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Google Cloud Training
A inteligência artificial (IA) e o machine learning (ML) representam importantes evoluções na tecnologia da informação que estão transformando uma ampla variedade de setores. O curso ""Innovating with Google Cloud Artificial Intelligence"" mostra como as organizações podem usar a IA e o ML para transformar processos comerciais.
Como parte do programa de aprendizado do Cloud Digital Leader, o objetivo deste curso é ajudar você a crescer profissionalmente e desenvolver o futuro do seu próprio negócio.
Register for this course and see more details by visiting:
OpenCourser.com/course/7esuxe/innovating
What's inside
Syllabus
Introdução ao curso
Nesta introdução, vamos conhecer os objetivos do curso e conferir uma prévia de cada seção.
Noções básicas de IA e ML
A inteligência artificial e o machine learning trazem muitos benefícios às empresas, mas é importante entender o básico antes de tomar qualquer iniciativa do tipo. Nesta seção do curso, você vai conhecer vários desses conceitos fundamentais.
Read more
Syllabus
Introdução ao curso
Nesta introdução, vamos conhecer os objetivos do curso e conferir uma prévia de cada seção.
Noções básicas de IA e ML
A inteligência artificial e o machine learning trazem muitos benefícios às empresas, mas é importante entender o básico antes de tomar qualquer iniciativa do tipo. Nesta seção do curso, você vai conhecer vários desses conceitos fundamentais.
Read more
Soluções de IA e ML do Google Cloud
Nesta seção do curso, você vai conhecer quatro opções para criar modelos de ML com o Google Cloud: BigQuery ML, APIs pré-treinadas, AutoML e treinamento personalizado.
Resumo do curso
O curso termina com um resumo dos pontos principais de cada seção e as próximas etapas de aprendizado.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Desenvolve habilidades fundamentais em IA e ML, que são essenciais para a transformação digital das organizações
Explora conceitos básicos de IA e ML, possibilitando que iniciantes entendam esses tópicos complexos
Oferece opções flexíveis para criar modelos de ML usando soluções do Google Cloud, atendendo a diversas necessidades
Ministrado pelo Google Cloud Training, reconhecido por sua expertise em tecnologias avançadas
Aborda a aplicação prática de IA e ML em processos de negócios, capacitando os alunos a impulsionar a inovação organizacional
Requisitos explícitos de pré-requisitos, indicando a necessidade de conhecimento prévio em IA e ML
Save this course
Save Innovating with GC Artificial Intelligence - Português 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 Innovating with GC Artificial Intelligence - Português with these
activities:
Review AI and ML Basics
Show steps
Brush up on fundamental AI and ML concepts before diving into the course to ensure a solid foundation.
Show steps
-
Identify and define key concepts of AI and ML, such as machine learning algorithms and data preprocessing.
-
Explore real-world applications of AI and ML in various industries.
Review Machine Learning Basics
Show steps
Reviewing the basics of machine learning will build a stronger foundation for your learning in this course
Browse courses on
Machine Learning Fundamentals
Show steps
-
Revisit supervised vs unsupervised learning
-
Review common machine learning algorithms
-
Practice implementing a simple machine learning model in code
Explore Google Cloud AI Platform Documentation
Show steps
Google Cloud AI Platform documentation provides in-depth technical resources to support your learning progress
Show steps
-
Find and read documentation relevant to this course
-
Follow along with code samples and tutorials
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Do AI and ML Code Challenges
Show steps
Coding challenges will provide hands-on practice and help you improve your understanding of AI and ML concepts
Browse courses on
AI Coding
Show steps
-
Find coding challenges tailored to the topic
-
Dive into the coding challenge and start practicing
-
Evaluate your solution and learn from your mistakes
Practice Model Training Exercises
Show steps
Engage in hands-on exercises to reinforce the model training process and enhance your understanding of algorithm selection and parameter tuning.
Show steps
-
Set up a development environment for ML model training.
-
Experiment with different ML algorithms and evaluate their performance on provided datasets.
-
Fine-tune model parameters to optimize accuracy and efficiency.
Join a Study Group for the Course
Show steps
Participating in a study group can provide support, encourage active learning, and promote a deeper understanding of course materials
Show steps
-
Find or form a study group with other students enrolled in the course
-
Establish regular meeting times and topics
-
Discuss course concepts, review materials, and work through problems together
Contribute to Open Source AI/ML Projects
Show steps
Contributing to open source projects allows you to collaborate with the wider AI/ML community and gain practical experience
Show steps
-
Find a suitable open source AI/ML project that aligns with your interests and skills
-
Review the project documentation and codebase
-
Identify an area where you can contribute
-
Fork the project repository, make changes, and submit a pull request
Participate in an AI or ML Competition
Show steps
Competitions provide a practical and challenging way to apply and test your skills in AI and ML
Show steps
-
Identify and join a relevant competition related to the course topics
-
Prepare by reviewing and studying relevant materials
-
Develop and submit your solution
-
Analyze your results and learn from your experience
Develop a Case Study Presentation
Show steps
Showcase your understanding of AI and ML applications by creating a case study presentation that demonstrates real-world impact and value.
