Cloud Platform CPB100 - Google Cloud Platform Big Data & Machine-Learning Fundamentals
This 1-day instructor-led class introduces participants to the Big Data & Machine Learning capabilities of Google Cloud Platform. It provides a quick overview of the Google Cloud Platform and a deep dive into the data processing capabilities that will serve as a catalyst to forward-thinking innovation.
Participants will be definitively positioned as positive drivers of workplace technology innovation, in the rapidly arriving age of Machine-Learning. Students will also benefit from gaining insights into overseeing, and making use of, Big Data and large swaths of information that need parsing - the benefits of which, can be endless.
Participants will gain knowledge of creating, automating, optimizing, and maintaining data analysis and Machine-Learning workflow.
- Participants will benefit from a deeper understanding of how to use the interconnectedness of the Google Cloud Platform, being readily able to identify the correct data processing tools and functions for the task ahead!
Overview of Learning Objectives
At the end of this 1-day course, participants will be able to:
- Identify the purpose and value of the key Big Data and Machine Learning products in the Google Cloud Platform
- Use CloudSQL and Cloud Dataproc to migrate existing MySQL and Hadoop/Pig/Spark/Hive workloads to Google Cloud Platform
- Employ BigQuery and Cloud Datalab to carry out interactive data analysis
- Choose between Cloud SQL, BigTable and Datastore
- Train and use a neural network using TensorFlow
- Choose between different data processing products on the Google Cloud Platform
Who Should Attend
This class is intended for Data analysts, Data scientists, Business analysts, and Adept IT Professionals. It is also suitable for IT decision makers evaluating Google Cloud Platform for use by data scientists.
This class is for people who do the following with big data:
- Extracting, Loading, Transforming, cleaning, and validating data for use in analytics
- Designing pipelines and architectures for data processing
- Creating and maintaining machine learning and statistical models
- Querying datasets, visualizing query results and creating reports
Before attending this course, participants should have roughly one (1) year of experience with one or more of the following:
- A common query language such as SQL
- Extract, transform, load activities
- Data modeling
- Machine learning and/or statistics
- Programming in Python
* Outline Attached Content (Class Times)
- Public Open Enrollment Training Courses - Course hours are 9am-4pm
- Public Open Enrollment Training hours scheduled at Branch locations may vary.
- Public Open Enrollment Online Courses - Course hours are 10am-5pm EST
We have training centers in Atlanta, Houston, Chicago, Denver, San Diego and Washington DC. We also have the option of live instructor lead online offerings for our courses. Our network of rental facilities is also an option for most of our high demand classes. If coming to a rental facility, please double-check the location of your class with our office to make sure you get to the right location.
As an option for customers needing completely customizable training we offer private onsite training and Individual instructor consulting sessions. To inquire about custom training please fill out our private training request form.
Please see our Enrollment Page (http://www.ledet.com/enroll) for our enrollment form.
Our goal is to make sure your class meets your objectives, not ours. Therefore, all of our outlines are treated as guides to help steer the workshop. This outline does not guarantee that all the topics listed will be covered in the time allowed. The amount of material covered is based on the skill level of the student audience. We may change or alter course topics to best suit the classroom situation.
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