Big Data Analytics Using Spark Training

Live Online & Classroom Enterprise Training

Big Data Analytics Using Spark focuses on processing and analyzing large datasets using Apache Spark. It enables fast, scalable data analysis through distributed computing and in-memory processing.

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What is Big Data Analytics Using Spark Training about?

This course is designed to provide learners with in-depth knowledge of Apache Spark for big data analytics. It covers Spark’s core concepts, architecture, and components, enabling learners to perform large-scale data processing and advanced analytics. Participants will explore Spark Core, Spark SQL, Spark Streaming, and Spark MLlib to implement scalable big data solutions. By the end of the course, learners will have the skills to analyze diverse datasets and build machine learning models using Spark.

What are the objectives of Big Data Analytics Using Spark Training ?

Understand Apache Spark architecture and its role in big data ecosystems.
Work with Spark Core, RDDs, and DataFrames for large-scale data analysis.
Use Spark SQL for structured data queries and transformations.
Implement streaming analytics with Spark Streaming.
Apply Spark MLlib for machine learning and predictive analytics.

Who is Big Data Analytics Using Spark Training for?

Data engineers and big data developers.
Data scientists working with large and complex datasets.
Software engineers exploring distributed data processing.
Business analysts seeking to leverage Spark for analytics.
Students and professionals pursuing careers in big data.

What are the prerequisites for Big Data Analytics Using Spark Training?

Prerequisites:

Basic programming knowledge (Scala, Python, or Java).
Understanding of SQL and relational databases.
Familiarity with statistics and analytics concepts.
Knowledge of distributed systems and Hadoop basics (optional but helpful).
Exposure to Linux command line and scripting.

Learning Path:

Introduction to big data and Apache Spark ecosystem.
Spark Core concepts: RDDs, DataFrames, and Datasets.
Spark SQL and structured data processing.
Real-time data processing with Spark Streaming.
Machine learning workflows using Spark MLlib.

Related Courses:

Apache Spark and Scala
Data Engineering with PySpark
Big Data Analytics with Hadoop
Machine Learning with Big Data

Available Training Modes

Live Online Training

5 Days

Course Outline Expand All

Expand All

Module 1- Map-Reduce and Spark

The memory hierarchy

Spark Basics

Lectures and notebooks: pyspark and RDDs

Lectures and notebooks: Spark SQL and dataFrames

Lectures and notebooks: preparing for data analysis

Module 2- PCA and Weather Analysis

Covariance and PCA

Visualizing PCA Coefficients

Visualizing PCA Residuals

Visualizing PCA Residuals II

Module 3- K-Means and Intrinsic Dimensions

K-Means clustering

Intrinsic dimensions

Module 4- Decision Trees, Random Forests and Boosting

Decision trees

Boosting

Ensembles

A real-world application of PCA and Boosting

Module 5- Neural Networks and TensorFlow

Neural Networks – A historical perspective

NN: Basics

TensorFlow, Base API

Estimator API

Who is the instructor for this training?

The trainer for this Big Data Analytics Using Spark Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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