Nanodegree-Programm

Werde Ingenieur für künstliche Intelligenz

Lerne die Grundlagen der Programmierung künstlicher Intelligenz

Künftig wird künstliche Intelligenz keine eigene Branche, sondern Teil jeder Branche sein. Unser Programm führt euch mit Experten wie Peter Norvig und Sebastian Thrun in KI-Grundlagen wie Search, Optimization, Planning oder Mustererkennung ein.

Kursvorschau

Bis 19. Juni anmelden!

  • Kursdauer
    3 Monate

    Lerne 12-15 Stunden/Woche, um in 3 Monaten abzuschließen

  • Kursbeginn
    19. Juni 2018
  • Voraussetzungen
    Algebra & Python

    Detaillierte Voraussetzungen ansehen

  • Sprache
    Englisch

    Lernmaterialien und Kurskommunikation in englischer Sprache

Was spricht für diesen Online-Kurs zur künstlichen Intelligenz?

Was ist künstliche Intelligenz? Diese Frage stellt sich heute nur noch selten. KI schreibt bereits die Zukunft unserer technologischen Umwelt geschrieben, sie wird unsere Leben in vielerlei Hinsicht neu definieren und ungemein erleichtern. Wer KI-Konzepte versteht, kann DIE Technologie unserer Zukunft wesentlich mitgestalten.

In diesem Programm lernst du von weltweit führenden KI-Experten und entwickelst ein Verständnis für die Grundlagen der künstlichen Intelligenz, für Algorithmen, die auf reale Herausforderungen in Feldern wie Natural Language Processing, Computer Vision oder Bioinformatik angewandt werden können. Mit dem strukturierten Vorgehen und Problemlösen bereitest du dich auf kommende KI-Herausforderungen und eine Karriere in jeder denkbaren Branche vor!


Was spricht für diesen Online-Kurs zur künstlichen Intelligenz?

KI-Experten verdienen zwischen $300-500K jährlich

Künstliche Intelligenz, reale Herausforderungen
Künstliche Intelligenz, reale Herausforderungen

Künstliche Intelligenz, reale Herausforderungen

Du lernst KI-Algorithmen, die bereits erfolgreich auf reale Herausforderungen in NLP, Computer Vision oder der Bioinformatik angewandt wurden. Diese Grundlagen kannst du auf diverse neue Problemfelder ausdehnen, um dein neues Wissen in der Welt geltend zu machen.

Lerne von und mit den Besten

Lerne von und mit den Besten

Erforsche probabilistische Modelle mit Sebastian Thrun, dem Gründer des Self-Driving Car-Teams von Google. Entdecke mit Peter Norvig, dem Co-Autor des führenden KI-Lehrbuchs, wie man zentrale KI-Algorithmen implementiert. Lerne mit diesen Kapazitäten, wie moderne KI-Probleme erfasst und gelöst werden können.

Persönliche Unterstützung
Persönliche Unterstützung

Persönliche Unterstützung

Dein Mentor steht dir während der gesamten Lernerfahrung für Fragen zur Verfügung. Bei deinen Projektarbeiten begleiten, korrigieren und fordern dich unsere KI-Experten.

Beweis' dich in Projektarbeiten

Beweis' dich in Projektarbeiten

Du beweist deinen Lernfortschritt an vier praxisnahen Projekten, die außerdem zur aussagekräftigen Ergänzung deiner kommenden Bewerbung werden. So entwickelst du unter anderem KI-Agenten, die Sudokus lösen, Games spielen oder Satzteile erkennen.

Was du lernst

Kursplan herunterladen
Lehrplan

Lerne grundlegende KI-Algorithmen

Lerne, Programme mit den grundlegenden KI-Algorithmen zu schreiben, die auch den Mars Rover der NASA oder DeepMinds AlphaGo Zero betreiben. Lernende werden u.a. den Beam Search- und Random Hill Climbing-Algorithmen, Bayessche Netze oder Hidden-Markov-Modelle beherrschen.

Lerne, Programme mit den grundlegenden KI-Algorithmen zu schreiben, die auch den Mars Rover der NASA oder DeepMinds AlphaGo Zero betreiben.

Weniger anzeigen

Dauer: 3 Monate

Voraussetzungen

Dieses Programm erfordert Erfahrung mit linearer Algebra, Statistik und Python (inkl. objektorientierter Programmierung).  Detaillierte Voraussetzungen ansehen

  • Constraint Satisfaction Problems

    Mithilfe eines Constraint Propagation und eines Searchalgorithmus entwirfst du einen Softbot, der Sudoku-Rätsel effizient löst.

    Der Sudoku-Enträtsler
  • Suche, Optimierung und Planung

    Baue einen KI-Bot vergleichbar mit dem Mars Rover der NASA, der seine Ziele mithilfe von Search und symbolischer Logik erreicht.

    Ein vorausdenkender Bot
  • Adversarial Search

    Du erweiterst deinen "klassischen" Suchalgorithmus auf Adversarial-Bereiche, um einen KI-Bot aufzubauen, der ohne menschliches Zutun sichere Entscheidungen trifft – vergleichbar zum AlphaGo-Agenten DeepMind.

