Serverless Machine Learning with Tensorflow on Google Cloud auf Deutsch from Coursera

***Wir möchten Sie darüber informieren, dass die Spezialisierung "Data Engineer, Big Data and ML on Google Cloud auf Deutsch" am 10. November 2020 geschlossen und nicht mehr angeboten wird.***

In diesem einwöchigen On-Demand-Intensivkurs erhalten Teilnehmer eine praxisorientierte Einführung in das Entwerfen und Erstellen von Modellen für das maschinelle Lernen (ML) mithilfe der Google Cloud Platform. In Präsentationen, Demos und praxisorientierten Labs lernen die Teilnehmer ML- und TensorFlow-Konzepte kennen und entwickeln ML-Modelle, die sie anschließend auswerten und produktionsreif machen.

ZIELE

In diesem Kurs werden die folgenden Fähigkeiten vermittelt:

● Anwendungsfälle für maschinelles Lernen erkennen

● ML-Modelle mit TensorFlow erstellen

● Skalier- und bereitstellbare ML-Modelle mit Cloud ML erstellen

● Bedeutung der Datenvorverarbeitung und der Kombination von Features verstehen

● Fortgeschrittene ML-Konzepte in Modelle einbinden

● Trainierte ML-Modelle produktionsreif machen

VORAUSSETZUNGEN

Für maximale Lernerfolge sollten die Teilnehmer folgende Voraussetzungen erfüllen:

● Abschluss des Kurses "Google Cloud Platform Fundamentals: Big Data & Machine Learning" ODER entsprechende Erfahrung auf dem Gebiet

● Grundkenntnisse in gängigen Abfragesprachen wie SQL

● Kenntnisse in Datenmodellierung, Extraktion, Transformation und Ladeaktivitäten

● Entwicklung von Anwendungen mit einer gängigen Programmiersprache wie Python

● Vertrautheit mit maschinellem Lernen und/oder Statistik

Hinweis zum Google-Konto:

• In China sind Google-Dienste derzeit nicht verfügbar.

What's inside

Syllabus

Willkommen zum serverlosen maschinellen Lernen mit der Google Cloud Platform

Modul 1: Einführung in maschinelles Lernen

Modul 2: ML-Modelle mit TensorFlow erstellen

Modul 3: ML-Modelle mit Cloud ML Engine skalieren

Modul 4: Feature Engineering

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Entwickelt Fähigkeiten für den Einsatz von Cloud Machine Learning, das in zukunftsgerichteten Unternehmen immer gefragter ist

Berücksichtigt Datenvorverarbeitung und Merkmalskombination, zwei grundlegende Elemente für die Entwicklung effektiver ML-Modelle

Bietet Hands-On-Labore und interaktive Materialien, die den Lernprozess lebendiger und ansprechender gestalten

Erfordert ein gewisses Maß an Vorwissen, was für Anfänger möglicherweise eine Hürde darstellen könnte

Ist Teil eines Spezialisierungsprogramms, was bedeutet, dass die Absolvierung anderer Kurse als Voraussetzung erforderlich sein kann

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 Serverless Machine Learning with Tensorflow on Google Cloud auf Deutsch with these activities:

Practice solving ML coding problems

Show steps

Solving ML coding problems is a great way to practice your coding skills and apply ML concepts. This activity will help you to become more confident in coding ML models and solving ML-related problems.

Browse courses on Problem Solving

Show steps

Find a set of ML coding problems.
Solve the problems on your own.
Check your solutions.
Review your mistakes.

Review your notes

Show steps

Taking time to review your notes can help you to retain the information better. This activity encourages you to organize your notes, identify key concepts, and reinforce your learning.

Browse courses on Revision

Show steps

Set aside time to review your notes.
Identify the key topics that you need to review.
Summarize each topic in your own words.

Follow Google Cloud ML tutorials

Show steps

Google provides a number of tutorials that teach you how to use the Google Cloud ML platform. These tutorials will help you to gain practical experience with Cloud ML, which will make you more confident in using it to build and deploy ML models.

Show steps

Choose a tutorial that interests you.
Follow the tutorial step-by-step.
Experiment with the tutorial code.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Study with classmates

Show steps

Studying with classmates can help you to understand concepts better and learn from different perspectives. This activity encourages you to collaborate with others, ask questions, and share your knowledge.

Show steps

Find a study group or create your own.
Meet regularly to discuss course materials.
Work together on assignments and projects.

Practice using TensorFlow

Show steps

TensorFlow is a powerful library for building and training ML models. This activity provides you with hands-on experience using TensorFlow, which will enhance your understanding of ML model development.

Browse courses on TensorFlow

Show steps

Install the TensorFlow library.
Create a new TensorFlow project.
Build a simple linear regression model.
Train your model and evaluate its performance.
Use your model to make predictions.

Create your own ML project

Show steps

This activity helps you to apply the principles of ML to solve a real-world problem, reinforcing your understanding of ML concepts.

