Google Cloud Big Data and ML Fundamentals

What's inside

Syllabus

Introduzione al corso

Questa sezione accoglie gli studenti al corso Big Data and Machine Learning Fundamentals e fornisce una panoramica della struttura e degli obiettivi del corso.

Big data e machine learning su Google Cloud

Questa sezione illustra i componenti chiave dell'infrastruttura di Google Cloud. È qui che presentiamo molti dei servizi e prodotti per big data e di machine learning che supportano il ciclo di vita dai dati all'IA su Google Cloud.

Data engineering per i flussi di dati

Questa sezione illustra la soluzione di Google Cloud per la gestione dei dati in modalità flusso. Prende in esame una pipeline di dati end-to-end che include l'importazione con Pub/Sub, l'elaborazione con Dataflow e la visualizzazione tramite Looker e Data Studio.

Big data con BigQuery

Questa sezione introduce gli studenti a BigQuery, il data warehouse serverless e completamente gestito di Google. Inoltre, esplora BigQuery ML e i processi e i comandi chiave utilizzati per creare modelli di machine learning personalizzati.

Opzioni di machine learning su Google Cloud

Questa sezione esplora quattro diverse opzioni per la creazione di soluzioni di machine learning su Google Cloud. Inoltre, introduce Vertex AI, la piattaforma unificata di Google per la creazione e la gestione del ciclo di vita dei progetti di ML.

Flusso di lavoro di machine learning con Vertex AI

Questa sezione illustra le tre fasi chiave del flusso di lavoro di machine learning in Vertex AI: preparazione dei dati, addestramento del modello e preparazione del modello. Gli studenti hanno l'opportunità di esercitarsi nella creazione di un modello di machine learning con AutoML.

Riepilogo del corso

Questa sezione ripercorre gli argomenti trattati nel corso e fornisce risorse aggiuntive per ulteriori approfondimenti.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Esplora i prodotti e servizi di big data e machine learning di Google Cloud che supportano il ciclo di vita dai dati all'IA

Fornisce una panoramica dei processi, delle sfide e dei vantaggi della creazione di una pipeline di big data e di modelli di machine learning con Vertex AI su Google Cloud

Illustra la soluzione di Google Cloud per la gestione dei dati in modalità flusso, esaminando una pipeline di dati end-to-end

Introduce BigQuery, il data warehouse serverless e completamente gestito di Google e approfondisce BigQuery ML

Esplora le quattro diverse opzioni per creare soluzioni di machine learning su Google Cloud, introducendo Vertex AI, la piattaforma unificata per la creazione e la gestione del ciclo di vita dei progetti di ML

Illustra le tre fasi chiave del flusso di lavoro di machine learning in Vertex AI: preparazione dei dati, addestramento del modello e preparazione del modello

Career center

Learners who complete Google Cloud Big Data and ML Fundamentals - Italiano will develop knowledge and skills that may be useful to these careers:

Data Analyst

Data Analysts play a key role in bridging the gap between data and business understanding. They use their expertise in statistics, data mining, and programming to analyze data and extract meaningful insights. This course provides a foundation in big data and machine learning tools such as Google Cloud's BigQuery and Vertex AI, which are essential for Data Analysts to perform their tasks effectively. By gaining proficiency in these tools, learners can enhance their ability to clean, organize, and analyze large datasets, leading to more accurate and valuable insights that can inform business decisions.

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Machine Learning Engineer

Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They use their knowledge of algorithms, data structures, and programming to build models that can learn from data and make predictions. This course introduces learners to the fundamentals of machine learning, including topics such as data preparation, model training, and model evaluation. It also provides hands-on experience with Google Cloud's Vertex AI platform, which streamlines the machine learning development process. With this foundation, learners can pursue a career as a Machine Learning Engineer, where they can leverage their skills to create innovative solutions to real-world problems.

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Big Data Architect

Big Data Architects design and implement data architectures that can handle the storage, processing, and analysis of large datasets. They work closely with data engineers and data scientists to ensure that the data infrastructure is scalable, reliable, and secure. This course provides an overview of big data technologies, such as Google Cloud's BigQuery and Cloud Bigtable, and explores the challenges and best practices associated with managing big data. By understanding the principles of big data architecture, learners can develop the skills necessary to design and implement data solutions that meet the needs of their organization.

