Big Data Training in Cincinnati, OH

R Programming Big Data

Our R language training course is specially designed to provide the required knowledge and skills to become a successful data analytics professional. Our course covers basic concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc.

Big Data Fundamentals

The Big Data Fundamentals course introduces participants to the essentials of managing and processing large, complex data sets that traditional tools cannot handle. With a focus on key technologies like Hadoop and Spark, this course provides hands-on experience in dealing with both structured and unstructured data, understanding Big Data concepts, and utilizing advanced data processing frameworks.

Big Data with Apache Hadoop and Solr

Our training will help you to expand your horizons in the field of big data and how Solr helps big data along with Hadoop. Our training will give adequate knowledge to take a deep dive into the ocean of Big data will all the necessary concepts.

Python Big Data

Our training course in Python will help you to understand the popularly used programming language for Data Science. In this Python programming training, you will be exposed to both the basic and advanced concepts of Python like machine learning, Deep Learning, Hadoop streaming, Map Reduce in Python, and work with packages like Scikit and Scipy.

Hadoop Fundamentals for Beginners

Enroll in Hadoop fundamentals course to gain knowledge using the environmental setup procedures, Hadoop Distributed File System Operations, Command reference, and Streaming. Demand for Hadoop in the market opens up the job opportunities for Hadoop professionals. This course syllabus was created by Big Data Hadoop experts and taught by professional trainers.

Introduction to Hadoop

This course provides a comprehensive introduction to Apache Hadoop, an open-source framework designed to handle large-scale data processing across clustered systems. Hadoop is essential for working with Big Data, leveraging its core components—Hadoop Distributed File System (HDFS), Hadoop YARN, Hadoop MapReduce, and Hadoop Common—to efficiently process and manage data. This course covers the fundamental aspects of Hadoop and its ecosystem, providing a solid foundation for further exploration in data science

Introduction to Spark Fundamentals

This introductory course on Apache Spark focuses on harnessing the power of Spark for accelerated data processing and analytics. Spark is a powerful framework that enhances Hadoop’s capabilities by providing in-memory cluster computing, which speeds up iterative algorithms, streaming, and interactive queries. Unlike Hadoop, Spark can run on various platforms including Hadoop YARN, Mesos, and in the cloud.

Moving Data into Hadoop

This course provides a comprehensive introduction to moving data into the Hadoop ecosystem. Hadoop, a powerful framework for distributed storage and computing, supports the efficient processing of large data sets across clusters. This training focuses on utilizing tools like Flume and Sqoop to ingest and manage data within Hadoop, leveraging its scalable and fault-tolerant architecture.

Access Hadoop Data using Hive

This course introduces Hive, a data warehousing infrastructure tool for querying and managing large datasets within the Hadoop ecosystem. Hive simplifies data analysis by providing a high-level query language (HiveQL) similar to SQL, built on top of Hadoop’s MapReduce framework. It offers an efficient way to perform data warehousing tasks and manage structured data at scale.

Machine Learning training

Deep Learning With TensorFlow training

Data Analysis training

Hadoop Developer training

Hadoop Spark training

Data Science training

Deep Learning training

Data Modeling training