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Andrew Ng
KI ist nicht nur für Ingenieure. Wenn Sie möchten, dass Ihre Organisation KI besser einsetzt, ist dies der Kurs, an dem alle – insbesondere Ihre nicht technischen Kollegen – teilnehmen müssen.
In diesem Kurs lernen Sie:
- Die Bedeutung der gängigen KI-Terminologie, dazu gehören neuronale Netze, maschinelles Lernen, Deep Learning und Datenwissenschaft
- Was KI realistisch kann und was nicht
- Wie Sie Möglichkeiten erkennen, KI bei Problemen in Ihrer eigenen Organisation anzuwenden
- Wie man Projekte für maschinelles Lernen und Datenwissenschaften aufbaut
Read more
KI ist nicht nur für Ingenieure. Wenn Sie möchten, dass Ihre Organisation KI besser einsetzt, ist dies der Kurs, an dem alle – insbesondere Ihre nicht technischen Kollegen – teilnehmen müssen.
In diesem Kurs lernen Sie:
- Die Bedeutung der gängigen KI-Terminologie, dazu gehören neuronale Netze, maschinelles Lernen, Deep Learning und Datenwissenschaft
- Was KI realistisch kann und was nicht
- Wie Sie Möglichkeiten erkennen, KI bei Problemen in Ihrer eigenen Organisation anzuwenden
- Wie man Projekte für maschinelles Lernen und Datenwissenschaften aufbaut
Read more
KI ist nicht nur für Ingenieure. Wenn Sie möchten, dass Ihre Organisation KI besser einsetzt, ist dies der Kurs, an dem alle – insbesondere Ihre nicht technischen Kollegen – teilnehmen müssen.
In diesem Kurs lernen Sie:
- Die Bedeutung der gängigen KI-Terminologie, dazu gehören neuronale Netze, maschinelles Lernen, Deep Learning und Datenwissenschaft
- Was KI realistisch kann und was nicht
- Wie Sie Möglichkeiten erkennen, KI bei Problemen in Ihrer eigenen Organisation anzuwenden
- Wie man Projekte für maschinelles Lernen und Datenwissenschaften aufbaut
- Wie Sie mit einem KI-Team zusammenarbeiten und eine KI-Strategie in Ihrem Unternehmen entwickeln
- Wie man sich in ethischen und gesellschaftlichen Diskussionen rund um KI zurechtfindet
Obwohl dieser Kurs größtenteils nicht technisch ist, können Ingenieure diesen Kurs auch nutzen, um die geschäftlichen Aspekte der KI kennenzulernen.
Register for this course and see more details by visiting:
OpenCourser.com/course/oiha6d/ki
What's inside
Syllabus
Was ist KI?
KI-Projekte erstellen
Aufbau von KI in Ihrem Unternehmen
Read more
Syllabus
Was ist KI?
KI-Projekte erstellen
Aufbau von KI in Ihrem Unternehmen
Read more
KI und die Gesellschaft
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Andrew Ng, who leads Google Brain and has been recognized for their work in AI
Discusses current trends in AI and how they are applied in various sectors
Emphasizes the integration of AI with business and data science
Suitable for non-technical individuals seeking to understand the impact of AI
Addresses ethical and societal considerations around AI
This course is offered in German
Save this course
Save KI für alle to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in KI für alle with these
activities:
Practice KI terminology
Show steps
Solidify your understanding of KI terminology through repetitive practice.
Show steps
-
Create a glossary of KI terms.
-
Take practice quizzes on KI terminology.
-
Participate in online discussions about KI terminology.
Review KI concepts
Show steps
Review basic concepts in KI to strengthen your foundational understanding and prepare for the course.
Browse courses on
Machine Learning
Show steps
-
Read the course syllabus and introduction materials.
-
Review online resources and videos on KI concepts.
-
Attend an introductory workshop or webinar on KI.
Build a simple KI project
Show steps
Gain practical experience by building a simple KI project, applying the concepts you learn in the course.
Browse courses on
Machine Learning Projects
Show steps
-
Identify a problem that can be solved using KI.