Show steps
-
Identify an industry or business problem that can be addressed with AI and ML.
-
Research and gather data to support your case.
-
Design and develop a prototype solution.
-
Evaluate the results and present your findings.
Explore Advanced ML Techniques
Show steps
Expand your knowledge beyond the course content by following tutorials and exploring advanced ML techniques, such as deep learning and natural language processing.
Show steps
-
Identify a specific advanced ML technique to explore.
-
Locate and follow online tutorials or workshops.
-
Implement the technique in a practical project.
Review AI and ML Basics
Show steps
Brush up on fundamental AI and ML concepts before diving into the course to ensure a solid foundation.
Show steps
Show steps
Show steps
- Identify and define key concepts of AI and ML, such as machine learning algorithms and data preprocessing.
- Explore real-world applications of AI and ML in various industries.
Review Machine Learning Basics
Show steps
Reviewing the basics of machine learning will build a stronger foundation for your learning in this course
Browse courses on
Machine Learning Fundamentals
Show steps
Show steps
Show steps
- Revisit supervised vs unsupervised learning
- Review common machine learning algorithms
- Practice implementing a simple machine learning model in code
Explore Google Cloud AI Platform Documentation
Show steps
Google Cloud AI Platform documentation provides in-depth technical resources to support your learning progress
Show steps
Show steps
Show steps
- Find and read documentation relevant to this course
- Follow along with code samples and tutorials
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Do AI and ML Code Challenges
Show steps
Coding challenges will provide hands-on practice and help you improve your understanding of AI and ML concepts
Browse courses on
AI Coding
Show steps
Show steps
Show steps
- Find coding challenges tailored to the topic
- Dive into the coding challenge and start practicing
- Evaluate your solution and learn from your mistakes
Practice Model Training Exercises
Show steps
Engage in hands-on exercises to reinforce the model training process and enhance your understanding of algorithm selection and parameter tuning.
Show steps
Show steps
Show steps
- Set up a development environment for ML model training.
- Experiment with different ML algorithms and evaluate their performance on provided datasets.
- Fine-tune model parameters to optimize accuracy and efficiency.
Join a Study Group for the Course
Show steps
Participating in a study group can provide support, encourage active learning, and promote a deeper understanding of course materials
Show steps
Show steps
Show steps
- Find or form a study group with other students enrolled in the course
- Establish regular meeting times and topics
- Discuss course concepts, review materials, and work through problems together
Contribute to Open Source AI/ML Projects
Show steps
Contributing to open source projects allows you to collaborate with the wider AI/ML community and gain practical experience
Show steps
Show steps
Show steps
- Find a suitable open source AI/ML project that aligns with your interests and skills
- Review the project documentation and codebase
- Identify an area where you can contribute
- Fork the project repository, make changes, and submit a pull request
Participate in an AI or ML Competition
Show steps
Competitions provide a practical and challenging way to apply and test your skills in AI and ML
Show steps
Show steps
Show steps
- Identify and join a relevant competition related to the course topics
- Prepare by reviewing and studying relevant materials
- Develop and submit your solution
- Analyze your results and learn from your experience
Develop a Case Study Presentation
Show steps
Showcase your understanding of AI and ML applications by creating a case study presentation that demonstrates real-world impact and value.
Show steps
Show steps
Show steps
- Identify an industry or business problem that can be addressed with AI and ML.
- Research and gather data to support your case.
- Design and develop a prototype solution.
- Evaluate the results and present your findings.
Explore Advanced ML Techniques
Show steps
Expand your knowledge beyond the course content by following tutorials and exploring advanced ML techniques, such as deep learning and natural language processing.
Show steps
Show steps
Show steps
- Identify a specific advanced ML technique to explore.
- Locate and follow online tutorials or workshops.
- Implement the technique in a practical project.
Career center
Learners who complete Innovating with GC Artificial Intelligence - Português will develop knowledge and skills
that may be useful to these careers:
Machine Learning Scientist
Machine Learning Scientist
Machine Learning Scientists pioneer the research in this field. This course can help a Machine Learning Scientist stay current with their field.
Artificial Intelligence Researcher
Artificial Intelligence Researcher
Artificial Intelligence Researchers focus on developing new AI and ML algorithms, as well as new applications for existing algorithms. This course can help an Artificial Intelligence Researcher stay current with the latest trends and developments in the field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for building and maintaining ML models in a production environment. This course can help a Machine Learning Engineer better understand the models they will be deploying.
