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IBM SkillsAcademy Fatec SJC 2017 .pdf



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Instituições Participantes do Programa IBM Skills Academy
Pouquíssimas Instituições de Ensino Superior no Brasil foram escolhidas para aplicar o
Programa IBM Skills Academy: a Fatec São José dos Campos foi selecionada!
Isso é motivo de grande orgulho pra nós!

Funcionamento dos Cursos

Em geral, os cursos são estruturados da seguinte forma:


Em torno de 70-80% da Carga Horária “Web based - a Distância”, em Portal
Educacional próprio da IBM, acessando a vídeos, textos e atividades;



Em torno de 20-30% da Carga Horária “Hands on - Prática Presencial”, na
própria instituição de ensino, com acompanhamento de professores da Fatec
São José dos Campos que passaram por Treinamento IBM. Recursos de
software acessíveis na Cloud IBM;



Sobre o idioma Inglês - inglês para leitura é desejável pois os vídeos estão com
áudio e legendas em inglês, mas todos esses vídeos tem material de apoio
(PDF) em português;



Ao final, os alunos podem, então, prestar Provas para serem “Certificados”
(Open Badges).

Cursos e Vagas Oferecidas na Fatec São José dos Campos

Na Fatec São José dos Campos, serão oferecidos dois cursos:



2º. Semestre de 2017: Big Data Developer (80 Vagas)
1º. Semestre de 2018: Cloud Application Developer (80 Vagas)

Público-alvo: alunos regulares dos cursos de Tecnologia em Análise e Desenvolvimento
de Sistemas e Tecnologia em Banco de Dados da Fatec São José do Campos. Exalunos não podem participar!

Critério de seleção: desempenho estudantil dos alunos.

Big Data Developer

Career path description
The Big Data Developer career path prepares students to use the Big Data platform and data
governance in order to efficiently store and manage massive amounts of data. This will require
skills in Big Data architecture, such as Hadoop, Map Reduce, Hbase, Big SQL and BigSheets.
The Big Data Developer will use tools to capture, store and analyze structured and unstructured
data.
Delivery method
80% web-based and 20% instructor led
Audience

Undergraduate senior students from IT related academic programs i.e. computer science,
software engineering, information systems and similar others.
Modules
Module I – Data Management Overview
Module II – Big Data Foundations
Module III – Big Data Developer
Prerequisites Skills
• Basic knowledge of Linux and Hadoop




It would be helpful to take DW613 – IBM BigInsights Overview to have a better
understanding of how BigSheets
Students can attend free courses at www.bigdatauniversity.com to acquire the
necessary requirements

Duration
77.35 hours (aprox.)
Skill level
Basic – Intermediate

Big Data Developer - Learning objectives
After completing this course, you should be able to:






































Understand relational database concepts
Demonstrate working with database objects
Reading data
Understand how to insert, update, and delete data
Work with multiple tables
Understand what DB2 Express-C is and its requirements
Understand DB2 servers, clients, and drivers and how to upgrade from one edition to
another
Learn how to install and get started with DB2
Understand the DB2 environment
Understand how to use IBM Data Studio to work with DB2
Understand how to use deprecated DB2 tools
Learn how to work with SQL scripts and operating system scripts
Understand the DB2 architecture (process model, memory model, and storage model)
Learn about the different DB2 directories, and how to connect to a DB2 server from a
DB2 client
Understand how to work with different DB2 database objects
Understand how to work with EXPORT, IMPORT, LOAD, db2move, and db2look data
movement utilities
Describe Big Data
Describe the Hadoop architecture
Start and stop the BigInsights components
Add, and remove nodes to a Hadoop cluster
Describe the use of MapReduce, Pig, Jaql, Hive, Flume, Sqooq, Oozie
Assess the state of Big Data adoption across a number of industry sectors
Differentiate between the use of open source components for Big Data and a platform
approach to integration of Big Data in an enterprise
List five high-value Big Data use cases
Point out technical details of some key Big Data components
Discuss some futures of Big Data and Cloud
Access additional resources in order to continue your learning
Understand why it’s important to understand and use Big Data
Explain the difference between data-at-rest and data-in-motion
Understand Big SQL, BigSheets, and Big R
Understand ODP core, namely Apache Hadoop, and Apache Ambari
Understand Hadoop Distributed File System (HDFS)
Explain the function of NameNode and DataNode
Understand how to store and access data
Understand data movement
Understand coordination management and governance
Understand how Big SQL fits in the Hadoop architecture
























Learn how to create Big SQL schemas and tables
Learn how load data into Big SQL tables
List and understand the Big SQL data types
Understand Big SQL data access plans
Understand how to use Big SQL statistics to improve query performance
Learn how to setup and use Big SQL federation
Understand how to use Big SQL operations on tables managed by Hbase
Learn how to use Spark operations on data managed by Big SQL
Understand how to use BigSheets for data analysis
Learn how to make data available to BigSheets
Demonstrate how to navigate a workbook
Discover data with expressions, functions, and formulas
Understand how to integrate with Big SQL
Visualize data with Big SQL
Understand and describe the need for text analytics
Understand the Annotation Query Language (AQL)
Describe the AQL data model
Text Analytics web tooling
Navigate a Text Analytics project in the web UI
Import documents into a project
Understand the Text Analytics development process
Use the tooling to create and test extractors

Gostou? Como participar?

Cronograma:
Datas
Até 18/08/2017

Até 25/08/2017
De 01/09/2017
a 30/11/2017

Atividades
Pré-inscrição no curso “Big Data Developer” (80 Vagas), para o
2º. Semestre de 2017, pelo formulário:
https://goo.gl/forms/43LZpkKtxQB5doVf2
Divulgação dos 80 alunos selecionados (por desempenho
estudantil)
Curso “Big Data Developer”, sendo que em torno de 20-30% será
presencial
Obs. Datas de
oportunamente.

encontros

presenciais

serão

divulgadas


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