IBM
NoSQL, Big Data, and Spark Foundations Specialization
IBM

NoSQL, Big Data, and Spark Foundations Specialization

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.

Taught in English

Some content may not be translated

IBM Skills Network Team
Muhammad Yahya
Romeo Kienzler

Instructors: IBM Skills Network Team

2,145 already enrolled

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Specialization - 3 course series

Get in-depth knowledge of a subject

4.4

(146 reviews)

Beginner level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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.

Details to know

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Specialization - 3 course series

Get in-depth knowledge of a subject

4.4

(146 reviews)

Beginner level

Recommended experience

1 month at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 3 course series

Introduction to NoSQL Databases

Course 117 hours4.6 (255 ratings)

What you'll learn

  • Differentiate among the four main categories of NoSQL repositories.

  • Describe the characteristics, features, benefits, limitations, and applications of the more popular Big Data processing tools.

  • Perform common tasks using MongoDB tasks including create, read, update, and delete (CRUD) operations.

  • Execute keyspace, table, and CRUD operations in Cassandra.

Skills you'll gain

Category: Cloud Database
Category: Mongodb
Category: Cassandra
Category: NoSQL
Category: Cloudant

Introduction to Big Data with Spark and Hadoop

Course 218 hours4.4 (330 ratings)

What you'll learn

  • Explain the impact of big data, including use cases, tools, and processing methods.

  • Describe Apache Hadoop architecture, ecosystem, practices, and user-related applications, including Hive, HDFS, HBase, Spark, and MapReduce.

  • Apply Spark programming basics, including parallel programming basics for DataFrames, data sets, and Spark SQL.

  • Use Spark’s RDDs and data sets, optimize Spark SQL using Catalyst and Tungsten, and use Spark’s development and runtime environment options.

Skills you'll gain

Category: Big Data
Category: SparkSQL
Category: SparkML
Category: Apache Hadoop
Category: Apache Spark

Machine Learning with Apache Spark

Course 314 hours4.6 (54 ratings)

What you'll learn

  • Describe ML, explain its role in data engineering, summarize generative AI, discuss Spark's uses, and analyze ML pipelines and model persistence.

  • Evaluate ML models, distinguish between regression, classification, and clustering models, and compare data engineering pipelines with ML pipelines.

  • Construct the data analysis processes using Spark SQL, and perform regression, classification, and clustering using SparkML.

  • Demonstrate connecting to Spark clusters, build ML pipelines, perform feature extraction and transformation, and model persistence.

Skills you'll gain

Category: Machine Learning
Category: Machine Learning Pipelines
Category: Data Engineer
Category: SparkML
Category: Apache Spark

Instructors

IBM Skills Network Team
IBM
53 Courses744,459 learners

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IBM

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