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Nestor Nicolas Campos Rojas
En este proyecto de 1 hora, aprenderás a desarrollar un modelo supervisado utilizando la herramienta gratuita de Azure Machine Learning Studio, de una forma interactiva sin necesidad de codificar.
Además, aprenderás a guardar tu modelo y publicarlo para su...
Read more
En este proyecto de 1 hora, aprenderás a desarrollar un modelo supervisado utilizando la herramienta gratuita de Azure Machine Learning Studio, de una forma interactiva sin necesidad de codificar.
Además, aprenderás a guardar tu modelo y publicarlo para su...
Read more
En este proyecto de 1 hora, aprenderás a desarrollar un modelo supervisado utilizando la herramienta gratuita de Azure Machine Learning Studio, de una forma interactiva sin necesidad de codificar.
Además, aprenderás a guardar tu modelo y publicarlo para su utilización por otros usuarios y aplicaciones.
Register for this course and see more details by visiting:
OpenCourser.com/course/mj66uh/disenando
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Develops beginner skills in Azure Machine Learning Studio, a commonly used, industry-standard tool
Teaches an in-demand skill relevant to data analytics, machine learning, and artificial intelligence
Provides practical, interactive instruction with no coding necessary
Requires proficiency in basic data analysis and machine learning concepts
Assumes familiarity with the Azure Machine Learning platform and its services
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Reviews summary
Helpful intro to azure machine learning studio
This course is a great starting point for learning how to use Azure Machine Learning Studio. It's a one-hour project-based course that teaches you how to develop a supervised model using Azure Machine Learning Studio without coding. The course also covers how to save your model and publish it for use by other users and applications.
Well-suited for beginners with little to no prior knowledge.
"Este curso es para tener un panorama general de Azure Machine Learning Studio."
Interactive and hands-on learning experience.
"Excelente taller práctico-introductorio para iniciar con Machine Learning!"
May require some background in Machine Learning concepts.
"Algunos aspectos de la presentación requieren conocimiento previo de temas de Machine Learning básico para aprovecharlo mejor."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Diseñando modelos con Azure Machine Learning Studio with these
activities:
Review linear algebra and calculus
Show steps
Ensures a solid understanding of mathematical concepts essential for machine learning.
Browse courses on
Linear Algebra
Show steps
-
Review key topics
-
Solve practice problems
-
Complete online quizzes
Review cloud computing concepts
Show steps
Provides a strong foundation in cloud computing concepts and prepares you for the course's hands-on activities.
View
Cloud Computing: Concepts, Technology &...
on Amazon
Show steps
-
Read chapters 1-3
-
Summarize key concepts
-
Complete practice exercises
Follow online tutorials on Azure Machine Learning Studio
Show steps
Provides additional support and guidance for using Azure Machine Learning Studio, supplementing the course's lessons.
Show steps
-
Identify relevant tutorials
-
Follow the steps and instructions
-
Practice and apply what you learn
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice building models in Azure Machine Learning Studio
Show steps
Develops practical skills in using Azure Machine Learning Studio, reinforcing the course's concepts.
Show steps
-
Create a new project
-
Import and prepare data
-
Train and evaluate models
-
Deploy and monitor models
Join or form a study group with other course participants
Show steps
Fosters collaboration, knowledge sharing, and peer support, promoting deeper understanding and retention.
Show steps
-
Find or create a study group
-
Schedule regular meetings
-
Discuss course topics
-
Share resources and insights
Create a blog post or article on machine learning
Show steps
Enhances understanding and retention by requiring you to explain machine learning concepts to others.
Show steps
-
Choose a topic
-
Research and gather information
-
Write and edit content
-
Publish and promote
Attend industry workshops or conferences on machine learning
Show steps
Exposes you to cutting-edge trends and practices in machine learning, broadening your knowledge and industry connections.
Show steps
-
Identify relevant events
-
Register and attend
-
Network with professionals
-
Learn about latest advancements
Review linear algebra and calculus
Show steps
Ensures a solid understanding of mathematical concepts essential for machine learning.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review key topics
- Solve practice problems
- Complete online quizzes
Review cloud computing concepts
Show steps
Provides a strong foundation in cloud computing concepts and prepares you for the course's hands-on activities.
