Highly rated on Google
4.9/5
Course Duration
6 weeks
Learning Mode
Offline
Placement's*
100%
Description:
The Big Data Fundamentals course provides participants with a comprehensive understanding of Big Data technologies and concepts. Participants will learn about the characteristics of Big Data, various tools and frameworks used for Big Data processing and analysis, and practical applications of Big Data in different industries. Through a combination of theoretical learning and hands-on exercises, students will gain proficiency in working with Big Data technologies and leveraging data analytics for business insights.
Key Topics:
- Introduction to Big Data
- Characteristics of Big Data (Volume, Velocity, Variety, Veracity)
- Big Data Storage and Processing Technologies (Hadoop, Spark, NoSQL databases)
- Data Ingestion and ETL (Extract, Transform, Load) processes
- Data Processing and Analysis using MapReduce and Spark
- Big Data Visualization and Reporting Tools
- Real-time Data Streaming and Processing
- Machine Learning for Big Data Analytics
- Big Data Security and Privacy Considerations
- Use Cases and Applications of Big Data in various industries
Prerequisites: Basic understanding of data analysis concepts and familiarity with programming languages such as Python or Java is recommended but not mandatory.
Who Should Attend:
- Data analysts, scientists, and engineers interested in learning about Big Data technologies and their applications.
- IT professionals seeking to enhance their skills in Big Data processing and analysis.
- Business professionals looking to gain insights from large volumes of data and make data-driven decisions.
Outcome:
Upon completion of the course, participants will have a solid understanding of Big Data fundamentals and be familiar with various Big Data technologies and tools. They will be equipped with the skills necessary to work with Big Data systems, analyze large datasets, and derive valuable insights for decision-making and business optimization.