Informações sobre o curso

210,500 visualizações recentes
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 4 de 6 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 30 horas para completar
Inglês
Legendas: Inglês
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 4 de 6 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário
Aprox. 30 horas para completar
Inglês
Legendas: Inglês

Instrutores

oferecido por

Logotipo de IBM

IBM

Programa - O que você aprenderá com este curso

Classificação do conteúdoThumbs Up88%(1,413 classificações)Info
Semana
1

Semana 1

5 horas para concluir

Tensor and Datasets

5 horas para concluir
6 vídeos (Total 44 mín.), 1 leitura, 11 testes
6 videos
1.1 Tensors 1D13min
1.2 Two-Dimensional Tensors9min
Differentiation in PyTorch5min
1.3 Simple Dataset7min
1.5 Dataset4min
1 leituras
Labs10min
5 exercícios práticos
1.1 Tensors 1D5min
1.2 Two-Dimensional Tensors5min
1.3 Derivatives in PyTorch5min
Simple Dataset5min
Datasets10min
Semana
2

Semana 2

2 horas para concluir

Linear Regression

2 horas para concluir
7 vídeos (Total 35 mín.)
7 videos
2.1 Linear Regression Training3min
Loss3min
Gradient Descent4min
Cost3min
Linear Regression PyToch5min
PyTorch Linear Regression Training Slope and Bias5min
7 exercícios práticos
Prediction in One Dimension5min
Linear Regression Training5min
Loss5min
Gradient Descent5min
Cost5min
Training Parameters in PyTorch5min
PyTorch Linear Regression Training Slope and Bias5min
3 horas para concluir

Linear Regression PyTorch Way

3 horas para concluir
5 vídeos (Total 21 mín.)
5 videos
Mini-Batch Gradient Descent3min
Optimization in PyTorch3min
Training, Validation and Test Split4min
Training, Validation and Test Split PyTorch3min
4 exercícios práticos
Quiz: Stochastic Gradient Descent5min
Mini-Batch Gradient Descent5min
3.3 Optimization in PyTorch5min
Training and Validation Data PyTorch5min
Semana
3

Semana 3

2 horas para concluir

Multiple Input Output Linear Regression

2 horas para concluir
4 vídeos (Total 18 mín.)
4 videos
Multiple Linear Regression Training2min
Linear Regression Multiple Outputs5min
Multiple Output Linear Regression Training1min
2 exercícios práticos
Multiple Linear Regression Prediction5min
Multiple Output Linear Regression5min
2 horas para concluir

Logistic Regression for Classification

2 horas para concluir
4 vídeos (Total 31 mín.)
4 videos
5.1 Logistic Regression: Prediction6min
Bernoulli Distribution and Maximum Likelihood Estimation5min
Logistic Regression Cross Entropy Loss10min
5 exercícios práticos
5.0 Linear Classifiers5min
5.0 Linear Classifiers5min
5.1 Logistic Regression: Prediction10min
Bernoulli Distribution and Maximum Likelihood Estimation5min
5.3 Logistic Regression Cross Entropy Loss10min
Semana
4

Semana 4

2 horas para concluir

Softmax Rergresstion

2 horas para concluir
3 vídeos (Total 18 mín.)
3 videos
6.2 Softmax Function:Using Lines to Classify Data3min
Softmax PyTorch6min
3 exercícios práticos
6.1 Softmax Function:Using Lines to Classify Data5min
6.2 Softmax Prediction5min
6.3 Softmax PyTorch Quizz5min
3 horas para concluir

Shallow Neural Networks

3 horas para concluir
6 vídeos (Total 33 mín.)
6 videos
More Hidden Neurons2min
Neural Networks with Multiple Dimensional Input5min
7.4 Multi-Class Neural Networks5min
7.5 Backpropagation5min
7.5 Activation Functions4min
6 exercícios práticos
Neural Networks5min
More Hidden Neurons 5min
Neural Networks with Multiple Dimensional Inputs5min
Multi-Class Neural Networks5min
Backpropagation5min
Activation Functions5min

Avaliações

Principais avaliações do DEEP NEURAL NETWORKS WITH PYTORCH

Visualizar todas as avaliações

Sobre Certificado Profissional IBM AI Engineering

The rapid pace of innovation in Artificial Intelligence (AI) is creating enormous opportunity for transforming entire industries and our very existence. After competing this comprehensive 6 course Professional Certificate, you will get a practical understanding of Machine Learning and Deep Learning. You will master fundamental concepts of Machine Learning and Deep Learning, including supervised and unsupervised learning. You will utilize popular Machine Learning and Deep Learning libraries such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow applied to industry problems involving object recognition and Computer Vision, image and video processing, text analytics, Natural Language Processing, recommender systems, and other types of classifiers. You will be able to scale Machine Learning on Big Data using Apache Spark. You will build, train, and deploy different types of Deep Architectures, including Convolutional Networks, Recurrent Networks, and Autoencoders. By the end of this Professional Certificate, you will have completed several projects showcasing your proficiency in Machine Learning and Deep Learning, and become armed with skills for a career as an AI Engineer....
IBM AI Engineering

Perguntas Frequentes – FAQ

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Certificate, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.