Following our bigdata.ro Spark (completed) and Druid+Superset working group (ongoing) , we are now opening registration on a new working group with the topic: Machine Learning with Decision Trees and Random Forest.

Timeline: September 27th – December 4th (1 online meeting/ 2 weeks, 5 meetings)
Predefined topic: Solving a regression/classification problem using decision trees and random forest. 
We will use: Python, Jupyter notebooks, sklearn, dtreeviz for tree visualisation, matplotlib/seaborn for data visualization

The group’s purpose is to go through the entire ML flow while learning about decision trees and random forest.
You can check out the group’s description and register here.

Open Course: Understanding Big Data Architecture E2E (Use case including Cassandra + Kafka + Spark + Zeppelin)  
Timeline & Duration: July 27th – August 14th, 6 X 4 hours online sessions, during 3 weeks (2 sessions/week, Monday + Thursday) . An online setup will be available for exercises/hands-on sessions for the duration of the course. 
Main trainer: Valentina Crisan
Location: Online (Zoom)
Price: 250 EUR 
Pre-requisites: knowledge of distributed systems, Hadoop ecosystem (HDFS, MapReduce), know a bit of SQL.

More details and registration here.

Learning a new solution or building an architecture for a specific use case is never easy, especially when you are trying to embark alone on such an endeavour – thus in 2020 bigdata.ro started a new way of learning specific big data solutions/use cases: working groups. And with the first working group (centered around Spark Structured Streaming + NLP) on its way to completion in July, we are now opening registration for a new working group – this time centered around Apache Druid: Building live dashboards with Apache Druid + Superset. The working group aims to take place End of July – October and will bring together a team of 5-6 participants that will define the scope, select the data (open data), install the needed components, implement the needed flow. Besides the participants for this group we will have a team of advisors (with experience in Druid and big data in general) that will advise the participants on how to solve different issues that will arise in the project.

Find more details of the working group here.

Learning a new solution or building an architecture for a specific use case is never easy, especially when you are trying to work alone on such an endeavour – thus this year we will debut a new way of learning specific big data solutions/use cases: working groups.

What will these working groups mean:

• A predefined topic (see below the topics for 2020) that will be either understanding a big data solution or building a use case;
• A group of 5 participants and one predefined driver per group – the scope of the driver is (besides being part of the group) to organize the groups, provide the meeting locations and the cloud infrastructure needed for installing the studied solution;
• 5 physical meetings every 2 weeks (thus a 10 weeks time window for each working group). The meetings will take place either during the week (5PM – 9PM) or Saturdays morning (10AM – 2PM).
• Active participation/contribution from each participant, for example each participant will have to present in 2 of the meetings to the rest of the group;
• Some study @ home between the sessions;

More details and registration here.