Bachelor of Data Science and Machine Learning Engineering
About this Specialization
In this Google Cloud Labs Specialization, you'll receive hands-on experience building and practicing skills in Big Query and Cloud Data Fusion. You will start learning the basics of Big Query, building and optimizing warehouses, and then get hands-on practice on the more advanced data integration features available in Cloud Data Fusion.
Learning will take place leveraging Google Cloud's Qwiklab platform where you will have the virtual environment and resources need to complete each lab.
This specialization is broken up into 4 courses comprised of a series of courses:
- BigQuery Basics for Data Analysts
- Building Advanced Codeless Pipelines on Cloud Data Fusion
- Data Science on Google Cloud
- Data Science on Google Cloud: Machine Learning
You will even be able to earn a Skills Badge
in one of these lab-based courses.
Applied Learning Project
This specialization leverages hands-on labs using our Qwiklabs platform. You can expect to gain practical hands-on experience with the concepts explained throughout each lab.
Learners will be able to practice:
- Creating dataset partitions that will reduce cost and improve query performance.
- Using macros in Data Fusion that introduce dynamic variables to plug-in configurations so that you can specify the variable substitutions at runtime.
- Building a reusable pipeline that reads data from Cloud Storage, performs data quality checks, and writes to Cloud Storage.
- Using Google Cloud Machine Learning and Tensor Flow to develop and evaluate prediction models using machine learning.
- Implementing logistic regression using a machine learning library for Apache Spark running on a Google Cloud Dataproc cluster to develop a model for data from a multivariable dataset. And much more!