Об этом курсе

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Курс 4 из 6 в программе
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Продвинутый уровень
Прибл. 7 часов на выполнение
Английский
Субтитры: Английский

Приобретаемые навыки

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
Сертификат, ссылками на который можно делиться с другими людьми
Получите сертификат по завершении
100% онлайн
Начните сейчас и учитесь по собственному графику.
Курс 4 из 6 в программе
Гибкие сроки
Назначьте сроки сдачи в соответствии со своим графиком.
Продвинутый уровень
Прибл. 7 часов на выполнение
Английский
Субтитры: Английский

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Логотип IBM

IBM

Программа курса: что вы изучите

Неделя
1

Неделя 1

4 ч. на завершение

Model Evaluation and Performance Metrics

4 ч. на завершение
6 видео ((всего 18 мин.)), 19 материалов для самостоятельного изучения, 6 тестов
6 видео
Evaluation Metrics2мин
Introduction to Predictive Linear and Logistic Regression3мин
Linear Models4мин
Watson Natural Language Understanding Service Overview3мин
Case Study Introduction1мин
19 материалов для самостоятельного изучения
Evaluation metrics: Through the eyes of our Working Example3мин
Evaluation Metrics3мин
Regression metrics5мин
Classification metrics10мин
Multi-class and multi-label metrics3мин
Model performance: Through the eyes of our Working Example3мин
Generalizing well to unseen data3мин
Model plots, bias, variance4мин
Relating the evaluation metric to a business metric4мин
Linear models: Through the eyes of our Working Example3мин
Generalized linear models5мин
Linear and logistic regression5мин
Regularized regression3мин
Stochastic gradient descent classifier3мин
Watson Natural Language Understanding: Through the eyes of our Working Example3мин
Watson Developer Cloud Python SDK10мин
Performance and business metrics: Through the eyes of our Working Example3мин
Getting started with performance and business metrics case study (hands-on)
Summary/Review10мин
6 практических упражнений
Check for Understanding2мин
Check for Understanding2мин
Check for Understanding2мин
Check for Understanding2мин
Check for Understanding2мин
End of Module Quiz10мин
Неделя
2

Неделя 2

3 ч. на завершение

Building Machine Learning and Deep Learning Models

3 ч. на завершение
5 видео ((всего 15 мин.)), 14 материалов для самостоятельного изучения, 5 тестов
5 видео
Introduction to Tree Based Methods2мин
Neural Networks2мин
Introduction to neural networks4мин
IBM Watson Visual Recognition Overview2мин
14 материалов для самостоятельного изучения
Tree-based methods: Through the eyes of our Working Example3мин
Decision trees4мин
Bagging and Random forests4мин
Boosting2мин
Ensemble learning4мин
Neural networks: Through the eyes of our Working Example3мин
Multilayer perceptron (MLP)4мин
Neural network architectures4мин
On interpretability2мин
Watson Visual Recognition: Through the eyes of our Working Example3мин
Watson Developer Cloud Python SDK10мин
TensorFlow: Through the eyes of our Working Example3мин
Getting started with Convolutional neural networks and TensorFlow (hands-on)
Summary/Review10мин
5 практических упражнений
Check for Understanding2мин
Check for Understanding2мин
Check for Understanding2мин
Check for Understanding2мин
End of Module Quiz10мин

Специализация IBM AI Enterprise Workflow: общие сведения

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

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