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Data Engineer

Data Engineers are responsible for building and maintaining the data pipelines that collect, transform, and store data. They use their expertise in data integration, data modeling, and data warehousing to ensure that data is available and accessible to users in a timely and reliable manner. This course provides a foundation in big data technologies, such as Google Cloud's BigQuery and Dataflow, and explores the challenges and best practices associated with data engineering. By gaining proficiency in these tools and techniques, learners can develop the skills necessary to succeed as Data Engineers and contribute to the success of their organization's data-driven initiatives.

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Data Scientist

Data Scientists use their expertise in statistics, machine learning, and programming to extract insights from data. They work closely with data engineers and business stakeholders to identify problems, develop solutions, and communicate insights. This course provides a foundation in big data and machine learning tools such as Google Cloud's BigQuery and Vertex AI, which are essential for Data Scientists to perform their tasks effectively. By gaining proficiency in these tools, learners can enhance their ability to analyze data, build predictive models, and develop data-driven solutions to business problems.

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Business Analyst

Business Analysts use data to identify and solve business problems. They work closely with stakeholders to understand their needs and develop solutions that meet those needs. This course provides a foundation in big data and machine learning tools such as Google Cloud's BigQuery and Vertex AI, which can be used to analyze data and extract meaningful insights. By gaining proficiency in these tools, Business Analysts can enhance their ability to make data-driven decisions and develop innovative solutions to business problems.

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Software Engineer

Software Engineers design, develop, and maintain software applications. They use their knowledge of programming languages and software engineering principles to create software that meets the needs of users. This course provides a foundation in big data and machine learning concepts, which are increasingly being used in software development. By gaining proficiency in these concepts, Software Engineers can enhance their ability to develop innovative software applications that leverage the power of data.

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Product Manager

Product Managers are responsible for the development and launch of new products. They work closely with engineers, designers, and marketing teams to ensure that products meet the needs of users. This course provides a foundation in big data and machine learning concepts, which can be used to understand user behavior and develop data-driven products. By gaining proficiency in these concepts, Product Managers can enhance their ability to develop and launch successful products.

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Marketing Analyst

Marketing Analysts use data to understand customer behavior and develop marketing campaigns. They work closely with marketing teams to identify target audiences, develop marketing strategies, and measure the effectiveness of marketing campaigns. This course provides a foundation in big data and machine learning tools such as Google Cloud's BigQuery and Vertex AI, which can be used to analyze data and extract meaningful insights. By gaining proficiency in these tools, Marketing Analysts can enhance their ability to develop and execute data-driven marketing campaigns.

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Financial Analyst

Financial Analysts use data to analyze financial markets and make investment recommendations. They work closely with clients to understand their investment goals and develop investment strategies. This course provides a foundation in big data and machine learning concepts, which can be used to analyze financial data and develop data-driven investment strategies. By gaining proficiency in these concepts, Financial Analysts can enhance their ability to make informed investment decisions.

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Operations Research Analyst

Operations Research Analysts use data to analyze and improve business operations. They work closely with managers to identify problems, develop solutions, and implement improvements. This course provides a foundation in big data and machine learning concepts, which can be used to analyze data and develop data-driven solutions to business problems. By gaining proficiency in these concepts, Operations Research Analysts can enhance their ability to improve the efficiency and effectiveness of business operations.

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Management Consultant

Management Consultants advise businesses on how to improve their performance. They work closely with clients to identify problems, develop solutions, and implement improvements. This course provides a foundation in big data and machine learning concepts, which can be used to analyze data and develop data-driven solutions to business problems. By gaining proficiency in these concepts, Management Consultants can enhance their ability to provide valuable advice to their clients.

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Data Visualization Specialist

Data Visualization Specialists use data to create visualizations that communicate insights to stakeholders. They work closely with data scientists and business analysts to develop visualizations that are clear, concise, and actionable. This course provides a foundation in big data and machine learning tools such as Google Cloud's BigQuery and Data Studio, which can be used to create interactive data visualizations. By gaining proficiency in these tools, Data Visualization Specialists can enhance their ability to communicate data-driven insights to a wide range of audiences.

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Database Administrator

Database Administrators maintain and manage databases. They ensure that databases are running smoothly and that data is secure. This course provides a foundation in big data technologies, such as Google Cloud's BigQuery and Cloud SQL, and explores the challenges and best practices associated with managing big data. By gaining proficiency in these technologies, Database Administrators can enhance their ability to manage and maintain data in a scalable, reliable, and secure manner.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course provides a foundation in big data and machine learning technologies, such as Google Cloud's BigQuery and Vertex AI, which can be used to detect and prevent security breaches. By gaining proficiency in these technologies, Information Security Analysts can enhance their ability to protect organizations from cyber threats.

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