This Data Science Edureka course is designed to provide knowledge and skills to become a successful data scientist. The course covers a range of Hadoop techniques, R and machine learning spanning the entire study of data science.
Who should attend this course?
This course is designed for all those who want to learn machine learning techniques and wish to apply these techniques in Big Data. The course is the fusion of two powerful open source tools: 'R language’ and Hadoop software framework.
Aprenderá a explorar datos cuantitativamente usando herramientas como SqoopSqoop es una herramienta de código abierto diseñada para facilitar la transferencia de datos entre bases de datos relacionales y el ecosistema Hadoop. Permite la importación de datos desde sistemas como MySQL, PostgreSQL y Oracle a HDFS, así como la exportación de datos desde Hadoop a estas bases de datos. Sqoop optimiza el proceso mediante la paralelización de las operaciones, lo que lo convierte en una solución eficiente para el... Y FlumeFlume is an open-source software designed for data collection and transport. Use a flow-based approach, allowing data to be moved from various sources to storage systems such as Hadoop. Its modular and scalable architecture makes it easy to integrate with multiple data sources, which makes it a valuable tool for the processing and analysis of large volumes of information in real time...., escribir trabajos Hadoop MapReduceMapReduce is a programming model designed to efficiently process and generate large data sets. Powered by Google, This approach breaks down work into smaller tasks, which are distributed among multiple nodes in a cluster. Each node processes its part and then the results are combined. This method allows you to scale applications and handle massive volumes of information, being fundamental in the world of Big Data...., perform text analysis and use language processing, learn machine learning techniques using Mahout and make the most of and visualize the results using the 'R programming language’ y Apache Mahout .
Prerequisites:
Some of the prerequisites for learning data science are familiarity with Hadoop, machine learning and knowledge of R (It is recommended not mandatory since these concepts will also be covered throughout the course). At the same time, having statistical knowledge will be an additional advantage.
Duration:
Online classes: 30 hours
Lab hours: 40 hours
Project: 20 hours
Way: Online
Halftime, full time:
Part time
Next lots:
