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Google Cloud
In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
Read more
In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
Read more
In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
In this course, we define what machine learning is and how it can benefit your business. You'll see a few demos of ML in action and learn key ML terms like instances, features, and labels. In the interactive labs, you will practice invoking the pretrained ML APIs available as well as build your own Machine Learning models using just SQL with BigQuery ML.
Register for this course and see more details by visiting:
OpenCourser.com/course/uqpsw1/applying
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What's inside
Syllabus
Introduction
Introduction to Machine Learning
Pre-trained ML APIs
Creating ML Datasets in BigQuery
Read more
Syllabus
Introduction
Introduction to Machine Learning
Pre-trained ML APIs
Creating ML Datasets in BigQuery
Read more
Creating ML Models in BigQuery
End of Course Recap
Course Resources
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Strengthens existing foundation for intermediate learners
Covers fundamental concepts required for beginners
Demonstrates practical applications of concepts through hands-on labs
Taught by experienced instructors from Google Cloud
Leverages BigQuery ML for practical implementation
Provides a comprehensive introduction to machine learning
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Save Applying Machine Learning to your Data with Google Cloud 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 Applying Machine Learning to your Data with Google Cloud with these
activities:
Practice applying machine learning algorithms in SQL
Show steps
Gain hands-on experience applying machine learning algorithms in SQL with BigQuery ML.
Browse courses on
SQL
Show steps
-
Set up a BigQuery sandbox
-
Load sample data into BigQuery
-
Build and train machine learning models using BigQuery ML
-
Evaluate model performance
Form a study group with classmates
Show steps
Engage in collaborative learning and knowledge sharing with fellow students.
Show steps
-
Find a group of classmates with diverse skills and perspectives
-
Set regular meeting times and establish clear goals
-
Discuss course materials, share insights, and work on assignments together
Connect with machine learning experts
Show steps
Seek guidance and advice from experienced machine learning professionals.
Show steps
-
Attend industry events and meetups
-
Join online communities and forums
-
Reach out to professors or researchers in the field
Three other activities
Expand to see all activities and additional details
Show all six activities
Build a simple machine learning application
Show steps
Apply your machine learning skills to build a practical application that addresses a real-world problem.
Browse courses on
Predictive Modeling
Show steps
-
Define the problem and gather data
-
Preprocess and explore the data
-
Build and train a machine learning model
-
Deploy the application
Share your machine learning insights
Show steps
Consolidate your knowledge by creating content that explains machine learning concepts and applications.
Show steps
-
Write a blog post or article
-
Record a podcast or video tutorial
-
Create an infographic or presentation
Explore advanced machine learning topics
Show steps
Expand your knowledge by delving into specialized machine learning topics beyond the course curriculum.
Show steps
-
Identify areas for further exploration
-
Find reputable online courses or tutorials
-
Dedicate time to studying and practicing
Practice applying machine learning algorithms in SQL
Show steps
Gain hands-on experience applying machine learning algorithms in SQL with BigQuery ML.
Browse courses on
SQL
Show steps
Show steps
Show steps
- Set up a BigQuery sandbox
- Load sample data into BigQuery
- Build and train machine learning models using BigQuery ML
- Evaluate model performance
Form a study group with classmates
Show steps
Engage in collaborative learning and knowledge sharing with fellow students.
Show steps
Show steps
Show steps
- Find a group of classmates with diverse skills and perspectives
- Set regular meeting times and establish clear goals
- Discuss course materials, share insights, and work on assignments together
Connect with machine learning experts
Show steps
Seek guidance and advice from experienced machine learning professionals.
Show steps
Show steps
Show steps
- Attend industry events and meetups
- Join online communities and forums
- Reach out to professors or researchers in the field
Three other activities
Expand to see all activities and additional details
Show all six activities
Build a simple machine learning application
Show steps
Apply your machine learning skills to build a practical application that addresses a real-world problem.
Browse courses on
Predictive Modeling
Show steps
Show steps
Show steps
- Define the problem and gather data
- Preprocess and explore the data
- Build and train a machine learning model
- Deploy the application
Share your machine learning insights
Show steps
Consolidate your knowledge by creating content that explains machine learning concepts and applications.
Show steps
Show steps
Show steps
- Write a blog post or article
- Record a podcast or video tutorial
- Create an infographic or presentation
Explore advanced machine learning topics
Show steps
Expand your knowledge by delving into specialized machine learning topics beyond the course curriculum.
Show steps
Show steps
Show steps
- Identify areas for further exploration
- Find reputable online courses or tutorials
- Dedicate time to studying and practicing
Career center
Learners who complete Applying Machine Learning to your Data with Google Cloud will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use their expertise in machine learning to analyze data and build predictive models. The course ‘Applying Machine Learning to your Data with Google Cloud’ will be useful in your journey toward becoming a Data Scientist. It will introduce you to core machine learning concepts, provide you with hands-on experience in building and deploying machine learning models using Google Cloud, and help you understand how to evaluate and interpret the results of your models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for the development and maintenance of machine learning models. The course 'Applying Machine Learning to your Data with Google Cloud' will help you build a strong foundation for a career as a Machine Learning Engineer. It will provide you with a comprehensive understanding of machine learning concepts and techniques, and train you in the use of popular machine learning tools and frameworks.