-
Research different KI techniques and choose the most suitable one.
-
Implement the KI solution using a programming language.
-
Test and evaluate the performance of your KI project.
One other activity
Expand to see all activities and additional details
Show all four activities
Develop a KI strategy for your organization
Show steps
Apply your learnings to your professional context by developing a KI strategy for your organization.
Show steps
-
Conduct a KI assessment within your organization.
-
Identify opportunities where KI can add value.
-
Develop a roadmap for implementing KI solutions.
-
Create a plan for monitoring and evaluating the impact of KI.
Practice KI terminology
Show steps
Solidify your understanding of KI terminology through repetitive practice.
Show steps
Show steps
Show steps
- Create a glossary of KI terms.
- Take practice quizzes on KI terminology.
- Participate in online discussions about KI terminology.
Review KI concepts
Show steps
Review basic concepts in KI to strengthen your foundational understanding and prepare for the course.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Read the course syllabus and introduction materials.
- Review online resources and videos on KI concepts.
- Attend an introductory workshop or webinar on KI.
Build a simple KI project
Show steps
Gain practical experience by building a simple KI project, applying the concepts you learn in the course.
Browse courses on
Machine Learning Projects
Show steps
Show steps
Show steps
- Identify a problem that can be solved using KI.
- Research different KI techniques and choose the most suitable one.
- Implement the KI solution using a programming language.
- Test and evaluate the performance of your KI project.
One other activity
Expand to see all activities and additional details
Show all four activities
Develop a KI strategy for your organization
Show steps
Apply your learnings to your professional context by developing a KI strategy for your organization.
Show steps
Show steps
Show steps
- Conduct a KI assessment within your organization.
- Identify opportunities where KI can add value.
- Develop a roadmap for implementing KI solutions.
- Create a plan for monitoring and evaluating the impact of KI.
Career center
Learners who complete KI für alle will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist uses data to solve business problems and make predictions. This course provides a foundation in the key concepts and techniques of data science, including machine learning, deep learning, and data visualization. This knowledge can help Data Scientists develop and implement AI solutions that can improve business outcomes.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer builds and deploys machine learning models. This course provides a foundation in the key concepts and techniques of machine learning, including data preprocessing, model training, and evaluation. This knowledge can help Machine Learning Engineers develop and implement AI solutions that can solve business problems and improve outcomes.
Business Analyst
Business Analyst
A Business Analyst helps companies understand how to use technology to improve business processes. This course introduces key AI terminology and concepts, including machine learning, deep learning, and data science. This knowledge can help Business Analysts identify opportunities to use AI to solve business problems and make better decisions.
Product Manager
Product Manager
A Product Manager is responsible for the development and launch of new products. This course introduces key AI concepts and their potential applications in different industries. This knowledge can help Product Managers identify opportunities to use AI to create new products and services that meet customer needs.
Project Manager
Project Manager
A Project Manager plans and executes projects. This course provides an overview of the key concepts and techniques of project management, including scope definition, project planning, and risk management. This knowledge can help Project Managers successfully manage AI projects and ensure that they are delivered on time and within budget.
Data Analyst
Data Analyst
This course provides a foundation in the key concepts and techniques of data analysis, including data collection, data cleaning, and data visualization. This knowledge can help Data Analysts identify trends and patterns in data and communicate insights to stakeholders.
Software Engineer
Software Engineer
This course provides a foundation in the key concepts and techniques of software engineering, including software design, development, and testing. This knowledge can help Software Engineers develop and implement AI solutions that are scalable, reliable, and efficient.
Quality Assurance Analyst
Quality Assurance Analyst
This course provides an overview of the key concepts and techniques of quality assurance, including testing, defect tracking, and risk management. This knowledge can help Quality Assurance Analysts ensure that AI solutions are of high quality and meet customer requirements.
Technical Writer
Technical Writer
This course provides an overview of the key concepts and techniques of technical writing, including documentation, communication, and collaboration. This knowledge can help Technical Writers create clear and concise documentation for AI solutions that can be easily understood by users.
