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Updated in [March 06th, 2023]

This course, Big Data Essentials: HDFS MapReduce and Spark RDD, is designed to provide learners with a comprehensive introduction to the modern Big Data landscape. Learners will gain an understanding of the fundamentals of distributed file systems, the MapReduce framework, and the Spark computational framework. Through practical assignments, learners will gain hands-on experience in applying these tools to create solutions in finance, social networks, telecommunications, and many other fields.

Learners will gain an understanding of the basics of HDFS, MapReduce, and Spark, including their internals and applications. They will learn how to use the MapReduce framework to process texts and solve sample business cases. They will also learn how to use Spark to build strong understanding of its basic concepts and develop skills to apply these tools to create solutions.

In addition, learners will have the opportunity to evaluate their practical assignments on a real cluster, providing them with a real-life experience. With the help of experienced instructors, learners will be able to gain a comprehensive understanding of Big Data technologies and apply them to their own projects.

[Applications]
The application of this course can be seen in various fields such as finance, social networks, telecommunications and many others. After completing this course, students will have a strong understanding of HDFS, MapReduce and Spark, and the skills to apply these tools to create solutions in the aforementioned fields. They will also be able to evaluate their practical assignments on a real cluster.

[Career Paths]
1. Big Data Engineer: Big Data Engineers are responsible for designing, developing, and maintaining the infrastructure and systems that store and process large amounts of data. They must be knowledgeable in the latest Big Data technologies such as HDFS, MapReduce, and Spark RDD, and have experience in developing and deploying distributed applications. As the demand for Big Data solutions continues to grow, Big Data Engineers will be in high demand.

2. Big Data Analyst: Big Data Analysts are responsible for analyzing large amounts of data to uncover trends and insights. They must be knowledgeable in data mining, machine learning, and statistical analysis techniques, and have experience in working with large datasets. As the need for data-driven decision making increases, Big Data Analysts will be in high demand.

3. Data Scientist: Data Scientists are responsible for developing and deploying data-driven solutions to solve complex business problems. They must be knowledgeable in data mining, machine learning, and statistical analysis techniques, and have experience in working with large datasets. As the need for data-driven solutions increases, Data Scientists will be in high demand.

4. Data Visualization Specialist: Data Visualization Specialists are responsible for creating visual representations of data to help people understand and interpret complex datasets. They must be knowledgeable in data visualization tools and techniques, and have experience in creating interactive visualizations. As the need for data-driven insights increases, Data Visualization Specialists will be in high demand.

[Education Paths]
1. Bachelor of Science in Computer Science: This degree program focuses on the fundamentals of computer science, such as programming, software engineering, and computer architecture. It also covers topics such as artificial intelligence, data structures, and algorithms. This degree is ideal for those interested in developing and managing software applications and systems. Developing trends in this field include the use of machine learning and artificial intelligence to create more efficient and powerful software applications.

2. Master of Science in Data Science: This degree program focuses on the analysis and interpretation of large datasets. It covers topics such as data mining, machine learning, and statistical analysis. This degree is ideal for those interested in working with large datasets to uncover insights and trends. Developing trends in this field include the use of natural language processing and deep learning to uncover more complex patterns in data.

3. Master of Science in Big Data Analytics: This degree program focuses on the analysis and interpretation of large datasets. It covers topics such as data mining, machine learning, and statistical analysis. This degree is ideal for those interested in working with large datasets to uncover insights and trends. Developing trends in this field include the use of predictive analytics and data visualization to uncover more complex patterns in data.

4. Doctor of Philosophy in Big Data: This degree program focuses on the research and development of new technologies and methods for analyzing and interpreting large datasets. It covers topics such as data mining, machine learning, and statistical analysis. This degree is ideal for those interested in advancing the field of big data and developing new methods for uncovering insights and trends. Developing trends in this field include the use of artificial intelligence and blockchain technology to create more efficient and secure data analysis systems.