Nanodegree-Programm

Computer Vision

Entwickle Software, die die Welt visuell wahrnimmt

Lerne die Computer Vision-Fähigkeiten hinter dem Fortschritt in der Robotik und Automatisierung. Hier lernst du, mithilfe von Deep Learning-Modellen eigene Programme zur Bildanalyse, Merkmalsextraktion oder Objekterkennung zu entwickeln.

Kursvorschau

Bis 24. April für den ersten Kurs anmelden

  • Kursdauer
    3 Monate

    Lerne 10-15 Stunden/Woche, um in 3 Monaten abzuschließen

  • Kursbeginn
    24. April 2018
  • Voraussetzungen
    Python, Statistik, Machine & Deep Learning

    Detaillierte Voraussetzungen ansehen

  • Sprache
    Englisch

    Lernmaterialien und Kurskommunikation in englischer Sprache

In Zusammenarbeit mit
  • Affectiva
  • Nvidia

Was spricht für dieses Nanodegree-Programm?

Von der Computergrafik über die soziale Robotik bis hin zu autonomen Fahrzeugen - Computer Vision ermöglicht neue Technologien, die die Welt verändern. In diesem Programm lernst du, Computer Vision in Anwendungen zur Gesichtserkennung, zum Szenenverständnis bis hin zur Objektverfolgung zu programmieren. Am Ende wirst du ein Zertifikat und ein eindrucksvolles Portfolio mit eigenen Programmen vorzeigen können.


Was spricht für dieses Nanodegree-Programm?

Die Nachfrage nach KI-Experten hat sich in den vergangene 3 Jahren mehr als verdoppelt.

Lerne heute, was morgen gebraucht wird
Lerne heute, was morgen gebraucht wird

Lerne heute, was morgen gebraucht wird

Computer Vision wächst rasant! Es ermöglicht eine unzählige Technologien maschineller Intelligenz, von Gesichtserkennung und Augmented Reality bis hin zu selbstfahrenden Autos. Wer heute die neuesten Deep Learning-Architekturen und Bildverarbeitungstechniken lernt, wird sich seinen Job morgen aussuchen können.

Lerne von und mit der Industrie

Lerne von und mit der Industrie

Wir haben das Programm mit Branchenführern wie NVIDIA und Affectiva gemeinsam konzipiert. Zum einen lernen wir so, welche Kenntnisse diese Unternehmen an Fachkräften schätzen, zum anderen lernt ihr, wo, wozu und wie Computer Vision heute in vorderster Front eingesetzt wird.

Lerne an praxisnahen Projekten
Lerne an praxisnahen Projekten

Lerne an praxisnahen Projekten

Du lernst, wie man Computer Vision in Python programmiert und dieses Wissen umgehend anwenden: Drei praxisnahe Computer Vision-Projekte stellen nicht nur deinen Lernfortschritt sicher, sie garantieren auch ein aussagekräftiges Portfolio für deine nächste Bewerbung.

Wachse an unserem Feedback

Wachse an unserem Feedback

Jedes deiner Computer Vision-Projekte wird von einem unserer Experten begutachtet. Sie werden dir nicht nur zeigen, wie sich deine Arbeit an Computer Vision-Modellen als Teil eines Großprojektes einfügt. Sie werden dich auch als Programmierer weiterentwickeln. So lernst du effektiv, aber nachhaltig und wächst an jeder Zeile Code.

Von und mit den Besten lernen

Sebastian Thrun
Sebastian Thrun

Präsident von Udacity

Sebastian ist Wissenschaftler, Pädagoge, Erfinder und Unternehmer. Vor der Gründung von Udacity startete er unter anderem Googles Self-Driving Car-Projekt.

Cezanne Camacho
Cezanne Camacho

Kursleiterin

Cezanne hat ihren Master in Elektrotechnik an der Stanford University gemacht. Als ehemalige Forscherin für Genomik und biomedizinische Bildgebung hat sie Computer Vision und Deep Learning bereits in der medizinischen Diagnostik angewandt.

Alexis Cook
Alexis Cook

Content Developer

Alexis hat angewandte Mathematik in Michigan studiert und einen Master in Informatik gemacht. Sie kommt aus einem National Science Foundation Stipendiat für die Deep Learning- und Machine Learning-Programme zu Udacity.

