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Google Cloud Training
This is a self-paced lab that takes place in the Google Cloud console. In this lab, you will explore millions of New York City yellow taxi cab trips available in a BigQuery Public Dataset, create an ML model inside of BigQuery to predict the fare, and evaluate the performance of your model to make predictions.
Register for this course and see more details by visiting:
OpenCourser.com/course/xjl3f1/predict
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What's inside
Syllabus
Predict Taxi Fare with a BigQuery ML Forecasting Model
In this lab you will explore millions of New York City yellow taxi cab trips available in a BigQuery Public Dataset, create a ML model inside of BigQuery to predict the fare, and evaluate the performance of your model to make predictions.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides exposure to industry-standard forecasting methods and tools used by data scientists and engineers globally
Highly accessible offering from Google Cloud Training, known for world-renowned courses and programs in data science and machine learning
Suitable for learners with prior experience in data science, machine learning, or related disciplines
Involves hands-on practice, offering learners a practical understanding of ML model development and evaluation in BigQuery
Requires prior knowledge of BigQuery, SQL, and Python, which may not be suitable for complete beginners in data science
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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 Predict Taxi Fare with a BigQuery ML Forecasting Model with these
activities:
Review and organize course materials
Show steps
Organize and review course materials to improve retention and access to key concepts.
Browse courses on
Note-Taking
Show steps
-
Gather all course materials (notes, assignments, quizzes)
-
Organize the materials into a logical structure
-
Review the materials regularly
Explore additional BigQuery ML tutorials
Show steps
Follow online tutorials to expand knowledge of BigQuery ML capabilities and best practices.
Browse courses on
Machine Learning
Show steps
-
Identify relevant tutorials
-
Follow the tutorials and complete the exercises
-
Apply the techniques learned to your own projects
Form a study group for deeper understanding
Show steps
Engage in peer discussions and collaborative problem-solving to enhance understanding of course concepts.
Browse courses on
Collaborative Learning
Show steps
-
Find a few classmates to form a study group
-
Meet regularly to discuss course materials
-
Work together to solve problems and clarify concepts
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice ML modeling with BigQuery
Show steps
Practice building and evaluating ML models using BigQuery ML to solidify understanding of the concepts covered in the course.
Browse courses on
Machine Learning
Show steps
-
Load a dataset into BigQuery
-
Create a BigQuery ML model
-
Evaluate the performance of the model
-
Improve the model by tuning hyperparameters
-
Deploy the model for predictions
Compile a collection of useful BigQuery ML resources
Show steps
Gather and organize resources related to BigQuery ML to serve as a valuable reference for future use.
Browse courses on
BigQuery ML
Show steps
-
Identify and gather relevant resources (e.g., documentation, blog posts, videos)
-
Organize the resources into a structured format (e.g., cheat sheet, annotated bibliography)
-
Share the compilation with others
Develop a presentation on ML forecasting models
Show steps
Create a presentation to demonstrate understanding of ML forecasting models, their applications, and their limitations.
Browse courses on
Machine Learning
Show steps
-
Research different types of ML forecasting models
-
Choose a specific model and explain its strengths and weaknesses
-
Gather data and train the model
-
Evaluate the performance of the model
-
Prepare and deliver the presentation
Identify a mentor in the field of ML
Show steps
Seek guidance and support from an experienced ML professional to gain insights and enhance career prospects.
Browse courses on
Mentorship
Show steps
-
Attend industry events and meetups to network
-
Reach out to potential mentors via LinkedIn or email
-
Build a relationship with your mentor
Review and organize course materials
Show steps
Organize and review course materials to improve retention and access to key concepts.
Browse courses on
Note-Taking
Show steps
Show steps
Show steps
- Gather all course materials (notes, assignments, quizzes)
- Organize the materials into a logical structure
- Review the materials regularly
Explore additional BigQuery ML tutorials
Show steps
Follow online tutorials to expand knowledge of BigQuery ML capabilities and best practices.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Identify relevant tutorials
- Follow the tutorials and complete the exercises
- Apply the techniques learned to your own projects
Form a study group for deeper understanding
Show steps
Engage in peer discussions and collaborative problem-solving to enhance understanding of course concepts.
Browse courses on
Collaborative Learning
Show steps
Show steps
Show steps
- Find a few classmates to form a study group
- Meet regularly to discuss course materials
- Work together to solve problems and clarify concepts
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice ML modeling with BigQuery
Show steps
Practice building and evaluating ML models using BigQuery ML to solidify understanding of the concepts covered in the course.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Load a dataset into BigQuery
- Create a BigQuery ML model
- Evaluate the performance of the model
- Improve the model by tuning hyperparameters
- Deploy the model for predictions
Compile a collection of useful BigQuery ML resources
Show steps
Gather and organize resources related to BigQuery ML to serve as a valuable reference for future use.
