Applications and Software

Big Data

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Course Overview

Our comprehensive Big Data course equips you with the skills to harness the power of massive datasets. Learn essential concepts, tools, and techniques for data storage, processing, and analysis. With hands-on projects and real-world applications, you’ll gain expertise in extracting valuable insights from complex data.

What You'll Learn?

  • 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 𝐅𝐮𝐧𝐝𝐚𝐦𝐞𝐧𝐭𝐚𝐥𝐬: Master the essentials of Big Data, including data storage, processing, and distributed systems.
  • 𝐇𝐚𝐝𝐨𝐨𝐩 𝐄𝐜𝐨𝐬𝐲𝐬𝐭𝐞𝐦: Dive into the Hadoop ecosystem and explore frameworks like HDFS, MapReduce, and Spark for scalable data processing.
  • 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐓𝐞𝐜𝐡𝐧𝐢𝐪𝐮𝐞𝐬:Learn advanced data analysis techniques for handling large datasets and uncovering valuable insights.
  • 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐨𝐧 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚: Apply machine learning algorithms to big datasets and develop predictive models for business applications.
  • 𝐑𝐞𝐚𝐥-𝐓𝐢𝐦𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬: Gain expertise in real-time data processing and analytics using technologies like Kafka and Apache Flink.
  • Basic understanding of programming in Python or Java
  • Familiarity with data structures and algorithms
  • Basic knowledge of databases and SQL
  • Basic knowledge of Linux command line interface.
  • 24 Hours of Sessions
  • Flexible Schedules
  • 24/7 Lifetime Support
  • Certification Oriented Curriculum
  • FREE Demo on Request
  • One-on-One Doubt Clearing
  • Real-time Project Use cases

Course Content

  • Introduction to Big Data

    • Definition and characteristics of Big Data

    • Challenges and opportunities in Big Data analytics

    • Potential applications of Big Data in various industries

  • Big Data Technologies

    • Overview of Hadoop, Spark, and other popular Big Data frameworks

    • Cluster computing and distributed computing concepts

    • Data storage and processing techniques in Big Data systems

  • Data Ingestion and Transformation

    • Extracting data from various sources

    • Transforming and cleaning data for analysis

    • Best practices for data ingestion in Big Data systems

  • Data Storage and Retrieval

    • Introduction to NoSQL databases (MongoDB, Cassandra, etc.)

    • Designing data models for efficient storage and retrieval

    • Query languages for Big Data systems

  • Data Visualization and Reporting

    • Principles of data visualization

    • Tools and techniques for visualizing Big Data

    • Creating insightful reports and dashboards

  • Advanced Analytics with Big Data

    • Introduction to machine learning and predictive modeling

    • Techniques for building and evaluating predictive models

    • Use cases of advanced analytics in Big Data

  • Scalability, Security, and Privacy in Big Data

    • Scalability challenges and techniques in Big Data systems

    • Ensuring data security and privacy in Big Data implementations

    • Compliance considerations for Big Data analytics

  • Real-world Big Data Case Studies

    • Analysis of successful Big Data implementations

    • Learning from real-world challenges and solutions

    • Trends and future directions in Big Data analytics

  • Capstone Project

    • Applying all concepts and techniques learned throughout the course

    • Solving a complex Big Data problem

    • Presenting the final project

Paid
  • Duration 01:00:00
  • Lessons 27
  • Language English, Hindi, Telugu
  • Skill Intermediate
  • Last Update October 19, 2023

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