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Smart Analytics, Machine Learning, and AI on Google Cloud

Google Cloud

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

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Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

Incorporating machine learning into data pipelines increases the ability to extract insights from data. This course covers ways machine learning can be included in data pipelines on Google Cloud. For little to no customization, this course covers AutoML. For more tailored machine learning capabilities, this course introduces Notebooks and BigQuery machine learning (BigQuery ML). Also, this course covers how to productionalize machine learning solutions by using Vertex AI.

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What's inside

Syllabus

Introduction
Introduction to Analytics and AI
Prebuilt ML Model APIs for Unstructured Data
Big Data Analytics with Notebooks
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Production ML Pipelines
Custom Model Building with SQL in BigQuery ML
Custom Model Building with AutoML
Summary
Course Resources

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Reinforces basic skills and knowledge
Covers standard skills used in the field of analytics
Instructors for this course are Google Cloud
Helps learners understand analytics and AI
Provides overview of tools from Google Cloud
Assumes some familiarity

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Activities

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Career center

Learners who complete Smart Analytics, Machine Learning, and AI on Google Cloud will develop knowledge and skills that may be useful to these careers:
Data Analyst
Data Analysts mine structured and unstructured data for actionable insights to help organizations make better decisions. They use the data gathered to make predictions and identify trends that can help organizations predict customer behavior. This course can help foster the skills you need to identify, collect, process, and analyze large datasets, making you a more valuable candidate in this field.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. They use their expertise in machine learning algorithms and software engineering to create models that can learn from data and make predictions. This course can help you build the skills you need to design and implement machine learning models, making you a more competitive candidate for this role.
Data Scientist
Data Scientists use models and algorithms to extract insights from data that can help make predictions about the future. They use machine learning, statistics, and other forms of advanced data analysis to help organizations leverage data more effectively. This course can help you learn the fundamentals of machine learning and how to apply it in practical situations, making you a more competitive candidate in this field. While this course does not cover data science in its entirety, it can help you build a foundation or add to your credentials.
Model Builder
Model Builders construct mathematical or statistical models to help businesses and organizations analyze performance and forecast future trends. This course can teach you the basics of model building, including how to collect data, prepare it for analysis, and build and evaluate models.
Statistician
Statisticians use statistical methods to collect, analyze, and interpret data. They work in a variety of industries, including finance, healthcare, and marketing. This course can teach you the fundamentals of statistics, which can help you succeed in this role.
Data Architect
Data Architects design and manage data systems. They work with stakeholders to understand business needs, and then design and implement data systems that meet those needs. This course can teach you the fundamentals of data architecture, which can help you succeed in this role.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to help organizations make better decisions. They work with stakeholders to identify business needs, and then use data to develop solutions that meet those needs. This course can teach you the fundamentals of operations research, which can help you succeed in this role.
Risk Analyst
Risk Analysts use data and analytical tools to help organizations identify and manage risks. They work with stakeholders to identify risks, and then use data to develop strategies to mitigate those risks. This course can teach you the fundamentals of risk analysis, which can help you succeed in this role.
Data Engineer
Data Engineers build and maintain the infrastructure that processes and stores data. They use their expertise in data management and architecture to ensure that data is available, reliable, and secure. This course can help teach you how to create and manage data pipelines, which is an essential skill for Data Engineers.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical methods to analyze financial data. They work with stakeholders to identify investment opportunities, and then use data to develop models that can help make investment decisions. This course can teach you the fundamentals of quantitative analysis, which can help you succeed in this role.
Actuary
Actuaries use mathematical and statistical methods to assess and manage financial risks. They work with stakeholders to identify financial risks, and then use data to develop models that can help manage those risks. This course can teach you the fundamentals of actuarial science, which can help you succeed in this role.
Credit Analyst
Credit Analysts use data and analytical tools to help organizations make lending decisions. They work with stakeholders to identify credit risks, and then use data to develop models that can help make lending decisions. This course can teach you the fundamentals of credit analysis, which can help you succeed in this role.
Insurance Analyst
Insurance Analysts use data and analytical tools to help organizations assess and manage insurance risks. They work with stakeholders to identify insurance risks, and then use data to develop models that can help manage those risks. This course can teach you the fundamentals of insurance analysis, which can help you succeed in this role.
Fraud Analyst
Fraud Analysts use data and analytical tools to help organizations identify and prevent fraud. They work with stakeholders to identify fraud risks, and then use data to develop strategies to mitigate those risks. This course can teach you the fundamentals of fraud analysis, which can help you succeed in this role.
Business Analyst
Business Analysts use data and analytical tools to help organizations make better decisions. They work with stakeholders to identify business needs, and then use data to develop solutions that meet those needs. This course can teach you the fundamentals of data analysis, which can help you succeed in this role.

Reading list

We've selected six 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 Smart Analytics, Machine Learning, and AI on Google Cloud.
Starts with a solid foundation in the fundamentals of machine learning before moving on to more advanced topics like deep learning and text processing. It's a great resource for anyone who wants to go deeper into machine learning, especially if you're interested in using scikit-learn, Keras, or TensorFlow.
Hands-on guide to machine learning, with lots of practical examples and code snippets. It's a great resource for anyone who wants to get started with machine learning quickly and easily.
Uses engaging visuals to explain the concepts of deep learning in a clear and concise way. It's a great resource for anyone who wants to learn about deep learning without getting bogged down in the math.
This comprehensive book covers a wide range of data mining topics, from data cleaning and preprocessing to machine learning and data visualization. It's a great resource for anyone who wants to learn about data mining in depth.
Aimed at people with no programming experience, this book teaches the basics of Python programming in a fun and engaging way. It's a great resource for anyone who wants to learn how to automate tasks and write simple Python scripts.

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