Juan Delgado
Juan Delgado

Content Developer

Juan ist Computerphysiker und promovierter Biophysiker mit Astronomie M.A.. Zu Udacity kam Juan von der NASA, für die er Weltrauminstrumente entwickelte – und Software, die wissenschaftliche Datenmassen mit Machine Learning-Techniken analysiert.

Jay Alammar
Jay Alammar

Content Developer

Als Entwickler liebt Jay die Visualisierung von Machine Learning-Konzepten. Er ist Investmentchef bei Riyad Taqnia, einem $120 Mio.-Wagniskapitalgeber für Hightech-Start-ups.

Ortal Arel
Ortal Arel

Content Developer

Ortal hat in Computertechnik promoviert, auf dem Feld der angewandten Kryptographie doziert und geforscht. Zuletzt hat sie für Endkunden digitale Hochgeschwindigkeitsarchitekturen analysiert und entwickelt.

Luis Serrano
Luis Serrano

Content Developer

Luis ist Doktor der Mathematik und Postdoc-Stipendiat der Universität Quebec. Zu Udacity stieß Luis von Google, wo er vorher als Machine Learning-Ingenieur tätig war.

Was du lernst

Kursplan herunterladen
Lehrplan

Grundlagen der Computer Vision

Du lernst modernste Computer Vision- und Deep-Learning-Techniken, von einfacher Bildverarbeitung bis hin zu konvolutionellen neuronalen Netwerken. Wende diese Konzepte zur automatischen Bildbeschreibung und Objektverfolgung an, um ein starkes Portfolio mit Bildverarbeitungsprojekten zu erstellen.

Arbeite an einer Vielzahl von Computer Vision- und Deep Learning-Anwendungen, von der einfachen Bildverarbeitung bis zur automatischen Bildbeschreibung.

Weniger anzeigen

Dauer: 3 Monate

Voraussetzungen

Das Programm erfordert Erfahrung mit Python, Machine Learning und Deep Learning sowie Statistik-Kenntnisse. Detaillierte Voraussetzungen ansehen

  • Einführung in die Computer Vision

    Wir legen die Grundlagen der Computer Vision und Bildverarbeitung. Dabei lernst du u. a., wie wichtige Merkmale aus Bilddaten extrahiert und wie Deep Learning-Techniken auf Klassifizierungsaufgaben angewandt werden.

    Gesichter erkennen
  • Fortgeschrittene Computer Vision und Deep Learning

    Lerne, Deep Learning-Architekturen auf Computer Vision-Aufgaben anzuwenden. Du entdeckst dabei, wie CNN- und RNN-Netzwerke zur Entwicklung einer automatischen Bildbeschreibungsanwendung kombiniert werden können.

    Automatische Bildunterschriften
  • Objekte verfolgen und verorten

    Lerne, Objekte zu lokalisieren und über einen gewissen Zeitraum zu verfolgen. Diese Techniken sind zentral für eine Vielzahl bewegter Systeme, etwa in der Navigation unbemannter Autos oder Drohnen.

    Simultane Lokalisierung und Kartenerstellung (SLAM)

“Computer Vision zählt zum Fundament maschineller Intelligenz. Es wird Unternehmen, Branchen, ja ganze Geschäftsmodelle transformieren.”

— Fei-Fei Li, Chief Scientist, Google Cloud
Nur für kurze Zeit
Computer Vision
€799$599 USD

7 Tage Geld-zurück-Garantie

Lerne die wichtigsten Computer Vision-Systeme (OpenCV, Deep Learning) und wende sie in eigenen Anwendungen wie Gesichtserkennungen oder neuronalen Netzen an.

Jetzt loslegen

*Bis 24. April anmelden und sparen!

