Coursera – NoSQL, Big Data, and Spark Foundations Specialization (by IBM)

Coursera – NoSQL, Big Data, and Spark Foundations Specialization (by IBM)
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Springboard your Big Data career. Master fundamentals of NoSQL, Big Data, and Apache Spark with hands-on job-ready skills in machine learning and data engineering.

What you’ll Learn:
• Work with NoSQL databases to insert, update, delete, query, index, aggregate, and
shard/partition data.
• Develop hands-on NoSQL experience working with MongoDB, Apache Cassandra, and IBM
Cloudant.
• Develop foundational knowledge of Big Data and gain hands-on lab experience using Apache
Hadoop, MapReduce, Apache Spark, Spark SQL, and Kubernetes.
• Perform Extract, Transform and Load (ETL) processing and Machine Learning model training
and deployment with Apache Spark.

Skills you’ll Gain:
• Cloud Database
• Mongodb
• Cassandra
• NoSQL
• Cloudant
• Machine Learning
• Machine Learning Pipelines
• Data Engineer
• SparkML
• Apache Spark
• Big Data
• SparkSQL
• Apache Hadoop

Specialization – 3 Course Series:
Big Data Engineers and professionals with NoSQL skills are highly sought after in the data management industry. This Specialization is designed for those seeking to develop fundamental skills for working with Big Data, Apache Spark, and NoSQL databases. Three information-packed courses cover popular NoSQL databases like MongoDB and Apache Cassandra, the widely used Apache Hadoop ecosystem of Big Data tools, as well as Apache Spark analytics engine for large-scale data processing.

You start with an overview of various categories of NoSQL (Not only SQL) data repositories, and then work hands-on with several of them including IBM Cloudant, MonogoDB and Cassandra. You’ll perform various data management tasks, such as creating & replicating databases, inserting, updating, deleting, querying, indexing, aggregating & sharding data. Next, you’ll gain fundamental knowledge of Big Data technologies such as Hadoop, MapReduce, HDFS, Hive, and HBase, followed by a more in depth working knowledge of Apache Spark, Spark Dataframes, Spark SQL, PySpark, the Spark Application UI, and scaling Spark with Kubernetes. In the final course, you will learn to work with Spark Structured Streaming Spark ML – for performing Extract, Transform and Load processing (ETL) and machine learning tasks.

This specialization is suitable for beginners in the fields of NoSQL and Big Data – whether you are or preparing to be a Data Engineer, Software Developer, IT Architect, Data Scientist, or IT Manager.

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