Big Data Analytics Training

Live Online & Classroom Enterprise Training

Big Data Analytics involves analyzing large and complex datasets to uncover patterns, insights, and trends. It uses advanced tools and technologies like Hadoop and Spark to support data-driven decision-making.

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What is Big Data Analytics Training about?

This course provides a comprehensive introduction to the principles, tools, and techniques of big data analytics. Learners will explore how to manage and analyze large-scale datasets using popular frameworks like Hadoop, Spark, and NoSQL databases. The course covers data ingestion, storage, processing, and visualization, along with real-world applications of analytics in business and research. By the end of the training, participants will be able to build scalable big data solutions that transform raw data into actionable insights.

What are the objectives of Big Data Analytics Training ?

Understand the fundamentals of big data and distributed systems.
Use Hadoop and Spark ecosystems for data processing and analytics.
Apply advanced analytical techniques on large datasets.
Work with NoSQL databases for unstructured and semi-structured data.
Design end-to-end big data pipelines and visualization dashboards.

Who is Big Data Analytics Training for?

Data analysts and business analysts exploring big data.
Data engineers and big data developers.
Data scientists working with large-scale data.
IT professionals transitioning into big data roles.
Students or professionals aiming for careers in analytics and AI.

What are the prerequisites for Big Data Analytics Training?

Prerequisites:

Basic programming knowledge (Python, Java, or Scala preferred).
Understanding of databases and SQL.
Familiarity with statistics and analytical concepts.
Knowledge of Linux command line and scripting.
Optional: Exposure to cloud platforms (AWS, Azure, GCP).

Learning Path:

Introduction to big data concepts and ecosystem.
Hadoop architecture and HDFS for data storage.
Spark Core, Spark SQL, and DataFrames for data analysis.
NoSQL databases (Cassandra, MongoDB, HBase).
Visualization and case studies in real-world big data analytics.

Related Courses:

Big Data Analysis with Scala and Spark
Data Engineering with PySpark
Machine Learning with Big Data
Data Warehousing and BI Analytics

Available Training Modes

Live Online Training

7 Days

Course Outline Expand All

Expand All

Module 1- Simple linear regression

Linear regression

Fitting linear regression in R

Module 2- Modelling data

Multiple continuous predictors

Multiple categorical predictors

Interactions between variables

Module 3- Many models

Fitting many models through stratification

Module 4- Classification

Generalized linear models

Linear Discriminant Analysis (LDA)

Module 5- Prediction using models

Model selection

Cross-validation

Issues with predictive models

Module 6- Getting bigger

Motivation

Getting started with sparklyr

Iris dataset redux: clustering using sparklyr

Module 7- Supervised machine learning with sparklyr

Evaluating predictive classification models

Prediction in sparklyr

Module 8- Deep learning

Deep learning models

Network structure

Defining and training networks

Module 9- Deep learning applications and scaling up

Deep learning applications

Software installation

Building and classification

Object detection Image captioning

Who is the instructor for this training?

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

Reviews

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