- Apache Hadoop
- Mongodb
- Big Data
- Apache Spark
- NoSQL Databases
- NoSQL
- Cloud Database
- Cloudant
- Cassandra
- SparkSQL
- SparkML
Programa especializado: NoSQL, Big Data, and Spark Foundations
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.
ofrecido por

Qué aprenderás
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.
Habilidades que obtendrás
Acerca de este Programa Especializado
Proyecto de aprendizaje aplicado
The emphasis in this specialization is on learning by doing. As such, each course includes hands-on labs to practice & apply the NoSQL and Big Data skills you learn during lectures.
In the first course, you will work hands-on with several NoSQL databases- MongoDB, Apache Cassandra, and IBM Cloudant to perform a variety of tasks: creating the database, adding documents, querying data, utilizing the HTTP API, performing Create, Read, Update & Delete (CRUD) operations, limiting & sorting records, indexing, aggregation, replication, using CQL shell, keyspace operations, & other table operations.
In the next course, you’ll launch a Hadoop cluster using Docker and run Map Reduce jobs. You’ll explore working with Spark using Jupyter notebooks on a Python kernel. You’ll build your Spark skills using DataFrames, Spark SQL, and scale your jobs using Kubernetes.
In the final course you will use Spark for ETL processing, and Machine Learning model training and deployment using IBM Watson.
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.
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.
Cómo funciona el programa especializado
Toma cursos
Un programa especializado de Coursera es un conjunto de cursos que te ayudan a dominar una aptitud. Para comenzar, inscríbete en el programa especializado directamente o échale un vistazo a sus cursos y elige uno con el que te gustaría comenzar. Al suscribirte a un curso que forme parte de un programa especializado, quedarás suscrito de manera automática al programa especializado completo. Puedes completar solo un curso: puedes pausar tu aprendizaje o cancelar tu suscripción en cualquier momento. Visita el panel principal del estudiante para realizar un seguimiento de tus inscripciones a cursos y tu progreso.
Proyecto práctico
Cada programa especializado incluye un proyecto práctico. Necesitarás completar correctamente el proyecto para completar el programa especializado y obtener tu certificado. Si el programa especializado incluye un curso separado para el proyecto práctico, necesitarás completar cada uno de los otros cursos antes de poder comenzarlo.
Obtén un certificado
Cuando completes todos los cursos y el proyecto práctico, obtendrás un Certificado que puedes compartir con posibles empleadores y tu red profesional.

Hay 3 cursos en este Programa Especializado
Introduction to NoSQL Databases
This course will provide you with technical hands-on knowledge of NoSQL databases and Database-as-a-Service (DaaS) offerings. With the advent of Big Data and agile development methodologies, NoSQL databases have gained a lot of relevance in the database landscape. Their main advantage is the ability to effectively handle scalability and flexibility issues raised by modern applications.
Introduction to Big Data with Spark and Hadoop
Bernard Marr defines Big Data as the digital trace that we are generating in this digital era. In this course, you will learn about the characteristics of Big Data and its application in Big Data Analytics. You will gain an understanding about the features, benefits, limitations, and applications of some of the Big Data processing tools. You’ll explore how Hadoop and Hive help leverage the benefits of Big Data while overcoming some of the challenges it poses.
Data Engineering and Machine Learning using Spark
Organizations need skilled, forward-thinking Big Data practitioners who can apply their business and technical skills to unstructured data such as tweets, posts, pictures, audio files, videos, sensor data, and satellite imagery and more to identify behaviors and preferences of prospects, clients, competitors, and others.
ofrecido por

IBM
IBM is the global leader in business transformation through an open hybrid cloud platform and AI, serving clients in more than 170 countries around the world. Today 47 of the Fortune 50 Companies rely on the IBM Cloud to run their business, and IBM Watson enterprise AI is hard at work in more than 30,000 engagements. IBM is also one of the world’s most vital corporate research organizations, with 28 consecutive years of patent leadership. Above all, guided by principles for trust and transparency and support for a more inclusive society, IBM is committed to being a responsible technology innovator and a force for good in the world.
Preguntas Frecuentes
¿Cuál es la política de reembolsos?
¿Puedo inscribirme en un solo curso?
¿Hay ayuda económica disponible?
¿Puedo tomar este curso de manera gratuita?
¿Este curso es 100 % en línea? ¿Necesito asistir a alguna clase en persona?
¿Cuánto tiempo se necesita para completar un programa especializado?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
¿Recibiré crédito universitario por completar el programa especializado?
What will I be able to do upon completing the Specialization?
¿Tienes más preguntas? Visita el Centro de Ayuda al Alumno.