Informações sobre o curso
5,759 visualizações recentes

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 9 horas para completar

Sugerido: This course requires 4 to 5 hours of study....

Inglês

Legendas: Inglês

Habilidades que você terá

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível intermediário

Aprox. 9 horas para completar

Sugerido: This course requires 4 to 5 hours of study....

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
2 horas para concluir

IBM AI Enterprise Workflow Introduction

3 vídeos (Total 12 mín.), 13 leituras, 3 testes
3 videos
IBM Watson Studio - Create a project5min
Workflow Overview3min
13 leituras
About this course3min
Target Audience2min
Required skills2min
An introduction to IBM Watson Studio and IBM Design Thinking12min
Overview of IBM Watson Studio2min
Am I ready?1min
Am I ready to take this Specialization?3min
Readiness Quiz Review12min
Advantages and disadvantages of process models2min
Data Science Process Models2min
The design thinking process2min
Data science workflow combined with design thinking13min
Process Models, Design Thinking, and Introduction: Summary/Review3min
3 exercícios práticos
Readiness Quiz45min
Process Models & Design Thinking: Check for Understanding2min
Process Models, Design Thinking, and Introduction: End of Module Quiz10min
1 hora para concluir

Data Collection

5 vídeos (Total 17 mín.), 5 leituras, 4 testes
5 videos
Introduction to Business Opportunities2min
Introduction to Scientific Thinking for Business2min
Introduction to Gathering Data2min
AI Workflow: Gathering data6min
5 leituras
Data Collection Objectives2min
Identifying the business opportunity: Through the eyes of our Working Example5min
Scientific Thinking for Business10min
Gathering Data12min
Data Collection: Summary/Review3min
4 exercícios práticos
Business Opportunities: Check for Understanding4min
Scientific Thinking for Business: Check for Understanding2min
Gathering Data: Check for Understanding2min
Data Collection: End of Module Quiz5min
Semana
2
3 horas para concluir

Data Ingestion

5 vídeos (Total 40 mín.), 15 leituras, 2 testes
5 videos
AI Workflow: Data ingestion6min
AI Workflow: Sparse matrices for data pipeline development10min
Using Watson Studio to complete the case study16min
Case Study2min
15 leituras
Data Engineering3min
Limitations of Extract, Transform, Load (ETL)3min
Data ingestion in the modern enterprise1min
Enterprise data stores for data ingestion3min
Why we need a data ingestion process2min
Data ingestion and automation3min
Sparse matrices are used early in data ingestion development5min
Getting started Watson Studio3min
Case Study Introduction2min
Getting Started3min
Data Sources2min
PART 1: Gathering the data10min
PART 2: Checks for quality assurance (Includes Assessment)10min
PART 3: Automating the process (Includes Assessment)10min
Data Ingestion: Summary/Review3min
2 exercícios práticos
Ingesting Data: Check for Understanding3min
Data Ingestion: End of Module Quiz

Instrutores

Avatar

Mark J Grover

Digital Content Delivery Lead
IBM Data & AI Learning
Avatar

Ray Lopez, Ph.D.

Data Science Curriculum Leader
IBM Data & Artificial Intelligence

Sobre IBM

IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame....

Sobre Programa de cursos integrados IBM AI Enterprise Workflow

This six course specialization is designed to prepare you to take the certification examination for IBM AI Enterprise Workflow V1 Data Science Specialist. IBM AI Enterprise Workflow is a comprehensive, end-to-end process that enables data scientists to build AI solutions, starting with business priorities and working through to taking AI into production. The learning aims to elevate the skills of practicing data scientists by explicitly connecting business priorities to technical implementations, connecting machine learning to specialized AI use cases such as visual recognition and NLP, and connecting Python to IBM Cloud technologies. The videos, readings, and case studies in these courses are designed to guide you through your work as a data scientist at a hypothetical streaming media company. Throughout this specialization, the focus will be on the practice of data science in large, modern enterprises. You will be guided through the use of enterprise-class tools on the IBM Cloud, tools that you will use to create, deploy and test machine learning models. Your favorite open source tools, such a Jupyter notebooks and Python libraries will be used extensively for data preparation and building models. Models will be deployed on the IBM Cloud using IBM Watson tooling that works seamlessly with open source tools. After successfully completing this specialization, you will be ready to take the official IBM certification examination for the IBM AI Enterprise Workflow....
IBM AI Enterprise Workflow

Perguntas Frequentes – FAQ

  • Ao se inscrever para um Certificado, você terá acesso a todos os vídeos, testes e tarefas de programação (se aplicável). Tarefas avaliadas pelos colegas apenas podem ser enviadas e avaliadas após o início da sessão. Caso escolha explorar o curso sem adquiri-lo, talvez você não consiga acessar certas tarefas.

  • Quando você se inscreve no curso, tem acesso a todos os cursos na Especialização e pode obter um certificado quando concluir o trabalho. Seu Certificado eletrônico será adicionado à sua página de Participações e você poderá imprimi-lo ou adicioná-lo ao seu perfil no LinkedIn. Se quiser apenas ler e assistir o conteúdo do curso, você poderá frequentá-lo como ouvinte sem custo.

  • This course assumes that you are already familiar with basic data science concepts including probability and statistics, linear algebra, machine learning, and the use of Python and Jupyter. If you are unsure we do offer a Readiness Exam you can take to see if you are prepared.

  • No. Most of the exercises may be completed with open source tools running on your personal computer. However, the exercises are designed with an enterprise focus and are intended to be run in an enterprise environment that allows for easier sharing and collaboration. The exercises in the last two modules of the course are heavily focused on deployment and testing of machine learning models and use the IBM Watson tooling found on the IBM Cloud.

  • Yes. All IBM Cloud Data and AI services are based upon open source technologies.

  • The exercises in the course may be completed by anyone using the IBM Cloud "Lite" plan, which is free for use.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.