Each project comes with 2-5 hours of micro-videos explaining the solution.
Get access to 50+ solved projects with iPython notebooks and datasets.
Add project experience to your Linkedin/Github profiles.
Most businesses seek to get reviews on their goods and services one way or another. It is a most basic way for the business to improve their efficiency and subsequently their bottom-line. Get the review is not only the issue, ability to extract and visualize analytics from review data is critical to business success.
In Apache Spark Project, we will use the yelp review dataset to analyze businesses and reviews over a period of time. Perhaps we will spot potential gaps in service delivery or see how business thrive in different scenarios.
Beyond processing this data, we will ingest the final output of our data processing in Elasticsearch and use the visualization tool in the ELK stack to visualize various kinds of ad-hoc reports from the data.
In this project, we will use complex scenarios to make Spark developers better to deal with the issues that come in the real world.
In this NoSQL project, we will use two NoSQL databases(HBase and MongoDB) to store Yelp business attributes and learn how to retrieve this data for processing or query.
In this project, we will evaluate and demonstrate how to handle unstructured data using Spark.