View
Cloud Computing: Concepts, Technology &...
on Amazon
Show steps
Show steps
Show steps
- Read chapters 1-3
- Summarize key concepts
- Complete practice exercises
Follow online tutorials on Azure Machine Learning Studio
Show steps
Provides additional support and guidance for using Azure Machine Learning Studio, supplementing the course's lessons.
Show steps
Show steps
Show steps
- Identify relevant tutorials
- Follow the steps and instructions
- Practice and apply what you learn
Four other activities
Expand to see all activities and additional details
Show all seven activities
Practice building models in Azure Machine Learning Studio
Show steps
Develops practical skills in using Azure Machine Learning Studio, reinforcing the course's concepts.
Show steps
Show steps
Show steps
- Create a new project
- Import and prepare data
- Train and evaluate models
- Deploy and monitor models
Join or form a study group with other course participants
Show steps
Fosters collaboration, knowledge sharing, and peer support, promoting deeper understanding and retention.
Show steps
Show steps
Show steps
- Find or create a study group
- Schedule regular meetings
- Discuss course topics
- Share resources and insights
Create a blog post or article on machine learning
Show steps
Enhances understanding and retention by requiring you to explain machine learning concepts to others.
Show steps
Show steps
Show steps
- Choose a topic
- Research and gather information
- Write and edit content
- Publish and promote
Attend industry workshops or conferences on machine learning
Show steps
Exposes you to cutting-edge trends and practices in machine learning, broadening your knowledge and industry connections.
Show steps
Show steps
Show steps
- Identify relevant events
- Register and attend
- Network with professionals
- Learn about latest advancements
Career center
Learners who complete Diseñando modelos con Azure Machine Learning Studio will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A Data Scientist uses their knowledge in data modeling to develop and apply machine learning models for predictive analytics, descriptive analytics, and prescriptive analytics. This course introduces the Azure Machine Learning Studio, a tool that enables professionals to create and deploy machine learning models. Azure Machine Learning Studio is free to use and requires no coding knowledge, making it a great option for professionals who are new to data modeling and machine learning.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, building, and deploying machine learning models. They work closely with data scientists and other engineers to ensure that machine learning models are accurate, efficient, and reliable. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models. The course also discusses how to save and publish machine learning models for use by other users and applications.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They use their findings to make recommendations and inform decision-making. This course teaches how to create and use machine learning models to automate this process, saving time and improving efficiency. The course will also cover how to save and publish machine learning models for use by other users and applications.
Business Analyst
Business Analyst
Business Analysts use data to identify and solve business problems. They work with stakeholders to understand their needs and then use data to develop and implement solutions. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models. Machine learning can be used to perform tasks such as detecting fraud, mitigating risk, and forecasting demand, all of which can help businesses improve their operations and performance.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with stakeholders to gather requirements, design software solutions, and then implement and test those solutions. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models. Machine learning models can be used to enhance software applications with features such as predictive analytics, image recognition, and natural language processing.