Data Scientist
Data Scientist
Data Scientists build and maintain the models used in AI and ML applications. This course can help them stay current and expand on this skillset. The course especially helps those with a focus on Google Cloud products.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts create and analyze models to find ways to improve business outcomes. This course can help an Operations Research Analyst build the skills needed to use AI and ML to improve their models and achieve better results for their organizations.
Statistician
Statistician
Statisticians devise, carry out, and interpret statistical analyses. This course can help a Statistician with a focus on machine learning and AI gain knowledge of the latest trends and developments in the field.
Data Analyst
Data Analyst
Data Analysts help create and use models that can help a company understand its data and make better decisions. This course is particularly relevant because it provides an introduction to the machine learning used to build these models.
Data Engineer
Data Engineer
Data Engineers are responsible for building the infrastructure that makes AI and ML models possible in a production environment. This course can help a Data Engineer better understand the models they will be deploying.
Software Engineer
Software Engineer
Software Engineers work closely with Data Scientists and Machine Learning Engineers to build out the rest of the software application that uses the AI and ML models. This course can help a Software Engineer better understand the models they will be working with.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to make better decisions. This course can help a Business Intelligence Analyst build the skills they need to utilize AI and ML in their work and develop better insights.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists transform data into easy to understand visual representations. This course can help a Data Visualization Specialist build the knowledge they need to build more effective visuals that leverage new insights provided by AI and ML.
ETL Developer
ETL Developer
ETL Developers help build the pipelines that make data available to data scientists for analysis. This course can help an ETL Developer learn about the varied sources of data that AI and ML models can leverage, and how to design pipelines that can better leverage these sources.
Quantitative Researcher
Quantitative Researcher
Quantitative Researchers use statistical and mathematical models to analyze financial data. This course can help a Quantitative Researcher gain more foundational knowledge of machine learning and AI.
Cloud Architect
Cloud Architect
Cloud Architects are responsible for making decisions about an organization's cloud computing environment. This course can help a Cloud Architect better understand the AI and ML services offered by their cloud provider.
Product Manager
Product Manager
Product Managers work closely with technical teams to determine the scope of the product's machine learning capabilities, the data the product will process and how that data will be stored during use. They may also work with marketing teams to help evangelize the benefits of the company's machine learning capabilities to customers. This course can help a Product Manager better understand the technical side of machine learning and AI applications.
For more career information including salaries, visit:
OpenCourser.com/course/7esuxe/innovating
Reading list
We've selected eight 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
Innovating with GC Artificial Intelligence - Português.
Save
Provides a comprehensive overview of deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone who wants to learn more about the latest advances in deep learning.
Este livro didático avançado fornece uma compreensão probabilística abrangente do aprendizado de máquina. É uma leitura essencial para aqueles que buscam uma compreensão profunda dos fundamentos teóricos do ML.
Save
Este livro fascinante explora a história e o potencial futuro do aprendizado de máquina. É uma ótima leitura para aqueles que desejam entender o desenvolvimento e o impacto da IA no mundo.
Este livro prático guia os leitores no uso da biblioteca Keras do Python para construir e treinar modelos de aprendizado profundo. É uma ótima escolha para aqueles que desejam se familiarizar com o aprendizado profundo e suas aplicações.
Save
Provides a comprehensive overview of machine learning, covering topics such as supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone who wants to learn more about the fundamentals of machine learning.
Provides a practical guide to machine learning, with a focus on using Scikit-Learn, Keras, and TensorFlow. It great resource for anyone who wants to learn how to build and train machine learning models using popular open-source tools.
Provides a comprehensive overview of artificial intelligence, covering topics such as the history of AI, different types of AI, and the ethical implications of AI. It valuable resource for anyone who wants to learn more about the big picture of AI.
Provides a non-technical overview of artificial intelligence, making it accessible to anyone who wants to learn more about this rapidly growing field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/7esuxe/innovating
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Level
Introductory
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
Português
Good to know
Desenvolve habilidades fundamentais em IA e ML, que são essenciais para a transformação digital das organizações
Explora conceitos básicos de IA e ML, possibilitando que iniciantes entendam esses tópicos complexos
Oferece opções flexíveis para criar modelos de ML usando soluções do Google Cloud, atendendo a diversas necessidades
Ministrado pelo Google Cloud Training, reconhecido por sua expertise em tecnologias avançadas
Aborda a aplicação prática de IA e ML em processos de negócios, capacitando os alunos a impulsionar a inovação organizacional
Requisitos explícitos de pré-requisitos, indicando a necessidade de conhecimento prévio em IA e ML
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