Browse courses on Machine Learning

Show steps

Identify a problem that can be solved using ML.
Build a dataset for your project.
Choose an ML algorithm and train a model.
Deploy your model and test its performance.
Monitor your model and make adjustments as needed.

Write a blog post about ML

Show steps

Writing about what you learn can help you to retain the knowledge better. This activity promotes writing as a way to improve your learning, explore ML concepts in depth, and share your knowledge with others.

Show steps

Choose a topic that you are interested in.
Research your topic.
Write a compelling and informative blog post.

Career center

Learners who complete Serverless Machine Learning with Tensorflow on Google Cloud auf Deutsch will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

A Machine Learning Engineer develops and implements machine learning models that can be used to solve a variety of problems, such as image recognition, natural language processing, and predictive analytics. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are essential tools for Machine Learning Engineers. By completing this course, you will be well-positioned to enter or advance your career as a Machine Learning Engineer.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

A Data Scientist uses data to solve business problems. They use a variety of techniques, including machine learning, to analyze data and extract insights. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are essential tools for Data Scientists. By completing this course, you will be well-positioned to enter or advance your career as a Data Scientist.

See salaries and explore the career path for Data Scientist

Software Engineer

A Software Engineer designs, develops, and maintains software applications. They use a variety of programming languages and technologies to create software that meets the needs of users. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in software development. By completing this course, you will be well-positioned to enter or advance your career as a Software Engineer.

See salaries and explore the career path for Software Engineer

Cloud Architect

A Cloud Architect designs and manages cloud computing systems. They work with clients to understand their business needs and design a cloud solution that meets those needs. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in cloud computing. By completing this course, you will be well-positioned to enter or advance your career as a Cloud Architect.

See salaries and explore the career path for Cloud Architect

Data Analyst

A Data Analyst collects, analyzes, and interprets data to help businesses make informed decisions. They use a variety of techniques, including machine learning, to analyze data and extract insights. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are essential tools for Data Analysts. By completing this course, you will be well-positioned to enter or advance your career as a Data Analyst.

See salaries and explore the career path for Data Analyst

Business Analyst

A Business Analyst helps businesses to improve their operations by analyzing data and making recommendations. They use a variety of techniques, including machine learning, to analyze data and extract insights. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in business analysis. By completing this course, you will be well-positioned to enter or advance your career as a Business Analyst.

See salaries and explore the career path for Business Analyst

Product Manager

A Product Manager is responsible for the development and launch of new products. They work with a team of engineers, designers, and marketers to bring a product to market. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in product development. By completing this course, you will be well-positioned to enter or advance your career as a Product Manager.

See salaries and explore the career path for Product Manager

Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical models to analyze financial data. They use these models to make investment decisions and to manage risk. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in quantitative analysis. By completing this course, you will be well-positioned to enter or advance your career as a Quantitative Analyst.

See salaries and explore the career path for Quantitative Analyst

Statistician

A Statistician collects, analyzes, and interprets data to help businesses make informed decisions. They use a variety of techniques, including machine learning, to analyze data and extract insights. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in statistics. By completing this course, you will be well-positioned to enter or advance your career as a Statistician.

See salaries and explore the career path for Statistician

Operations Research Analyst

An Operations Research Analyst uses mathematical and statistical models to solve business problems. They use these models to improve efficiency and productivity. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in operations research. By completing this course, you will be well-positioned to enter or advance your career as an Operations Research Analyst.

See salaries and explore the career path for Operations Research Analyst

Market Research Analyst

A Market Research Analyst collects and analyzes data about consumers and markets. They use this data to help businesses make informed decisions about their products and marketing campaigns. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in market research. By completing this course, you will be well-positioned to enter or advance your career as a Market Research Analyst.

See salaries and explore the career path for Market Research Analyst

Financial Analyst

A Financial Analyst analyzes financial data to help businesses make informed investment decisions. They use a variety of techniques, including machine learning, to analyze data and extract insights. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in financial analysis. By completing this course, you will be well-positioned to enter or advance your career as a Financial Analyst.

See salaries and explore the career path for Financial Analyst

Actuary

An Actuary uses mathematical and statistical models to assess risk and uncertainty. They use these models to help businesses make informed decisions about their insurance and pension plans. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in actuarial science. By completing this course, you will be well-positioned to enter or advance your career as an Actuary.

See salaries and explore the career path for Actuary

Risk Manager

A Risk Manager identifies and assesses risks to a business. They develop and implement strategies to mitigate these risks. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in risk management. By completing this course, you will be well-positioned to enter or advance your career as a Risk Manager.

See salaries and explore the career path for Risk Manager

Auditor

An Auditor examines financial records to ensure that they are accurate and complete. They also make sure that businesses are complying with laws and regulations. This course provides a strong foundation in the principles of machine learning and TensorFlow, which are increasingly being used in auditing. By completing this course, you will be well-positioned to enter or advance your career as an Auditor.

See salaries and explore the career path for Auditor