Acerca de este Curso
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Data Analysis with Python

Aprox. 13 horas para completar

Sugerido: 5-6 weeks of study, 3-6 hours per week...

Inglés (English)

Subtítulos: Inglés (English)

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Data Analysis with Python

Aprox. 13 horas para completar

Sugerido: 5-6 weeks of study, 3-6 hours per week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
1 hora para completar

Introduction to Machine Learning

In this week, you will learn about applications of Machine Learning in different fields such as health care, banking, telecommunication, and so on. You’ll get a general overview of Machine Learning topics such as supervised vs unsupervised learning, and the usage of each algorithm. Also, you understand the advantage of using Python libraries for implementing Machine Learning models.

...
4 videos (Total 24 minutos), 1 quiz
4 videos
Introduction to Machine Learning8m
Python for Machine Learning6m
Supervised vs Unsupervised5m
1 ejercicio de práctica
Intro to Machine Learning10m
Semana
2
5 horas para completar

Regression

In this week, you will get a brief intro to regression. You learn about Linear, Non-linear, Simple and Multiple regression, and their applications. You apply all these methods on two different datasets, in the lab part. Also, you learn how to evaluate your regression model, and calculate its accuracy.

...
6 videos (Total 50 minutos), 5 quizzes
6 videos
Simple Linear Regression12m
Model Evaluation in Regression Models8m
Evaluation Metrics in Regression Models3m
Multiple Linear Regression13m
Non-Linear Regression7m
1 ejercicio de práctica
Regression10m
Semana
3
5 horas para completar

Classification

In this week, you will learn about classification technique. You practice with different classification algorithms, such as KNN, Decision Trees, Logistic Regression and SVM. Also, you learn about pros and cons of each method, and different classification accuracy metrics.

...
9 videos (Total 81 minutos), 5 quizzes
9 videos
K-Nearest Neighbours9m
Evaluation Metrics in Classification7m
Introduction to Decision Trees4m
Building Decision Trees10m
Intro to Logistic Regression7m
Logistic regression vs Linear regression15m
Logistic Regression Training13m
Support Vector Machine8m
1 ejercicio de práctica
Classification10m
Semana
4
4 horas para completar

Clustering

In this section, you will learn about different clustering approaches. You learn how to use clustering for customer segmentation, grouping same vehicles, and also clustering of weather stations. You understand 3 main types of clustering, including Partitioned-based Clustering, Hierarchical Clustering, and Density-based Clustering.

...
6 videos (Total 41 minutos), 1 reading, 4 quizzes
6 videos
Intro to k-Means9m
More on k-Means3m
Intro to Hierarchical Clustering6m
More on Hierarchical Clustering5m
DBSCAN6m
1 lectura
IBM Digital Badge2m
1 ejercicio de práctica
Clustering10m
Semana
5
2 horas para completar

Recommender Systems

In this module, you will learn about recommender systems. First, you will get introduced with main idea behind recommendation engines, then you understand two main types of recommendation engines, namely, content-based and collaborative filtering.

...
3 videos (Total 17 minutos), 3 quizzes
3 videos
Content-based Recommender Systems5m
Collaborative Filtering7m
1 ejercicio de práctica
Recommender System10m
Semana
6
4 horas para completar

Final Project

In this module, you will do a project based of what you have learned so far. You will submit a report of your project for peer evaluation.

...
2 videos (Total 20 minutos), 3 readings, 2 quizzes
2 videos
OPTIONAL: Sharing Notebooks on Watson Studio15m
3 lecturas
How to do the final project?10m
Congratulations!10m
IBM Digital Badge2m
4.7
221 revisionesChevron Right

50%

comenzó una nueva carrera después de completar estos cursos

50%

consiguió un beneficio tangible en su carrera profesional gracias a este curso

17%

consiguió un aumento de sueldo o ascenso

Principales revisiones sobre Machine Learning with Python

por RCFeb 7th 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

por JJDec 6th 2018

I am happy to have this online education, I drop out my nuclear engineering degree, I am happy to learn practical things with future... I work for IBM also...but I want to become a data scientis

Instructor

Avatar

SAEED AGHABOZORGI

Ph.D., Sr. Data Scientist
IBM Developer Skills Network

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 Certificado profesional de Ciencia de datos de IBM

Data Science has been ranked as one of the hottest professions and the demand for data practitioners is booming. This Professional Certificate from IBM is intended for anyone interested in developing skills and experience to pursue a career in Data Science or Machine Learning. This program consists of 9 courses providing you with latest job-ready skills and techniques covering a wide array of data science topics including: open source tools and libraries, methodologies, Python, databases, SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud using real data science tools and real-world data sets. It is a myth that to become a data scientist you need a Ph.D. This Professional Certificate is suitable for anyone who has some computer skills and a passion for self-learning. No prior computer science or programming knowledge is necessary. We start small, re-enforce applied learning, and build up to more complex topics. Upon successfully completing these courses you will have done several hands-on assignments and built a portfolio of data science projects to provide you with the confidence to plunge into an exciting profession in Data Science. In addition to earning a Professional Certificate from Coursera, you will also receive a digital Badge from IBM recognizing your proficiency in Data Science. LIMITED TIME OFFER: Subscription is only $39 USD per month for access to graded materials and a certificate....
Certificado profesional de Ciencia de datos de 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 del Certificado 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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