Welcome
IPN-Dharma AI Lab
This is an IPN CIC - DHARMA initiative to provide an Artificial Intelligence Laboratory to motivate researchers, professors and students to take advantage of the courses, resources and tools of the main technology platforms of the industry in the areas of Machine Learning, Data Science, Cloud Computing, Artificial Intelligence and Internet of Things with the purpose of generating a practical experience through a learning model between peers and by objectives.
Level 2: Contextual Knowledge
Hands-on Foundations for Data Science and Machine Learning with GC Labs
In this program, you'll receive hands-on experience building and practicing skills in BigQuery and Cloud Data Fusion. You will start learning the basics of BigQuery, building and optimizing warehouses, and then get hands-on practice on the more advanced data integration features available in Cloud Data Fusion.
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 plugin 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 TensorFlow 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.
Courses in this program
1) BigQuery Basics for Data Analysts
Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive collection of BigQuery Google Cloud Labs Series. BigQuery is Google's fully managed, NoOps, low-cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.
Estimated effort 5 hours
English language
2) Building Advanced Codeless Pipelines on Cloud Data Fusion
In this Google Cloud Labs Series, learners get hands-on practice on the more advanced data integration features available in Cloud Data Fusion, while sharing best practices to build more robust, reusable, dynamic pipelines. Learners get to try out the data lineage feature as well to derive interesting insights into their data’s history.
3) Data Science on Google Cloud
Activities in these self-paced labs are derived from the exercises from the book Data Science on Google Cloud Platform by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this first Google Cloud Labs Series, covering up through chapter 8, you are given the opportunity to practice all aspects of ingestion, preparation, processing, querying, exploring, and visualizing data sets using Google Cloud tools and services.
4) Data Science on Google Cloud: Machine Learning
Activities in these self-paced labs are derived from the exercises from the book Data Science on Google Cloud Platform by Valliappa Lakshmanan, published by O'Reilly Media, Inc. In this Google Cloud Labs Series, covering chapter 9 through the end of the book, you run full-fledged machine learning jobs with state-of-the-art tools and real-world data sets, all using Google Cloud tools and services.