IBM
4 weeks to complete at 10 hours a week
Master fundamentals of NoSQL, Big Data, and Apache Spark with hands-on job-ready skills in machine learning and data engineering.
The courses in the specialization require that you have basic computer and data literacy skills, as well as some programming background with languages such as with Python and SQL. No prior knowledge or experience of Big Data and NoSQL is required.
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.
As a market-leading tech innovator, IBM is committed to helping you thrive in this dynamic landscape. Through IBM Skills Network, their expertly designed training programs in AI, software development, cybersecurity, data science, business management, and more, provide the essential skills you need to secure your first job, advance your career, or drive business success.
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. Upon successful completion, you will have the practical knowledge and experience to start tackling Data Engineering tasks involving NoSQL Databases, Big Data and Apache Spark.
