In this course, you can understand the basics of Big data, Hadoop and machine learning concepts. You will learn how Sparkenables in- memory data processing and runs much faster than the Hadoop MapReduce, Python, Java and R-languages. You will also learn about the various APIs offered by Spark Streamingby Structured Processing. This course is an integral part of the professional career of Big Data Developer. It will also cover basic concepts such as data capture with Flume, loading data with Sqoop, a messaging system like Kafka etc.
Overview of Big data and horoscope, including HDFS (Hadoop Distributed File System), YARN (Yet AnotherResource Negotiator)
- Comprehensive knowledge of various tools that falls in Spark Ecosystem like Spark SQL, Sqoop, Kafka, Flume and Spark Streaming
The ability to include data in HDFS using Sqoop and Flume and the ability to analyse large datasets stored in HDFS
It feeds like the management of data in real time through a messaging system of publication subscribed as Kafka
Get in touch with a series of real-life projects based on the industry
The projects that are different, cover banking, telecommunications, social media and government domains.
- Rigorous involvement of an SME throughout the Spark Training to learn industry standards and best practices
Automatically analyse data using Python
Work with data in real time.
Learn tools and techniques to understand modelling
Validate automatic learning algorithms.
Explain the time series and its related ideas.
Dominate the business to manage the future.
Who Should Join this Course?
Developers aspiring to be a ‘MachineLearning Engineer | Data Scientist ‘.
Analysis Managers who manage the team of analysts.
Business analysts want to understand machine learning techniques (MLs)
Python and Java Professionals who want to design automated prediction models.
- Lectures 1
- Quizzes 0
- Duration 50 hours
- Skill level All levels
- Language English
- Students 452
- Assessments Yes