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Updated in [May 25th, 2023]

Learners can learn a variety of topics from this course, including:

1. Big Data Environment: Learners will gain an understanding of the big data environment, including how to sign up for big data labs and troubleshoot any login issues.

2. Introduction to ITVersity Forums: Learners will be introduced to the ITVersity forums, which provide a wealth of resources and support for their learning journey.

3. Introduction to Scala: Learners will learn the basics of Scala, including how to read and save sequence files.

4. Hadoop Certifications: Learners will gain the skills and knowledge necessary to become a Cloudera Certified Associate Spark and Hadoop Developer.

[Applications]
The application of this course can be seen in the development of Big Data applications. After completing this course, individuals can use their knowledge to develop applications that can process large amounts of data efficiently. They can also use their knowledge to create applications that can store and analyze data in a distributed environment. Additionally, they can use their knowledge to create applications that can read and save sequence files. Furthermore, they can use their knowledge to create applications that can interact with the ITVersity forums.

[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large datasets to uncover trends and insights. They use a variety of tools and techniques to extract, clean, and transform data, and then use statistical and machine learning methods to uncover patterns and insights. Data Scientists are in high demand as organizations look to leverage the power of big data to gain a competitive edge.

2. Big Data Engineer: Big Data Engineers are responsible for designing, building, and maintaining the infrastructure and systems that store and process large datasets. They use a variety of technologies, such as Hadoop, Spark, and NoSQL databases, to create and maintain data pipelines and data warehouses.

3. Data Analyst: Data Analysts are responsible for analyzing large datasets to uncover trends and insights. They use a variety of tools and techniques to extract, clean, and transform data, and then use statistical and machine learning methods to uncover patterns and insights.

4. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models. They use a variety of tools and techniques to build and deploy models, and then use them to make predictions and recommendations. Machine Learning Engineers are in high demand as organizations look to leverage the power of machine learning to gain a competitive edge.

[Education Paths]
1. Bachelor's Degree in Computer Science: A Bachelor's Degree in Computer Science provides students with a comprehensive understanding of computer programming, software engineering, and computer systems. This degree path is ideal for those interested in developing and managing large-scale software systems. Additionally, this degree path provides students with the opportunity to specialize in areas such as artificial intelligence, machine learning, and data science.

2. Master's Degree in Data Science: A Master's Degree in Data Science provides students with the skills and knowledge necessary to analyze and interpret large datasets. This degree path is ideal for those interested in developing predictive models and uncovering insights from data. Additionally, this degree path provides students with the opportunity to specialize in areas such as machine learning, natural language processing, and deep learning.

3. Master's Degree in Artificial Intelligence: A Master's Degree in Artificial Intelligence provides students with the skills and knowledge necessary to develop intelligent systems. This degree path is ideal for those interested in developing autonomous agents and intelligent systems. Additionally, this degree path provides students with the opportunity to specialize in areas such as robotics, computer vision, and natural language processing.

4. Doctoral Degree in Machine Learning: A Doctoral Degree in Machine Learning provides students with the skills and knowledge necessary to develop advanced machine learning algorithms. This degree path is ideal for those interested in developing and deploying machine learning models in real-world applications. Additionally, this degree path provides students with the opportunity to specialize in areas such as deep learning, reinforcement learning, and natural language processing.