    Baue einen Adversial Game Playing Agent
  • Grundlagen probabilistischer Grafikmodelle

    Für deinen KI-Bot modellierst du reale Unwägbarkeiten, um deine Mustererkennung durch Wahrscheinlichkeit zu trainieren.

    Trage deinen Teil zur Spracherkennung bei!

“Künstliche Intelligenz wird etliche Arbeitsplätze schaffen, auch solche, die heute noch gar nicht abzusehen sind! Ich denke, es ist nichts anderes als ein gewaltiger Fortschritt und aufregend für alle, die wissen, was sie damit anfangen können.”

— Jordan Bitterman, CMO, IBM Watson Content & IoT Platform

Von und mit den Besten lernen

Peter Norvig
Peter Norvig

Forschungsleiter, Google

Peter Norvig ist Forschungsleiter bei Google und Mitautor von „Artificial Intelligence: A Modern Approach“, dem führenden Lehrbuch auf diesem Gebiet.

Sebastian Thrun
Sebastian Thrun

Gründer, Udacity

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

Thad Starner
Thad Starner

Professor für Informatik, Georgia Tech

Thad Starner leitet die Contextual Computing Group (CCG) der Georgia Tech und ist einer der verdientesten technischen Leiter des Google-Projekts Google Glass.

Jetzt loslegen

Nanodegree-Programm
Künstliche Intelligenz
$599 USD

7 Tage Geld-zurück-Garantie

Lerne Methoden und Konzepte, um eigene KI-Anwendungen entwickeln zu können.

Jetzt loslegen

FAQ

    Highlights
  • Why should I enroll in this program?
    Udacity is the only place to offer this kind of opportunity. We have collaborated with the best companies in the field to offer world-class curriculum with instructors. This program provides a broad introduction to the field of artificial intelligence that can help you maximize your potential as an artificial intelligence or machine learning engineer. Almost any student anywhere in the world with an internet connection can study the field of artificial intelligence through Udacity.
  • What kinds of topics will the program cover?
    This program covers classical artificial intelligence techniques and algorithms including uninformed, heuristic, and adversarial search; local neighborhood & gradient free optimization; constraint satisfaction, symbolic logic, and planning; and probabilistic graphical models like Bayes nets & Hidden Markov Models.
  • How does the Artificial Intelligence 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 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.
  • 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.
    Enrollment & Structure
  • What is a Nanodegree Program?
    To read more about our Nanodegree program structure, please refer to Udacity FAQ.
  • Is this program online, in-person, or some combination of both?
    The program is online, and students interact with peers, mentors, coaches, and instructors in our virtual classrooms, in forums, and on Slack.
  • 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.
  • Once I am enrolled, when does the content become available?
    When you enroll, you are automatically added to the next available term. Every term has a fixed start date, and content becomes available on that date.

    Please note: You can enter es, 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?
    No. 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 course material after the term end date?
    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.
    Tuition & Payment
  • How much does the Nanodegree program cost?
    This Nanodegree program consists of one three month term. The term costs €799 (local curreny shown on page), paid at the beginning of the term.
  • 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.
  • 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.
  • 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.
  • 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.
  • Are there scholarships or financial aid available?
    All current scholarship opportunities are posted on our scholarships page.
    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


    Additionally, you should be able to follow and interpret pseudocode for algorithms like the example below and implement them in Python. You should also be able to informally evaluate the time or space complexity of an algorithm. For example, you should be able to explain that a for loop that does constant O(1) work on each iteration over an array of length n has a complexity of O(n).
    function Hill-Climbing(problem) returns a State current <- Make-Node(problem.Initial-State) loop do neighbor <- a highest-valued successor of current if neighbor.value ≤ current.value then return current.state current <- neighbor
  • If I don’t meet the requirements to enroll, what should I do?
  • 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 12-15 hours/week 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.
  • Can I enroll in other Nanodegree programs while I’m enrolled in the Artificial Intelligence Foundations program?
    We do not recommend doing so, though we do not prohibit concurrent enrollments. 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!
  • 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.
    Career
  • What jobs will this program prepare me for?
    This program is designed to build on your skills as an engineer or developer. As such, it doesn't prepare you for a specific job, but expands your skills with artificial intelligence algorithms. These skills can be applied to various applications such as video game AI, pathfinding for robots, and recognizing patterns over time like handwriting and sign language.
  • Will I receive a credential when I graduate, as with other Nanodegree programs?
    Yes! You will receive an Artificial Intelligence Nanodegree program credential after you successfully completed the program.
  • I've graduated from the Artificial Intelligence Nanodegree program, but I want to keep learning. Where should I go from here?
    Many of our graduates continue on to our Robotics Engineer Nanodegree program and our Self-Driving Car Engineer Nanodegree programs. Feel free to explore other Nanodegree program options as well.

Werde Ingenieur für künstliche Intelligenz

Lerne die Grundlagen der Programmierung künstlicher Intelligenz

Kursvorschau