterfahrung in das Programm: über reale Robotik-Anwendungen, ROS, Automation, Embedded Systems und agile Entwicklung.

Learn now, pay later

To make it even easier to learn, you can finance your Nanodegree through Affirm.

  • Easy monthly payments

    As low as 100 $ per month at 0% APR.

    Learn more.

  • Flexible Payments

    Pay your monthly bill using a bank transfer, check, or debit card.

Abschnitt 1
Robotik-Software
$1199 USD

insgesamt

Du machst erste Erfahrungen mit ROS (Robotic Operating System) und tastest dich so an die robotischen Schlüsseldisziplinen Wahrnehmung, Steuerung und Deep Learning heran.

Abschnitt 2
Fortgeschrittene Robotik-Software
$1199 USD

insgesamt

Lerne bei und mit NVIDIA, SLAM (Lokalisierung und Mapping) und Reinforcement Learning-Techniken auf die Herausforderungen der Robotik anzuwenden.



Nanodegree-Programme bei Udacity

Jobs von morgen beginnen heute

Program Details

    PROGRAM OVERVIEW - WHY SHOULD I TAKE THIS PROGRAM?
  • Why should I enroll?

    Demand for software engineers with the right skills in robotics far exceeds the current supply of qualified talent. This makes this an ideal time to enter this field, and this groundbreaking program represents a unique opportunity to develop in-demand skills.

    Expert instructors and detailed project reviews are among hallmarks of this Nanodegree program, and in collaboration with the NVIDIA Deep Learning Institute—one of the most exciting and innovative companies in the world—we have built an unrivalled curriculum that offers a cutting-edge learning experience.

    You will graduate from this Nanodegree program having completed several hands-on robotics projects in simulation that will serve as portfolio pieces demonstrating acquired skills. These skills will enable you to pursue a rewarding career in the robotics field.

    Over the course of the Nanodegree program, you'll also have the opportunity to learn about robotics hardware such as the NVIDIA Jetson TX2 Developer Kit. Eligible students will also have access to a special education discount on the Jetson TX2 through our collaboration with NVIDIA.

    For anyone seeking to launch or advance a career as a Robotics Software Engineer, and who wishes to be a part of the incredible world of robotics, this is the ideal program.

  • What jobs will this program prepare me for?

    As a Robotics Software Engineer, you'll be equipped to bring value to a wide array of industries.

    Robotics Software Engineers opportunities might include:

    • developing pick and place robotics systems for advanced manufacturing;
    • developing the next surgical robot for the healthcare industry;
    • building the next form of package delivery either on the ground or in the air.
  • How do I know if this program is right for me?

    A career in robotics is exciting presenting changing challenges and new approaches constantly. If you want to work in an area where you get to see your solutions come to life and solve some of the world’s most difficult problems, a career in robotics is right for you! The Robotics Software Engineer Nanodegree program is here to provide you a great entry into the world of robotics and jumpstart your career in the field. You will gain the knowledge to create robotic systems in simulation and have the opportunity to turn those projects into real-world platforms if you purchase an NVIDIA TX2.

  • How is the Robotics Software Engineer Nanodegree program different from your Machine Learning Engineer Nanodegree program or your Self-Driving Car Engineer Nanodegree program?

    The Robotics Software Engineer Nanodegree program provides an introduction to software and artificial intelligence as applied to robotics. The areas we focus on are perception, localization, path planning, deep learning, reinforcement learning, and control. These are taught using the Robot Operating System (ROS) framework. All of the techniques required to complete the projects in the Robotics Software Engineer Nanodegree program (including machine learning) are taught as part of the program.

    The Machine Learning Engineer Nanodegree program is the most general of the three programs. It offers a great foundation, and is an excellent choice for anyone pursuing a career in a field where machine learning techniques are used. However, the curriculum is not as advanced or specialized as the other two programs.

    The Self-Driving Car Engineer Nanodegree program focuses entirely on a specialized application of robotics—it uses robotics concepts and applies them to a self-driving car. If your primary interest is in the application of robotics, machine learning, and artificial intelligence to autonomous vehicles, then this is the program for you. However, if you want a broader and more comprehensive robotics curriculum, with an emphasis on software engineering, then the Robotics Software Engineer Nanodegree program is your best option.