Product Manager
Product Manager
Product Managers are responsible for the development and marketing of products. They work with stakeholders to identify market needs, develop product specifications, and then launch and manage products. Machine learning can be used in nearly every aspect of product management, including developing new products, improving product quality, and marketing products to specific user segments. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment recommendations. They work with clients to understand their financial goals and then use data to develop and implement investment strategies. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models. Machine learning models can be used to automate tasks such as stock selection, portfolio optimization, and risk management.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and implementing marketing campaigns. They work with stakeholders to identify target markets, develop marketing messages, and then launch and manage marketing campaigns. Machine learning can be used to automate tasks such as customer segmentation, lead scoring, and campaign optimization. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Sales Manager
Sales Manager
Sales Managers are responsible for leading and managing sales teams. They work with stakeholders to identify sales goals, develop sales strategies, and then motivate and manage sales teams. Machine learning can be used to automate tasks such as lead generation, lead qualification, and sales forecasting. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Operations Manager
Operations Manager
Operations Managers are responsible for the day-to-day operations of an organization. They work with stakeholders to identify operational goals, develop operational plans, and then implement and manage operational processes. Machine learning can be used to automate tasks such as process optimization, inventory management, and quality control. This course teaches the basics of machine learning modeling and covers how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Human Resources Manager
Human Resources Manager
Human Resources Managers are responsible for the management of human resources within an organization. They work with stakeholders to identify human resources goals, develop human resources policies, and then implement and manage human resources programs. Machine learning can be used to automate tasks such as employee screening, training and development, and performance management. This course may teach the basics of machine learning modeling and cover how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Project Manager
Project Manager
Project Managers are responsible for the planning and execution of projects. They work with stakeholders to identify project goals, develop project plans, and then manage project teams. Machine learning can be used to automate tasks such as project planning, resource allocation, and risk management. This course may teach the basics of machine learning modeling and cover how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Consultant
Consultant
Consultants provide advice and guidance to clients on a variety of topics. They work with clients to identify problems, develop solutions, and then implement and evaluate solutions. Machine learning can be used to automate tasks such as data analysis, market research, and financial modeling. This course may teach the basics of machine learning modeling and cover how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Teacher
Teacher
Teachers plan and deliver instruction to students in a variety of settings. They work with students to identify learning goals, develop lesson plans, and then teach and assess students. Machine learning can be used to automate tasks such as grading, providing feedback, and creating personalized learning experiences. This course may teach the basics of machine learning modeling and cover how to use the Azure Machine Learning Studio to create and deploy machine learning models.
Writer
Writer
Writers create and publish content in a variety of formats. They work with editors and publishers to develop and produce content that meets the needs of their audience. Machine learning can be used to automate tasks such as content generation, editing, and translation. This course may teach the basics of machine learning modeling and cover how to use the Azure Machine Learning Studio to create and deploy machine learning models.
For more career information including salaries, visit:
OpenCourser.com/course/mj66uh/disenando
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Diseñando modelos con Azure Machine Learning Studio.
This advanced textbook offers a comprehensive and rigorous treatment of machine learning from a probabilistic perspective. It covers a wide range of topics, including supervised and unsupervised learning, graphical models, and Bayesian inference. Suitable for those with a strong mathematical background.
Convex optimization powerful technique used in machine learning for solving optimization problems. This textbook provides a comprehensive treatment of convex optimization, including algorithms, theory, and applications. It offers a deep understanding of the mathematical foundations of ML.
Providing a strong foundation in the mathematical concepts underlying machine learning algorithms, this book can supplement the course by enhancing learners' understanding of the theoretical basis of ML and its applications.
This advanced textbook focuses on statistical learning methods that exploit sparsity, such as the lasso and its generalizations. It provides a theoretical understanding of these methods and their applications in various fields, including machine learning.
This classic textbook provides a comprehensive introduction to reinforcement learning, which subfield of machine learning concerned with training agents to make decisions in complex environments. It offers a theoretical foundation and practical guidance for implementing RL algorithms.
While not directly related to supervised learning, this book offers a comprehensive introduction to deep learning, including theoretical concepts and practical implementation using Python. It provides valuable insights into a more advanced area of machine learning.
Save
This widely-used textbook covers deep learning, an advanced topic related to machine learning. While not directly related to the course's focus on supervised learning, it can provide valuable insights into the broader field of machine learning for those interested in further exploration.
Offers a practical approach to learning data science concepts and techniques from scratch. It covers the fundamentals of data manipulation, analysis, and visualization, providing a strong foundation for working with machine learning models.
Might offer a useful background on machine learning concepts and techniques, using R as the programming language. It covers essential ML algorithms and provides a solid foundation for understanding the course's content.
A helpful reference for those who want to learn Python for data analysis and manipulation, which are essential skills for working with machine learning models. It assumes no prior programming experience and provides a thorough introduction to Python.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/mj66uh/disenando
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Time
60 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Nestor Nicolas Campos Rojas
Good to know
Develops beginner skills in Azure Machine Learning Studio, a commonly used, industry-standard tool
Teaches an in-demand skill relevant to data analytics, machine learning, and artificial intelligence
Provides practical, interactive instruction with no coding necessary
Requires proficiency in basic data analysis and machine learning concepts
Assumes familiarity with the Azure Machine Learning platform and its services
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