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.
I have worked for more than 15 years in Java and J2EE and have recently developed an interest in Big Data technologies and Machine learning due to a big need at my workspace. I was referred here by a... Read More
This is one of the best of investments you can make with regards to career progression and growth in technological knowledge. I was pointed in this direction by a mentor in the IT world who I highly... Read More
Data is everywhere and constantly being generated around us. Using Big data tools, it is possible to ingest, process and make decisions based on data at high speed.
This big data project for beginners demonstrates how to use Apache Flume to ingest trading data from a source. While the default data flow is to archive all data to HDFS, Flume is also configured to channel some preconfigured symbols or trading pairs of interest to another processing server using Kafka. All the processed instructions are stored in a relational database (MySQL).
We will use following tools in this flume kafka project:
In this hadoop project, we are going to be continuing the series on data engineering by discussing and implementing various ways to solve the hadoop small file problem.
In this spark streaming project, we are going to build the backend of a IT job ad website by streaming data from twitter for analysis in spark.
The goal of this IoT project is to build an argument for generalized streaming architecture for reactive data ingestion based on a microservice architecture.