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Big Data

Big Data courses introduce key concepts for handling massive datasets, including tools like Hadoop and Spark.

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Course Detail

Course covers distributed systems, processing frameworks (Spark), and applications like machine learning at scale.

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Course Features

  • Introduction to Big Data
  • Big Data Architecture
  • Hadoop Ecosystem
  • Lexical Sense

Lexsense

Semantic Search

Lexsense is a research-driven platform focused on helping computers understand language, meaning, and context. It works at the intersection of AI, linguistics, and data science, especially in fields like NLP, semantic search, and machine learning. 

  • 20 hours on-demand video
  • Full Lifetime Access
  • Access on Mobile and TV
  • Certificate of Completion

Course Content

11 sections • 28 lecture • 19h 33m total length

Explains the design of systems that handle large-scale data processing and storage. Covers distributed computing models and the flow of data across different components.

Introduces the Apache Hadoop framework for distributed storage and processing of big data.
Covers core components like HDFS and MapReduce for scalable data handling.

Focuses on fast and efficient data processing using Apache Spark. Covers concepts like RDDs, DataFrames, and real-time analytics.

Explores different storage solutions for big data, including relational and NoSQL systems. Covers distributed databases and data lakes for scalable and flexible data management.

Describes methods for collecting and transferring data from various sources into big data systems.
Includes real-time streaming and tools for handling continuous data flows.

Focuses on analyzing large datasets to extract meaningful insights. Covers visualization techniques to present data through charts, dashboards, and reports.

Explains how cloud platforms provide scalable resources for storing and processing big data. Covers cloud-based tools and services for flexible and cost-effective data solutions.

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