Data Analyst
Data Analyst
Data Analysts use data to solve business problems. The course ‘Applying Machine Learning to your Data with Google Cloud’ may help you as a Data Analyst by providing you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills are in high demand in today’s data-driven business world.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. The course ‘Applying Machine Learning to your Data with Google Cloud’ may help you as a Business Analyst, as it will provide you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills can help you to make better decisions and to improve the efficiency of your business.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. The course ‘Applying Machine Learning to your Data with Google Cloud’ may help you as a Software Engineer, as it will provide you with the skills to build and deploy machine learning models. These skills are in high demand in today’s software industry.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. The course ‘Applying Machine Learning to your Data with Google Cloud’ can be helpful for Product Managers, as it will provide you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills can help you to make better decisions about your products and to improve the user experience.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for the development and execution of marketing campaigns. The course ‘Applying Machine Learning to your Data with Google Cloud’ may help you as a Marketing Manager, as it will provide you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills can help you to target your marketing campaigns more effectively and to improve your ROI.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment decisions. The course ‘Applying Machine Learning to your Data with Google Cloud’ may help you as a Financial Analyst, as it will provide you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills can help you to make better investment decisions and to improve your returns.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to solve business problems. The course ‘Applying Machine Learning to your Data with Google Cloud’ may help you as an Operations Research Analyst, as it will provide you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills can help you to make better decisions and to improve the efficiency of your business.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data pipelines. The course ‘Applying Machine Learning to your Data with Google Cloud’ may be useful for Data Engineers, as it will provide you with the skills to build and deploy machine learning models. These skills are in high demand in today’s data-driven business world.
Database Administrator
Database Administrator
Database Administrators are responsible for the management and maintenance of databases. The course ‘Applying Machine Learning to your Data with Google Cloud’ may be useful for Database Administrators, as it will provide you with the skills to build and deploy machine learning models. These skills can help you to improve the performance and security of your databases.
Systems Analyst
Systems Analyst
Systems Analysts design, develop, and implement computer systems. The course ‘Applying Machine Learning to your Data with Google Cloud’ may be useful for Systems Analysts, as it will provide you with the skills to build and deploy machine learning models. These skills can help you to improve the efficiency and effectiveness of your computer systems.
IT Project Manager
IT Project Manager
IT Project Managers plan, execute, and close IT projects. The course ‘Applying Machine Learning to your Data with Google Cloud’ may be useful for IT Project Managers, as it will provide you with the skills to build and deploy machine learning models. These skills can help you to improve the efficiency and effectiveness of your IT projects.
Business Intelligence Analyst
Business Intelligence Analyst
Business Intelligence Analysts use data to make business decisions. The course ‘Applying Machine Learning to your Data with Google Cloud’ may be useful for Business Intelligence Analysts, as it will provide you with the skills to collect, clean, and analyze data, and to build and deploy machine learning models. These skills can help you to make better decisions and to improve the performance of your business.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists use data to create visual representations of data. The course ‘Applying Machine Learning to your Data with Google Cloud’ may be useful for Data Visualization Specialists, as it will provide you with the skills to build and deploy machine learning models. These skills can help you to create more effective and informative data visualizations.
For more career information including salaries, visit:
OpenCourser.com/course/uqpsw1/applying
Reading list
We've selected ten 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
Applying Machine Learning to your Data with Google Cloud.
Provides a practical introduction to machine learning using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers a wide range of topics, including data preprocessing, model selection, and deep learning.
Save
Comprehensive reference on deep learning, covering topics such as neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn about the latest advances in deep learning.
Provides an overview of data science and machine learning. It covers topics such as data collection, data cleaning, and data analysis. It valuable resource for anyone who wants to learn about the basics of data science and machine learning.
Provides a comprehensive overview of machine learning using the R programming language. It covers a wide range of topics, including data preprocessing, model selection, and model evaluation.
Classic reference on statistical learning. It covers a wide range of topics, including linear regression, logistic regression, and support vector machines. It valuable resource for anyone who wants to learn about the mathematical foundations of machine learning.
Comprehensive reference on pattern recognition and machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning. It valuable resource for anyone who wants to learn about the mathematical foundations of machine learning.
Comprehensive reference on machine learning from a probabilistic perspective. It covers a wide range of topics, including Bayesian inference, graphical models, and reinforcement learning. It valuable resource for anyone who wants to learn about the mathematical foundations of machine learning.
Provides a practical introduction to machine learning using Python. It covers a wide range of topics, including data preprocessing, model selection, and model evaluation. It valuable resource for anyone who wants to learn about the basics of data science and machine learning.
Provides a practical introduction to deep learning using Python. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone who wants to learn about the basics of data science and machine learning.
Comprehensive reference on reinforcement learning. It covers a wide range of topics, including Markov decision processes, value iteration, and policy gradient methods. It valuable resource for anyone who wants to learn about the mathematical foundations of reinforcement learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/uqpsw1/applying
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Time
67 hours
Level
Introductory
Via
Pluralsight
Instructor
Google Cloud
Language
English
Good to know
Strengthens existing foundation for intermediate learners
Covers fundamental concepts required for beginners
Demonstrates practical applications of concepts through hands-on labs
Taught by experienced instructors from Google Cloud
Leverages BigQuery ML for practical implementation
Provides a comprehensive introduction to machine learning
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