The Machine Learning Engineer certification prepares professionals to design, build, and deploy machine learning models. It covers key topics like data preparation, algorithm selection, model evaluation, and scaling solutions. Ideal for those aiming to leverage machine learning to solve complex problems and drive data-driven decisions.
This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a mix of presentations, demos, and hands-on labs, participants gain an understanding of the Google Cloud Platform and its data processing and machine learning capabilities. The course highlights the ease, flexibility, and power of big data solutions available on Google Cloud Platform.
Target Audience
Data analysts, data scientists, and business analysts new to Google Cloud Platform.
Professionals responsible for designing data processing pipelines, maintaining machine learning and statistical models, querying datasets, and creating reports.
Executives and IT decision-makers evaluating Google Cloud Platform for data science use.
Prerequisites Participants should have:
Basic proficiency in SQL or a similar query language.
Experience with data modeling and ETL (Extract, Transform, Load) activities.
Programming experience in languages such as Python.
Familiarity with machine learning and/or statistics.
Learning Outcomes Participants will learn to:
Identify the purpose and value of key Big Data and Machine Learning products in Google Cloud Platform.
Use Cloud SQL and Cloud Dataproc to migrate MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
Perform interactive data analysis with BigQuery and Cloud Datalab.
Train and use neural networks with TensorFlow.
Utilize ML APIs.
Choose the appropriate data processing products on Google Cloud Platform.
This one-day instructor-led course introduces participants to the big data capabilities of Google Cloud Platform. Through a mix of presentations, demos, and hands-on labs, participants gain an understanding of the Google Cloud Platform and its data processing and machine learning capabilities. The course highlights the ease, flexibility, and power of big data solutions available on Google Cloud Platform.
Target Audience
Data analysts, data scientists, and business analysts new to Google Cloud Platform.
Professionals responsible for designing data processing pipelines, maintaining machine learning and statistical models, querying datasets, and creating reports.
Executives and IT decision-makers evaluating Google Cloud Platform for data science use.
Prerequisites Participants should have:
Basic proficiency in SQL or a similar query language.
Experience with data modeling and ETL (Extract, Transform, Load) activities.
Programming experience in languages such as Python.
Familiarity with machine learning and/or statistics.
Learning Outcomes Participants will learn to:
Identify the purpose and value of key Big Data and Machine Learning products in Google Cloud Platform.
Use Cloud SQL and Cloud Dataproc to migrate MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform.
Perform interactive data analysis with BigQuery and Cloud Datalab.
Train and use neural networks with TensorFlow.
Utilize ML APIs.
Choose the appropriate data processing products on Google Cloud Platform.
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Live Online Training (Duration : 8 Hours)
