Informações sobre o curso
7,212 visualizações recentes

100% on-line

Comece imediatamente e aprenda em seu próprio cronograma.

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.

Nível avançado

Aprox. 7 horas para completar

Sugerido: This course requires 7.5 to 9 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 avançado

Aprox. 7 horas para completar

Sugerido: This course requires 7.5 to 9 hours of study....

Inglês

Legendas: Inglês

Programa - O que você aprenderá com este curso

Semana
1
4 horas para concluir

Model Evaluation and Performance Metrics

6 vídeos (Total 18 mín.), 19 leituras, 6 testes
6 videos
Evaluation Metrics2min
Introduction to Predictive Linear and Logistic Regression3min
Linear Models4min
Watson Natural Language Understanding Service Overview3min
Case Study Introduction1min
19 leituras
Evaluation metrics: Through the eyes of our Working Example3min
Evaluation Metrics3min
Regression metrics5min
Classification metrics10min
Multi-class and multi-label metrics3min
Model performance: Through the eyes of our Working Example3min
Generalizing well to unseen data3min
Model plots, bias, variance4min
Relating the evaluation metric to a business metric4min
Linear models: Through the eyes of our Working Example3min
Generalized linear models5min
Linear and logistic regression5min
Regularized regression3min
Stochastic gradient descent classifier3min
Watson Natural Language Understanding: Through the eyes of our Working Example3min
Watson Developer Cloud Python SDK10min
Performance and business metrics: Through the eyes of our Working Example3min
Getting started with performance and business metrics case study (hands-on)2h
Summary/Review10min
6 exercícios práticos
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
End of Module Quiz10min
Semana
2
3 horas para concluir

Building Machine Learning and Deep Learning Models

5 vídeos (Total 15 mín.), 14 leituras, 5 testes
5 videos
Introduction to Tree Based Methods2min
Neural Networks2min
Introduction to neural networks4min
IBM Watson Visual Recognition Overview2min
14 leituras
Tree-based methods: Through the eyes of our Working Example3min
Decision trees4min
Bagging and Random forests4min
Boosting2min
Ensemble learning4min
Neural networks: Through the eyes of our Working Example3min
Multilayer perceptron (MLP)4min
Neural network architectures4min
On interpretability2min
Watson Visual Recognition: Through the eyes of our Working Example3min
Watson Developer Cloud Python SDK10min
TensorFlow: Through the eyes of our Working Example3min
Getting started with Convolutional neural networks and TensorFlow (hands-on)2h
Summary/Review10min
5 exercícios práticos
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
Check for Understanding2min
End of Module Quiz10min

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.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.