    Note: The Machine Learning Engineer program is not a prerequisite for either the Self-Driving Car or Robotics Software Engineer programs, but it may be beneficial to some students to complete this program first, depending on your existing knowledge and experience.

  • Do I need to apply? What are the admission criteria?

    No. This Nanodegree program accepts all applicants regardless of experience and specific background.

  • What are the prerequisites for enrollment?

    To succeed in this Nanodegree program, you need to have significant experience with:

    • Calculus and Linear Algebra
    • Statistics and Probability
    • Intermediate Python
    • Unix/Linux Command Line Basics
    • Basic Physics (Newtonian Mechanics)
    • English Skills

    Background in the following is recommended but not required:

    • Intermediate C++
    • Programming for ROS
    • Machine Learning
  • If I do not meet the requirements to enroll, what should I do?

    We have a number of Nanodegree programs and free courses that can help you prepare, including:

    • Machine Learning Engineer, Nanodegree program, by Udacity
    • AI for Robotics, by Udacity
    • Programming Foundations with Python, by Udacity
    • C++ tutorial, by Sololearn
    • Linux Command Line Basics, by Udacity
    • Statistics and Probability, by Khan Academy
    • Linear Algebra, by Khan Academy
    • Multivariable Calculus, by Khan Academy
    • ROS Tutorials
  • How is this Nanodegree program structured?

    The program is comprised of two (2) terms of four (4) months with fixed start and end dates. Students must successfully complete all assigned projects by the end date for each term to graduate from the full Nanodegree program. There are either 4 or 5 projects per Term, which give you an opportunity to apply the skills you've learned.

    To graduate, students must successfully complete the required projects, which give you the opportunity to apply and demonstrate new skills that you learn in the lessons. Each project will be reviewed by the Udacity reviewer network and platform. Feedback will be provided, and if you do not pass the project, you will be asked to resubmit the project until it passes.

  • How long is this Nanodegree program?

    Access to this Nanodegree program runs for the period noted in the Term length section above.

    See the Terms of Use and FAQs for other policies around the terms of access to our Nanodegree programs.

  • Can I switch my start date? Can I get a refund?

    Please see the Udacity Nanodegree program FAQs found here for policies on enrollment in our programs.

  • I have graduated from the Robotics Software Engineer Nanodegree program but I want to keep learning. Where should I go from here?

    Both our Self-Driving Car and Flying Car Nanodegree programs address specific areas of robotics and autonomous systems. If you want to continue your education either on the ground or in the air, take one of these exciting Nanodegree programs next!

  • What software and versions will I need in this program?

    For this Nanodegree program you will use the Robot Operating System (ROS) and Gazebo. You wl code primarily with Python in Term 1 and C++ in Term 2. These platforms and languages are freely available. There will also be various packages utilized, so an active internet connection is needed to download these. The projects are designed to run on a Linux operating system, which can be accommodated with the use of a virtual machine on other types of systems. Term 2 also features the use of a the new GPU-enabled Udacity Workspace within your browser for most of the projects and labs.

  • What special hardware will I need in this program?

    The core of this Nanodegree program focuses on robotics applications in software. You can master the skills, and complete every project, while focusing entirely on software, and working in simulation.

    We are also excited that our collaboration with NVIDIA DLI makes it possible for eligible Term 2 students to receive an education discount that can be applied to the purchase of an NVIDIA Jetson TX2 Developer Kit! Eligible students are encouraged to take advantage of this special offer, as this embedded supercomputing platform will enable you to take classroom projects (and your own personal projects) out of simulation and bring them into real-world scenarios.

    NVIDIA JETSON TX2 DEVELOPER KIT
  • What is the NVIDIA Jetson TX2 Developer Kit?

    NVIDIA Jetson is the world's leading platform for “AI at the edge.” Its high-performance, low-power computing for deep learning and computer vision makes it the ideal platform for compute-intensive robotics projects.

    For more information, see the NVIDIA Jetson Developer Zone.

  • I understand that as a benefit of being enrolled in this program, I have the opportunity to purchase the NVIDIA Jetson TX2 at a discount, is that true?

    Yes! As an enrolled student of the Robotics Software Engineer Nanodegree program, you are eligible to receive a special education discount that can be applied to the purchase of a Jetson TX2 Developer Kit.

