Acerca de este Curso
4.8
59 calificaciones
12 revisiones
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel avanzado

Nivel avanzado

Horas para completar

Aprox. 20 horas para completar

Sugerido: 16 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)...
Programa Especializado
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel avanzado

Nivel avanzado

Horas para completar

Aprox. 20 horas para completar

Sugerido: 16 hours/week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)...

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
5 horas para completar

Setting the stage

...
Reading
10 videos (Total: 59 min), 2 readings, 3 quizzes
Video10 videos
Linear algebra5m
High Dimensional Vector Spaces2m
Supervised vs. Unsupervised Machine Learning4m
How ML Pipelines work3m
Introduction to SparkML20m
What is SystemML (1/2) ?3m
What is SystemML (2/2) ?6m
How to use Apache SystemML in IBM Watson Studio4m
Extract - Transform - Load3m
Reading2 lecturas
Object Store10m
Latest Video summary on environment setup10m
Quiz2 ejercicios de práctica
Machine Learning12m
ML Pipelines6m
Semana
2
Horas para completar
6 horas para completar

Supervised Machine Learning

...
Reading
26 videos (Total: 131 min), 1 reading, 10 quizzes
Video26 videos
LinearRegression with Apache SparkML6m
Linear Regression using Apache SystemML3m
Batch Gradient Descent using Apache SystemML8m
The importance of validation data to prevent overfitting3m
Important evaluation measures2m
Logistic Regression1m
LogisticRegression with Apache SparkML4m
Probabilities refresher6m
Rules of probability and Bayes' theorem10m
The Gaussian distribution4m
Bayesian inference4m
Bayesian inference - example9m
Maximum a posteriori estimation5m
Bayesian inference in Python8m
Why is Naive Bayes "naive"7m
Support Vector Machines3m
Support Vector Machines using Apache SparkML8m
Crossvalidation1m
Hyper-parameter tuning using GridSearch3m
Decision Trees2m
Bootstrap Aggregation (Bagging) and RandomForest1m
Boosting and Gradient Boosted Trees6m
Gradient Boosted Trees with Apache SparkML2m
Hyperparameter-Tuning using GridSeach and CrossValidation in Apache SparkML on Gradient Boosted Trees3m
Regularization3m
Reading1 lectura
Classification evaluation measures10m
Quiz9 ejercicios de práctica
Linear Regression6m
Splitting and Overfitting2m
Evaluation Measures2m
Logistic Regression2m
Naive Bayes16m
Support Vector Machines2m
Testing, X-Validation, GridSearch4m
Enselble Learning4m
Regularization4m
Semana
3
Horas para completar
5 horas para completar

Unsupervised Machine Learning

...
Reading
13 videos (Total: 67 min), 1 reading, 3 quizzes
Video13 videos
Introduction to Clustering: k-Means3m
Hierarchical Clustering3m
Density-based clustering (Guest Lecture Saeed Aghabozorgi)4m
Using K-Means in Apache SparkML2m
Curse of Dimensionality9m
Dimensionality Reduction4m
Principal Component Analysis6m
Principal Component Analysis (demo)6m
Covariance matrix and direction of greatest variance8m
Eigenvectors and eigenvalues8m
Projecting the data4m
PCA in SystemML2m
Reading1 lectura
Reading on Clustering Evaluation and Assessment10m
Quiz2 ejercicios de práctica
Clustering4m
PCA16m
Semana
4
Horas para completar
5 horas para completar

Digital Signal Processing in Machine Learning

...
Reading
13 videos (Total: 108 min), 3 quizzes
Video13 videos
Fourier Transform in action6m
Signal generation and phase shift11m
The maths behind Fourier Transform11m
Discrete Fourier Transform16m
Fourier Transform in SystemML15m
Fast Fourier Transform7m
Nonstationary signals5m
Scaleograms7m
Continous Wavelet Transform3m
Scaling and translation3m
Wavelets and Machine Learning3m
Wavelets transform and SVM demo6m
Quiz2 ejercicios de práctica
Fourier Transform16m
Wavelet Transform16m
4.8

Principales revisiones

por ASep 8th 2018

A career changer course, thanks the hand-ons which is second to none, i have gained experience which on other online course can produce, thanks to IBM for this course which timely and excellent.

por IMJun 26th 2018

Very well structured, easy to follow/understand. This is a hot topic at the moment and helped me in my job.

Instructores

Avatar

Romeo Kienzler

Chief Data Scientist, Course Lead
IBM Watson IoT
Avatar

Nikolay Manchev

Data Scientist
IBM EMEA Data Science

Acerca 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....

Acerca del programa especializado 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. If you choose to take this specialization and earn the Coursera specialization certificate, you will also earn an IBM digital badge. To find out more about IBM digital badges follow the link ibm.biz/badging....
Advanced Data Science with IBM

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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