À propos de ce cours
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Niveau avancé

Approx. 9 heures pour terminer

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

Anglais

Sous-titres : Anglais
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Les étudiants prenant part à ce Course sont
  • Data Scientists
  • Software Engineers

Compétences que vous acquerrez

Data ScienceInformation EngineeringArtificial Intelligence (AI)Machine LearningPython Programming
User
Les étudiants prenant part à ce Course sont
  • Data Scientists
  • Software Engineers

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau avancé

Approx. 9 heures pour terminer

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

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1
4 heures pour terminer

Model Evaluation and Performance Metrics

6 vidéos (Total 18 min), 19 lectures, 6 quiz
6 vidéos
Evaluation Metrics2 min
Introduction to Predictive Linear and Logistic Regression3 min
Linear Models4 min
Watson Natural Language Understanding Service Overview3 min
Case Study Introduction1 min
19 lectures
Evaluation metrics: Through the eyes of our Working Example3 min
Evaluation Metrics3 min
Regression metrics5 min
Classification metrics10 min
Multi-class and multi-label metrics3 min
Model performance: Through the eyes of our Working Example3 min
Generalizing well to unseen data3 min
Model plots, bias, variance4 min
Relating the evaluation metric to a business metric4 min
Linear models: Through the eyes of our Working Example3 min
Generalized linear models5 min
Linear and logistic regression5 min
Regularized regression3 min
Stochastic gradient descent classifier3 min
Watson Natural Language Understanding: Through the eyes of our Working Example3 min
Watson Developer Cloud Python SDK10 min
Performance and business metrics: Through the eyes of our Working Example3 min
Getting started with performance and business metrics case study (hands-on)2 h
Summary/Review10 min
6 exercices pour s'entraîner
Check for Understanding2 min
Check for Understanding2 min
Check for Understanding2 min
Check for Understanding2 min
Check for Understanding2 min
End of Module Quiz10 min
Semaine
2
3 heures pour terminer

Building Machine Learning and Deep Learning Models

5 vidéos (Total 15 min), 14 lectures, 5 quiz
5 vidéos
Introduction to Tree Based Methods2 min
Neural Networks2 min
Introduction to neural networks4 min
IBM Watson Visual Recognition Overview2 min
14 lectures
Tree-based methods: Through the eyes of our Working Example3 min
Decision trees4 min
Bagging and Random forests4 min
Boosting2 min
Ensemble learning4 min
Neural networks: Through the eyes of our Working Example3 min
Multilayer perceptron (MLP)4 min
Neural network architectures4 min
On interpretability2 min
Watson Visual Recognition: Through the eyes of our Working Example3 min
Watson Developer Cloud Python SDK10 min
TensorFlow: Through the eyes of our Working Example3 min
Getting started with Convolutional neural networks and TensorFlow (hands-on)2 h
Summary/Review10 min
5 exercices pour s'entraîner
Check for Understanding2 min
Check for Understanding2 min
Check for Understanding2 min
Check for Understanding2 min
End of Module Quiz10 min

Enseignants

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Mark J Grover

Digital Content Delivery Lead
IBM Data & AI Learning
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Ray Lopez, Ph.D.

Data Science Curriculum Leader
IBM Data & Artificial Intelligence

À propos de 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....

À propos du Spécialisation 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

Foire Aux Questions

  • Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.

  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

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