Browse courses on
BigQuery ML
Show steps
Show steps
Show steps
- Identify and gather relevant resources (e.g., documentation, blog posts, videos)
- Organize the resources into a structured format (e.g., cheat sheet, annotated bibliography)
- Share the compilation with others
Develop a presentation on ML forecasting models
Show steps
Create a presentation to demonstrate understanding of ML forecasting models, their applications, and their limitations.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Research different types of ML forecasting models
- Choose a specific model and explain its strengths and weaknesses
- Gather data and train the model
- Evaluate the performance of the model
- Prepare and deliver the presentation
Identify a mentor in the field of ML
Show steps
Seek guidance and support from an experienced ML professional to gain insights and enhance career prospects.
Browse courses on
Mentorship
Show steps
Show steps
Show steps
- Attend industry events and meetups to network
- Reach out to potential mentors via LinkedIn or email
- Build a relationship with your mentor
Career center
Learners who complete Predict Taxi Fare with a BigQuery ML Forecasting Model will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist uses scientific methods to extract knowledge and insights from data. They use their skills to develop and implement predictive models that can help businesses make better decisions. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of data science.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. They use their skills to create models that can learn from data and make predictions. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of machine learning engineering.
Business Analyst
Business Analyst
A Business Analyst uses data to help businesses make better decisions. They use their skills to identify problems and develop solutions that can help businesses improve their performance. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of business analysis.
Statistician
Statistician
A Statistician uses data to make informed decisions. They use their skills to design and conduct studies, analyze data, and draw conclusions. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of statistics.
Data Architect
Data Architect
A Data Architect designs and manages data systems. They use their skills to ensure that data is organized and accessible to those who need it. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of data architecture.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. They use their skills to create software that meets the needs of users. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of software engineering.
Data Analyst
Data Analyst
A Data Analyst collects, interprets, and transforms data into meaningful insights. They use their skills to make data-driven recommendations for businesses. This course can help develop the data analysis skills needed for this role. It teaches users how to access, explore, and analyze data to extract and generate actionable insights. This course would be particularly helpful for those interested in entering the field of data analytics.
Database Administrator
Database Administrator
A Database Administrator manages and maintains databases. They use their skills to ensure that data is stored and retrieved efficiently. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of database administration.
Information Security Analyst
Information Security Analyst
An Information Security Analyst protects computer systems and networks from unauthorized access. They use their skills to identify and mitigate security risks. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of information security.
Financial Analyst
Financial Analyst
A Financial Analyst uses financial data to make recommendations about investments. They use their skills to develop models that can help investors make better decisions. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of financial analysis.
Data Engineer
Data Engineer
A Data Engineer designs, builds, and maintains data systems. They use their skills to ensure that data is available and accessible to those who need it. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of data engineering.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical techniques to analyze financial data. They use their skills to develop models that can help investors make better decisions. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of quantitative finance.
Actuary
Actuary
An Actuary uses mathematical and statistical techniques to assess and manage risk. They use their skills to develop models that can help businesses make better decisions about risk. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of actuarial science.
Cloud Engineer
Cloud Engineer
A Cloud Engineer designs and manages cloud computing systems. They use their skills to ensure that cloud-based applications and services are available and scalable. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of cloud engineering.
Systems Engineer
Systems Engineer
A Systems Engineer designs and manages complex systems. They use their skills to ensure that systems are reliable and efficient. This course can help build a foundation for this role. It teaches users how to use machine learning algorithms to make predictions. This course would be particularly useful for those interested in entering the field of systems engineering.
For more career information including salaries, visit:
OpenCourser.com/course/xjl3f1/predict
Reading list
We've selected 11 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
Predict Taxi Fare with a BigQuery ML Forecasting Model.
A classic reference on time series analysis and forecasting, providing a strong theoretical foundation.
A guide to using SQL for data science tasks, including data cleaning, transformation, and analysis.
An introductory guide to machine learning, suitable for those with little to no prior knowledge.
Save
A non-technical guide to data science for business leaders, providing an understanding of its concepts and applications.
Provides a practical introduction to data science for business professionals. It covers a wide range of topics, including data analysis, machine learning, and data visualization.
Save
Provides a comprehensive overview of data mining with R. It covers a wide range of topics, including data preprocessing, feature engineering, and model evaluation.
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Provides a gentle introduction to data science. It covers a wide range of topics, including data analysis, machine learning, and data visualization.
Provides a practical introduction to machine learning with Python. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
Provides a comprehensive overview of machine learning with R. It covers a wide range of topics, including data preprocessing, feature engineering, and model evaluation.
Provides a practical introduction to machine learning. It covers a wide range of topics, including supervised learning, unsupervised learning, and reinforcement learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/xjl3f1/predict
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Effort
1 hour
Level
Intermediate
Via
Coursera
Institution
Google Cloud
Instructor
Google Cloud Training
Language
English
Good to know
Provides exposure to industry-standard forecasting methods and tools used by data scientists and engineers globally
Highly accessible offering from Google Cloud Training, known for world-renowned courses and programs in data science and machine learning
Suitable for learners with prior experience in data science, machine learning, or related disciplines
Involves hands-on practice, offering learners a practical understanding of ML model development and evaluation in BigQuery
Requires prior knowledge of BigQuery, SQL, and Python, which may not be suitable for complete beginners in data science
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