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Updated in [May 25th, 2023]

This course provides an overview of Cloudera's Shared Data Experience (SDX) and the Cloudera Data Platform (CDP). Participants will learn how to provision workspaces in Cloudera Machine Learning, get started with Cloudera Data Engineering on CDP, and operate a database with HBase on Data Hub. Additionally, participants will learn how to automate the deployment of Apache Spark jobs in Cloudera Data Engineering, explore data with Cloudera Data Warehouse, collect data using NiFi & Kafka on CDP Public Cloud, build automated ML pipelines in Cloudera Machine Learning, and use NVIDIA RAPIDS to accelerate AI training in CDP Hybrid Cloud. The course will also cover a day in the life of a CDP admin, ABAC configuration, and how to create a CDP Private Cloud Base (Trial) Development Cluster.

[Applications]
Upon completion of this course, participants should be able to apply the knowledge gained to their own CDP environment. They should be able to provision workspaces in Cloudera Machine Learning, get started with Cloudera Data Engineering on CDP, and operationalize databases with HBase on Data Hub. Participants should also be able to automate the deployment of Apache Spark jobs in Cloudera Data Engineering, explore and report on data with Cloudera Data Warehouse, collect data using NiFi & Kafka on CDP Public Cloud, build automated ML pipelines in Cloudera Machine Learning, and use NVIDIA RAPIDS to accelerate AI training in CDP Hybrid Cloud. Additionally, participants should be able to configure ABAC and create a CDP Private Cloud Base (Trial) Development Cluster.

[Career Paths]
1. Data Scientist: Data Scientists are responsible for analyzing large amounts of data to identify trends and patterns. They use their findings to develop predictive models and create data-driven solutions. They must have strong technical skills, such as programming, machine learning, and statistics, as well as the ability to interpret and communicate their findings. With the increasing demand for data-driven solutions, the demand for Data Scientists is expected to continue to grow.

2. Data Engineer: Data Engineers are responsible for designing, building, and maintaining data pipelines. They must have strong technical skills, such as programming, database design, and data warehousing. They must also be able to work with a variety of data sources and formats. With the increasing demand for data-driven solutions, the demand for Data Engineers is expected to continue to grow.

3. Machine Learning Engineer: Machine Learning Engineers are responsible for developing and deploying machine learning models. They must have strong technical skills, such as programming, machine learning, and statistics. They must also be able to work with a variety of data sources and formats. With the increasing demand for data-driven solutions, the demand for Machine Learning Engineers is expected to continue to grow.

4. Cloud Architect: Cloud Architects are responsible for designing and implementing cloud-based solutions. They must have strong technical skills, such as programming, cloud computing, and networking. They must also be able to work with a variety of cloud platforms and services. With the increasing demand for cloud-based solutions, the demand for Cloud Architects is expected to continue to grow.

[Education Paths]
Recommended Degree Paths:
1. Bachelor of Science in Computer Science: This degree path provides students with a comprehensive understanding of computer science fundamentals, including programming, software engineering, data structures, algorithms, and computer architecture. Students will also learn about the latest trends in computer science, such as artificial intelligence, machine learning, and cloud computing. This degree path is ideal for those interested in developing and deploying applications on the Cloudera Data Platform.

2. Master of Science in Data Science: This degree path provides students with a comprehensive understanding of data science fundamentals, including data mining, machine learning, and data visualization. Students will also learn about the latest trends in data science, such as big data analytics, natural language processing, and deep learning. This degree path is ideal for those interested in leveraging the Cloudera Data Platform to analyze and interpret data.

3. Master of Science in Artificial Intelligence: This degree path provides students with a comprehensive understanding of artificial intelligence fundamentals, including robotics, computer vision, and natural language processing. Students will also learn about the latest trends in artificial intelligence, such as deep learning, reinforcement learning, and generative adversarial networks. This degree path is ideal for those interested in using the Cloudera Data Platform to develop and deploy AI applications.

4. Master of Science in Cloud Computing: This degree path provides students with a comprehensive understanding of cloud computing fundamentals, including distributed systems, cloud architecture, and cloud security. Students will also learn about the latest trends in cloud computing, such as serverless computing, containerization, and DevOps. This degree path is ideal for those interested in deploying and managing applications on the Cloudera Data Platform.