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.
Este curso faz parte do Programa de cursos integrados Advanced Data Science with IBM
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Informações sobre o curso
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Resultados de carreira do aprendiz
67%
comecei uma nova carreira após concluir estes cursos
57%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 4 de 4 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível avançado
Aprox. 9 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Russo, Inglês, Espanhol
Resultados de carreira do aprendiz
67%
comecei uma nova carreira após concluir estes cursos
57%
consegui um benefício significativo de carreira com este curso
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 4 de 4 no
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível avançado
Aprox. 9 horas para completar
Inglês
Legendas: Árabe, Francês, Portuguese (European), Chinês (simplificado), Russo, Inglês, Espanhol
oferecido por
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.
Programa - O que você aprenderá com este curso
2 horas para concluir
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
2 horas para concluir
1 vídeo (Total 2 mín.), 7 leituras, 2 testes
1 vídeos
7 leituras
A warm welcome10min
Overview of Architectural Methodologies for DataScience10min
Lightweight IBM Cloud Garage Method for Data Science10min
Data Sources and Use Cases10min
Initial Data Exploration10min
Architectural Decisions Document (ADD)10min
Process Model Guidelines10min
1 exercício prático
Milestones Checklist Week 1
2 horas para concluir
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
2 horas para concluir
3 leituras
3 leituras
Extract Transform Load (ETL)10min
Data Cleansing10min
Feature Engineering10min
1 exercício prático
Milestones Checklist Week 2
2 horas para concluir
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 horas para concluir
2 leituras
2 leituras
Model Definition10min
Model Training10min
1 exercício prático
Milestones Checklist Week 3
3 horas para concluir
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
3 horas para concluir
5 leituras
5 leituras
Model Evaluation10min
Model Deployment10min
Data Product (optional)10min
Create ADD - Architectural Decisions Document10min
Create a Video of your final presentation10min
2 exercícios práticos
Milestones Checklist Week 4
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Avaliações
Principais avaliações do ADVANCED DATA SCIENCE CAPSTONE
por KW11 de Jul de 2019
Innovative teacher and course. Learned how to make a youtube video beside the data science challenge. On the whole specialization, very comprehensive and set me up to want to delve further next.
por SS13 de Jan de 2019
I liked the peer-graded environment. Like the final submission requirements. That's really helps in aquiring the skills like presentation skills, Documentation skills, project mangement
por VT17 de Mar de 2019
Like that course. It combine all you skills in a one project. It is very helpful for the understanding why and how ML can help for the business. Personal thanks for Romeo Kienzler!
por MZ20 de Jan de 2020
This is data crunching, varied machine learning model exploring, training, testing, validating and deployment course. What a goldmine for both novices and seasoned and initiated!
Sobre Programa de cursos integrados Advanced Data Science with IBM
As a coursera certified specialization completer you will have a proven deep understanding on massive parallel data processing, data exploration and visualization, and advanced machine learning & deep learning. You'll understand the mathematical foundations behind all machine learning & deep learning algorithms. You can apply knowledge in practical use cases, justify architectural decisions, understand the characteristics of different algorithms, frameworks & technologies & how they impact model performance & scalability.
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