  • What is the education discount?

    The education discount varies by region. For most countries the discount is 50% off the retail price of the Jetson TX2 Developer Kit.

  • How do I get the discount, and make the purchase?

    Upon successfully enrolling in Term 2 of the program, you'll receive an email with detailed instructions for buying the Jetson TX2 developer kit at the discounted price from the NVIDIA store, or the local distributor, depending on the country of residence.

    *Students must meet eligibility requirements as defined by NVIDIA on their site to purchase the Jetson TX2 Developer Kit with the education discount.

  • If I have an issue with my Jetson TX2 Developer Kit, who should I contact?

    NVIDIA will be supporting the Jetson TX2 hardware directly. You can find more information about support options here.

  • If I have an issue with the shipping of my Jetson TX2 Developer Kit, who should I contact?

    When you place your order, you should receive confirmation emails and contact information for the distributor who will be handling your order. Contact the distributor with your order number for any assistance needed.

    TUITION / PAYMENT
  • When is my tuition payment due?

    You pay your full tuition fee before the start of each term.

  • Is there a free preview for this program?

    Yes! Click here to start your free preview!

  • Are there scholarships or financial aid available?

    All current scholarship opportunities are posted on our Scholarships page.

    PROGRAM STRUCTURE
  • How is this Nanodegree program structured?

    The program is comprised of 2 terms (4 months each) with fixed start and end dates. Students must successfully complete all assigned projects by the end date for each term to graduate. There are 4-5 projects per term, which give you an opportunity to apply the skills you've learned in the lessons. Each project must be submitted for review by one of the expert project reviewers in the Udacity Robotics network. Your reviewer will give you detailed feedback on your work and let you know where your project needs improvement if necessary. You may submit each project as many times as you like.

  • Are there Udacity Connect sessions held for this program?

    No, not currently. Students of this program are welcome to attend Connect sessions, but we will not provide curriculum support at the sessions, nor will there be session leads onsite who are equipped to provide specific program guidance and input.

  • Do you offer the opportunity for students to pause their studies for this program?

    No, this is not an option. The fixed-term nature of the program, and the need for maintaining a consistent and stable student body throughout, doesn't allow for offering the option to pause your studies.

  • Is this program self-paced?

    The start and end dates of each term are fixed, and you must complete all assigned projects by the end dates, so to that extent, the answer is “no, it is not self-paced.” You must complete the program within a fixed time period. However, projects may be submitted at any time during the term, and individual project deadlines are recommendations, not requirements. So within the boundaries of a given term, there is some opportunity to work at your own pace. But you should plan to follow our recommended timeline, as this will best enable you to keep pace with your peers, and complete the program on time.

    DEADLINE POLICY
  • When we use the term "deadline" with regards to Nanodegree Program projects, we use it in one of two ways:

    • To mean a final deadline for submitting all projects
    • To refer to ongoing suggested deadlines for individual projects

    It is very important to understand the distinctions between the two, as your progress in the program is measured against the deadlines we've established. Please see below for an explanation of what each usage means.

  • A final deadline for submitting all projects

    In order to graduate a term, you must submit all projects by the last day of the term and pass all projects once they are reviewed by a Udacity Reviewer (the review may take place after the last day of the term). Passing a project means a Udacity Reviewer has marked a project as "Meets Specifications."

    If you do not submit all projects by the end of the term, and also pass all projects once they are reviewed, you will receive a 4-week extension to complete any outstanding projects. You will only receive this extension a maximum of once. Once you submit and pass all projects, you can enroll in the next term, which will potentially be with a later class. If you do not submit and pass all projects within the 4-week extension, you will be removed from the program.

  • Ongoing suggested deadlines for individual projects

    The deadlines you see in your classroom are suggestions for when you should ideally pass each project. They are meant to help keep you on track so that you maintain an appropriate pace throughout the program—one that will see you graduate on time!

    Please note that you can submit your project as many times as you need to. There are no penalties if you miss these deadlines. However, you will be at risk of not passing all projects on time if you miss these deadlines, and fall behind, so it is a recommended best practice to try and meet each suggested deadline.

Entwickle Robotik-Software

Programmiere ROS, Kinematik, Kontrolle, Computer Vision, KI und Reinforcement Learning