Sales Engineer
Sales Engineer
This course introduces key AI concepts and their potential applications in different industries. This knowledge can help Sales Engineers identify opportunities to use AI to solve customer problems and close deals.
Marketing Manager
Marketing Manager
This course introduces key AI concepts and their potential applications in different industries. This knowledge can help Marketing Managers identify opportunities to use AI to create and execute marketing campaigns that are more effective and engaging.
Operations Manager
Operations Manager
This course provides an overview of the key concepts and techniques of operations management, including process improvement, quality control, and supply chain management. This knowledge can help Operations Managers identify opportunities to use AI to improve operational efficiency and reduce costs.
Customer Success Manager
Customer Success Manager
This course introduces key AI concepts and their potential applications in different industries. This knowledge can help Customer Success Managers identify opportunities to use AI to improve customer satisfaction and retention.
Human Resources Manager
Human Resources Manager
This course introduces key AI concepts and their potential applications in different industries. This knowledge can help Human Resources Managers identify opportunities to use AI to improve recruiting, hiring, and employee development.
For more career information including salaries, visit:
OpenCourser.com/course/oiha6d/ki
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
KI für alle.
Save
Dieses Buch ist ein umfassender Leitfaden zu Deep Learning, einer Teilmenge der KI, die in den letzten Jahren an Bedeutung gewonnen hat. Es bietet eine gründliche Erläuterung der Theorie und Praxis des Deep Learning.
Dieses Buch bietet eine Einführung in Machine Learning aus einer probabilistischen Perspektive. Es ist eine gute Wahl für diejenigen, die ein tieferes Verständnis der theoretischen Grundlagen des Machine Learning erlangen möchten.
Dieses Buch bietet eine praktische Einführung in Machine Learning mit Python-Bibliotheken. Es ist eine wertvolle Ressource für diejenigen, die praktische Erfahrungen mit der Implementierung von Machine-Learning-Modellen sammeln möchten.
Dieses Buch bietet einen Überblick über Data Science, einschließlich der Techniken und Methoden zur Gewinnung von Erkenntnissen aus Daten. Es ist eine gute Wahl für diejenigen, die verstehen möchten, wie KI und Data Science in Unternehmen eingesetzt werden können.
Dieses Buch bietet eine umfassende Einführung in die KI, einschließlich ihrer Grundlagen, Anwendungen und ethischen Implikationen. Es ist eine gute Wahl für diejenigen, die ein umfassendes Verständnis der KI erlangen möchten.
Save
Dieses Buch bietet einen Überblick über die Geschichte, den aktuellen Stand und die Zukunft der KI. Es ist eine gute Wahl für diejenigen, die sich für die breiteren Implikationen der KI für Gesellschaft und Wirtschaft interessieren.
Dieses Buch untersucht die Herausforderungen bei der Entwicklung KI-Systeme, die mit menschlichen Werten vereinbar sind. Es ist eine gute Wahl für diejenigen, die sich für die langfristige Zukunft der KI interessieren.
Save
Dieses Buch untersucht die potenziellen Risiken und Vorteile einer hochentwickelten KI. Es ist eine gute Wahl für diejenigen, die sich für die langfristigen Auswirkungen der KI auf die Menschheit interessieren.
Save
Dieses Buch untersucht die möglichen Auswirkungen der KI auf unser Leben und unsere Gesellschaft. Es ist eine gute Wahl für diejenigen, die sich für die breiteren philosophischen Implikationen der KI interessieren.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/oiha6d/ki
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Effort
4 weeks of study, 2-3 hours/week
Level
Introductory
Via
Coursera
Institution
DeepLearning.AI
Instructor
Andrew Ng
Language
Deutsch
Transcripts
English
Español
Français
中文
العربية
日本語
Nederlands
ไทย
tiếng Việt
Good to know
Taught by Andrew Ng, who leads Google Brain and has been recognized for their work in AI
Discusses current trends in AI and how they are applied in various sectors
Emphasizes the integration of AI with business and data science
Suitable for non-technical individuals seeking to understand the impact of AI
Addresses ethical and societal considerations around AI
This course is offered in German
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