We provide Continuous Learning using Workshops, Conferences and hands-on Projects
Before you take a technology learning decision ask following questions
Would you have greater chance of success learning a single technology / language like Python / Java or would you rather learn a full technology track which would help you deliver real life projects?
What skills are required to work as big data engineer, data analyst and data scientist?
First step is to understand the learning track to start working as a data engineer or data analyst or data scientist – though technology stack could change but core concepts would remain the same.
Whereas Data scientist could typically start with Algebra + Statistics + Analytical techniques + Python + R + TensorFlow + Artificial Intelligence + Deep learning + Spark
Add to these few common skills like Cloud + Devops
Most of the working professionals struggle to find a project after learning new technologies.
Project based learning is a step to bridge that gap.
Mathematics for Data Science
Analytical Techniques and Machine Learning
Deep Learning with TensorFlow
Spark, Pig, Hive
Big Data Track
Hadoop Ecosystem (Hadoop, Pig, Hive, Flume, Sqoop)
Spark (SparkSQL, DataFrames, Streaming, MLib)
Kafka, NiFi, Integrations
NoSQL Architecture, Data Modeling