FAQ

    Highlights
  • Why should I enroll in this program?
    The demand for engineers with computer vision and deep learning skills far exceeds the current supply. This program offers a unique opportunity to develop these in-demand skills and is for anyone seeking to launch or advance their skills in modern computer vision techniques. You’ll complete several computer vision applications using a combination of Python, computer vision, and deep learning libraries that will serve as portfolio pieces that demonstrate the skills you’ve acquired.
  • What kinds of topics will the program cover?
    This program covers a combination of classical and modern artificial intelligence techniques specific to computer vision. The program starts by exploring the fundamental math and programming concepts that drive pattern and object recognition tasks, such as image processing, image color and shape manipulation, feature detection, and convolutional neural network (CNN) architecture. Then, the program moves onto deep learning architectures that have led to state of the art advances in computer vision tasks, such as region-based CNN’s and recurrent neural networks for image captioning. Lastly, it covers object tracking and localization techniques that are necessary skills for those looking to get into the field of robotics and autonomous systems.
  • How are you developing the curriculum, and who are your partners?
    Udacity has developed the Computer Vision Nanodegree program in partnership with NVIDIA, a cutting-edge deep learning and robotics company whose work relies on the computer vision techniques of scene understanding and robot localization. We have also partnered with Affectiva, an emotion-recognition technology company that is contributing to the development of social robotics and emotionally intelligent systems.
  • Will content from the program also be available for free outside of the Nanodegree program?
    While some of the video material is available outside of the program, most of the material will only be available to enrolled Nanodegree students. Access to project feedback, instructor support, and hiring partners are benefits exclusive to the Nanodegree programs.
  • How does the Computer Vision Nanodegree program differ from Udacity’s free AI courses?
    Our free courses are an excellent way to refresh your skills on a particular topic, or address a particular arena where you may need to advance your skills in order to pursue the next stage of your learning. But to benefit from the full measure of what Udacity can do to support your career goals, you’ll want to enroll in the Nanodegree program, where you’ll gain access to personalized project reviews, classroom mentorship, personalized career guidance, and more. The Nanodegree program is also the best way to pursue specializations, as you’ll benefit from exclusive access to unique content.
    Enrollment & Program Structure
  • What is a Nanodegree Program?
    To read more about our Nanodegree program structure, please refer to Udacity FAQ.
  • What payment methods do you accept?
    At this time we only accept credit cards in Europe. Since last year, students in Germany, Austria and Switzerland also have the option to pay via SEPA direct debit. We hope to add more payment options in the near future.
    Please note that you can always change your payment method.
  • Can I enroll in the program at any time?
    Yes! We admit students on a rolling basis, and you will automatically be added to the next available term once you’ve successfully enrolled. Depending on when you enroll, your term may start as late as four weeks after your enrollment date.
  • Can I enter the classroom prior to the start of my term?
    Yes, but you won't be able to access the content, as it stays locked until your term begins. In the classroom, you'll see a countdown to your term's start date.
  • Are deferments an option if I'm enrolled, but not ready to start yet?
    No, deferments are not an option. We ask that you please make sure to enroll for a term only if you are able to commit to the entire time frame.
  • Is this program self-paced?
    This is not a self-paced program. Students will need to keep pace with their peers throughout the duration of the program and complete all graduation requirements before the term end date (plus any allowed extension).
  • I know you offer the opportunity for students to pause their studies in other Nanodegree programs; will that be an option for this program?
    The fixed-term nature of the program, and the need for maintaining a consistent and stable student body throughout, precludes offering the option to pause your studies.
  • What happens if I don’t complete a project on time?
    It is strongly recommended that you complete each project on time to ensure you meet graduation requirements. To graduate, you must complete, submit, and meet expectations for all required projects by the final deadline . While there is no penalty for missing a project deadline, missing one puts you at risk to be removed from the program if you do not stay on track and complete all required projects before the term ends. Finally, by keeping pace with your fellow students, you'll gain much more value from forums and Slack channels!
  • What happens if I don't complete a term by the term deadline?
    You will receive a free four-week extension, which is automatically applied to your account if you do not complete the program within the term. If you do not complete the program within the extension, you will be removed from the program and will no longer be able to access course content. To resume access to the course, you would need to pay the term fee again. In such case, your progress will carry over, so you will be able to continue where you left off.
  • Will I have access to the material even after the term ends?
    No. You will retain access to the program materials for a period of time after graduation and you may download certain materials for your own records if you wish. Please note however, that students who leave the program—or who are removed from the program for failure to meet the final deadlines—prior to successfully graduating, will cease to have access.
    Prerequisites
  • What are the prerequisites for enrollment?
    You must have completed a course in Deep Learning equivalent to the Deep Learning Nanodegree program prior to entering the program. Additionally, you should have the following knowledge:
    Intermediate Python programming knowledge, including:
    • Strings, numbers, and variables
    • Statements, operators, and expressions
    • Lists, tuples, and dictionaries
    • Conditions, loops
    • Generators & comprehensions
    • Procedures, objects, modules, and libraries
    • Troubleshooting and debugging
    • Research & documentation
    • Problem solving
    • Algorithms and data structures

