À propos de ce cours : This project completer has proven a deep understanding on massive parallel data processing, data exploration and visualization, advanced machine learning and deep learning and how to apply his knowledge in a real-world practical use case where he justifies architectural decisions, proves understanding the characteristics of different algorithms, frameworks and technologies and how they impact model performance and scalability.
Créé par : IBM
Enseigné par : Romeo Kienzler, Chief Data Scientist, Course Lead
IBM Watson IoT
| Informations de base | Cours 4 de 4 dans Advanced Data Science with IBM Specialization |
| Niveau | Avancées |
| Langue | English |
| Comment réussir | Réussissez tous les devoirs notés pour terminer le cours. |
Programme de cours
SEMAINE 1
Week 1 - Identify DataSet and UseCase
In this module, the basic process model used for this capstone project is introduced. Furthermore, the learner is required to identify a practical use case and data set
1 vidéo, 6 lectures
- Leitura: A warm welcome
- Leitura: Overview of Architectural Methodologies for DataScience
- Leitura: Lightweight IB Cloud Garage Method for Data Science
- Leitura: Data Sources and Use Cases
- Leitura: Initial Data Exploration
- Leitura: Architectural Decisions Document (ADD)
- Avaliação entre colegas: Assignment 1
- Prompt de discussão: Discussion Promt Week 1
Noté: Milestones Checklist Week 1
SEMAINE 2
Week 2 - ETL and Feature Creation
This module emphasizes on the importance of ETL, data cleansing and feature creation as a preliminary step in ever data science project
3 lectures
- Leitura: Extract Transform Load (ETL)
- Leitura: Data Cleansing
- Leitura: Feature Engineering
- Prompt de discussão: Discussion Prompt Week 2
- Avaliação entre colegas: Assignment 2
Noté: Milestones Checklist Week 2
SEMAINE 3
Week 3 - Model Definition and Training
This module emphasizes on model selection based on use case and data set. It is important to understand how those two factors impact choice of a useful model algorithm.
2 lectures
- Leitura: Model Definition
- Leitura: Model Training
- Prompt de discussão: Discussion Promt Week 3
- Avaliação entre colegas: Assignment 3
Noté: Milestones Checklist Week 3
SEMAINE 4
Model Evaluation, Tuning, Deployment and Documentation
One a model is trained it is important to assess its performance using an appropriate metric. In addition, once the model is finished, it has to be made consumable by business stakeholders in an appropriate way
5 lectures
- Leitura: Model Evaluation
- Leitura: Model Deployment
- Leitura: Data Product (optional)
- Leitura: Create ADD - Architectural Decisions Document
- Leitura: Create a Video of your final presentation
- Prompt de discussão: Discussion Promt Week 4
- Avaliação entre colegas: Assignment 4
Noté: Milestones Checklist Week 4
Noté: Project Asset Submission
FAQ
Comment cela fonctionne
Trabalho
Cada curso é como um livro didático interativo, com vídeos pré-gravados, testes e projetos.
Ajuda dos seus colegas
Conecte-se com milhares de outros aprendizes, debata ideias, discuta sobre os materiais do curso e obtenha ajuda para dominar conceitos.
Certificados
Obtenha reconhecimento oficial pelo seu trabalho e compartilhe seu sucesso com amigos, colegas e empregadores.
Créateurs
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.
Tarification
| Acheter le cours | |
|---|---|
| Accéder au contenu du cours | Disponible |
| Accéder au contenu noté | Disponible |
| Recevoir une Note Finale | Disponible |
| Obtenir un Certificat de Cours partageable | Disponible |
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