    Basic shell scripting:

    • Run programs from a command line
    • Debug error messages and feedback
    • Set environment variables
    • Establish remote connections

    Basic statistical knowledge, including:

    • Populations, samples
    • Mean, median, mode
    • Standard error
    • Variation, standard deviations
    • Normal distribution

    Intermediate differential calculus and linear algebra, including:

    • Derivatives & Integrals
    • Series expansions
    • Matrix operations through eigenvectors and eigenvalues
  • If I don’t meet the requirements to enroll, what should I do?
  • What software and versions will I need in this program?
    You will need a computer running a 64-bit operating system (most modern Windows, OS X, and Linux versions will work) with at least 8GB of RAM, along with administrator account permissions sufficient to install programs including Anaconda with Python 3.5 and supporting packages. Your network should allow secure connections to remote hosts (like SSH). We will provide you with instructions to install the required software packages.
  • Can I enroll in other Nanodegree programs while I’m enrolled in the AI Programming with Python Nanodegree program?
    Our programs require a serious time commitment from students, so while we do not recommend doing so, we do not prohibit concurrent enrollments. This is an intensive, paced program, and students must proceed throughout the programs at the required rate of progress. To make the most of your experience, we believe you are best served by focusing on one program at a time and being fully immersed in the unique structure and pacing. You can always take one after the other!
  • How many hours a week should I expect to spend on my coursework, in order to succeed in this program?
    Between instructional content, quizzes, projects, and other course-related activity, we estimate that investing 10 hours/week for 3 months will enable you to proceed through the program at a successful pace. Students with significant prior experience may spend less time, while students with very limited prior experience may require significantly more time.
    Tuition & Payment
  • How much does the Nanodegree program cost?
    This Nanodegree program consists of one three month term. The term costs €799 (local currencies shown on overview page), paid at the beginning of the term.
  • Is payment due before the term begins?
    Yes. In this way, we know exactly how many student are in a term, and can optimize our instructional and support resources accordingly. Additionally, this approach ensures a consistent and stable student body throughout the program, which fosters a deeper sense of community, and enables richer collaborations as students work together as a group.
  • Is there an installment plan for tuition?
    No, the full tuition must be paid before the start of your term.
  • Why are students required to pay the full term fee in advance vs. a monthly payment format like other Nanodegree programs?
    Given the extended curriculum and the services available to students, it is critical that we know exactly how many students we’ll be supporting and teaching. It’s important that this student body remains consistent and stable throughout the duration of the program as they work together as a group.
  • Is there a free trial period for this program?
    There is no free trial period for this program.
  • Are there any scholarships available for this program?
    All current scholarship opportunities are posted on our Scholarships page.
  • What is the refund policy?
    There is a 7-day refund policy. During this time, you can visit the Settings page of your Udacity classroom where you can unenroll and request a full refund. This 7-day window begins the day the classroom opens. After the first 7 days, course fees are non-refundable.
    Career
  • What jobs will this program prepare me for?
    This program is designed to build on your skills in machine learning and deep learning. As such, it doesn't prepare you for a specific job, but expands your skills in the computer vision domain. These skills can be applied to various applications such as image and video processing, automated vehicles, smartphone apps, and more.
  • Will I receive a credential when I graduate, as with other Nanodegree programs?
    Yes! You will receive an Computer Vision Nanodegree program credential after you successfully complete the program.
  • I've graduated from the Computer Vision Nanodegree program, but I want to keep learning. Where should I go from here?
    Many of our graduates continue on to our Artificial Intelligence Nanodegree program, Natural Language Processing Nanodegree Program, Robotics Engineer Nanodegree program, and our Self-Driving Car Engineer Nanodegree programs. Feel free to explore other Nanodegree program options as well.

Computer Vision

Entwickle Software, die die Welt visuell wahrnimmt

Kursvorschau