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Rav Ahuja
En este curso aprenderá cómo comenzar rápida y fácilmente con la Inteligencia Artificial utilizando IBM Watson. Comprenderá cómo funciona Watson, se familiarizará con sus casos de uso y ejemplos de clientes de la vida real, y se le presentarán varios de los...
Read more
En este curso aprenderá cómo comenzar rápida y fácilmente con la Inteligencia Artificial utilizando IBM Watson. Comprenderá cómo funciona Watson, se familiarizará con sus casos de uso y ejemplos de clientes de la vida real, y se le presentarán varios de los...
Read more
En este curso aprenderá cómo comenzar rápida y fácilmente con la Inteligencia Artificial utilizando IBM Watson. Comprenderá cómo funciona Watson, se familiarizará con sus casos de uso y ejemplos de clientes de la vida real, y se le presentarán varios de los servicios de inteligencia artificial de Watson de IBM que permiten a cualquiera aplicar fácilmente la inteligencia artificial y crear aplicaciones inteligentes. También trabajará con varios servicios de Watson para demostrar la IA en acción.
Este curso no requiere ninguna experiencia en programación o ciencias de la computación y está diseñado para cualquier persona, ya sea que tenga una formación técnica o no.
Esta es una traducción al español de un curso que se creó originalmente en inglés. Muchos de los componentes del curso se han traducido al español, incluidos títulos de lecciones, transcripciones de videos, lecturas, instrucciones de laboratorio y cuestionarios. Sin embargo, algunos componentes del curso, incluidos los videos originales y su narración, todavía están en inglés.
Register for this course and see more details by visiting:
OpenCourser.com/course/5pw1rk/iniciacion
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Teaches introductory artificial intelligence (AI) concepts and IBM Watson's AI services
Provides a good starting point for beginners in AI
Emphasizes practical applications of AI in various fields
Involves hands-on activities and demonstrations with IBM Watson services
Accessible to learners without prior programming or computer science experience
Course materials are a mix of English (videos and narration) and Spanish (lecture titles, transcripts, readings, labs, and quizzes)
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Reviews summary
Beginner-friendly ai with ibm watson
This introductory course on AI fundamentals using IBM Watson has earned high praise for its accessible content and clear explanations. With no prior programming or computer science experience required, learners of all backgrounds can benefit from its practical demonstrations and real-world examples.
Relevant use cases enhance understanding.
"se familiarizará con sus casos de uso y ejemplos de clientes de la vida real"
Concepts are easy to understand.
"se entiende bien.Gracias a los profesores y a todo el equipo de Coursera.saludosMiriam O"Neil"
Hands-on examples reinforce learning.
"También trabajará con varios servicios de Watson para demostrar la IA en acción."
No prior experience required.
"Este curso no requiere ninguna experiencia en programación o ciencias de la computación y está diseñado para cualquier persona, ya sea que tenga una formación técnica o no."
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 Iniciación A La IA con IBM Watson with these
activities:
Review basics of IBM Watson
Show steps
Reinforce your foundational knowledge of IBM Watson's capabilities and functionalities by reviewing the basics.
Browse courses on
IBM Watson
Show steps
-
Revisit the course materials from previous courses or online resources that cover IBM Watson's core concepts.
-
Attend a webinar or workshop focused on IBM Watson's fundamentals.
-
Complete online tutorials or exercises that provide hands-on practice with IBM Watson's services.
Review prerequisite concepts
Show steps
Strengthen your foundational knowledge by reviewing concepts related to this course.
Browse courses on
Data Analysis
Show steps
-
Revisit introductory programming concepts such as variables, data types, and control structures.
-
Refresh your understanding of data analysis techniques, including data cleaning and visualization.
-
Review the basics of cloud computing platforms and services.
Organize and review course materials
Show steps
Enhance your understanding by organizing and reviewing the materials provided in this course.
Show steps
-
Create a dedicated folder or notebook to store all course materials.
-
Regularly review lecture notes, videos, and assigned readings.
-
Summarize key concepts and create flashcards for better retention.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Review artificial intelligence basics
Show steps
Refreshing your knowledge of foundational artificial intelligence principles will facilitate smoother onboarding with learning the concepts in this course.
Show steps
-
Read over the latest articles and blog posts on major advancements in AI over the last 5 years.
-
Complete practical exercises covering foundational AI topics to revisit the applications of various AI algorithms.
Follow online tutorials and courses
Show steps
Supplement your learning by exploring additional resources and tutorials.
Browse courses on
Online Courses
Show steps
-
Consult the official IBM Watson documentation for in-depth technical information.
-
Enroll in online courses or tutorials offered by IBM or other platforms to gain a structured learning experience.
-
Explore community forums and discussion groups to connect with other IBM Watson users and learn from their experiences.
Experiment with IBM Watson services
Show steps
Solidify your understanding of IBM Watson's services by engaging in practical exercises.
Show steps
-
Explore the Watson Discovery Service by building a simple application that analyzes text data.
-
Utilize the Watson Assistant service to create a chatbot that interacts with users.
-
Experiment with the Watson Speech to Text service by developing an application that converts speech to text.
-
Build a project using the Watson Visual Recognition service to classify images.
IBM Watson API tutorials
Show steps
Completing hands-on tutorials using the IBM Watson API will build familiarity with its functionalities and aid in the development of practical skills.
Show steps
-
Explore the IBM Watson API documentation to familiarize yourself with its different services and applications.
-
Locate relevant tutorials aligning with your interests or learning objectives.
-
Complete the hands-on exercises and activities provided in the tutorials to gain practical experience with the API.
-
Build a small project or experiment using the IBM Watson API to apply your acquired knowledge.
Participate in online AI discussion forums
Show steps
Engaging in discussions with peers will provide diverse perspectives, foster critical thinking, and enhance your understanding of AI concepts.
Show steps
-
Identify online forums or communities focused on AI topics relevant to the course.
-
Actively participate in discussions by sharing your insights, asking thoughtful questions, and responding to others' posts.
-
Engage with the community by providing constructive feedback and support to other members.
Attend AI workshops or webinars
Show steps
Attending AI workshops or webinars will supplement your course learning, provide exposure to industry experts, and offer networking opportunities.
Show steps
-
Research and identify AI workshops or webinars that align with your interests and learning objectives.
-
Register and attend the selected events, actively participating in discussions and taking notes of key insights.
Seek guidance from AI experts
Show steps
Connecting with AI experts can provide valuable mentorship, guidance, and support throughout your learning journey.
Show steps
-
Identify potential mentors within your professional network or through online platforms like LinkedIn.
-
Reach out to your selected mentors, expressing your interest in AI and requesting their guidance.
-
Schedule regular meetings or calls with your mentor to discuss your progress, seek advice, and gain insights from their experiences.
IBM Watson Toolkit Compilation
Show steps
Creating a compilation of tools and resources focused on IBM Watson can deepen your knowledge of the subject and provide a quick reference guide for future use.
Show steps
-
Gather resources such as articles, tutorials, and documentation related to IBM Watson.
-
Organize the resources into categories such as getting started, use cases, and best practices.
-
Develop a brief summary or description for each resource.
-
Consider including your own insights and experiences with IBM Watson.
Coding exercises on AI platforms
Show steps
Engaging in coding exercises on AI platforms will reinforce the concepts learned in the course and enhance your practical abilities.
Show steps
-
Identify AI platforms that offer coding exercises or challenges relevant to the topics covered in the course.
-
Select exercises that align with your skill level and learning objectives.
-
Attempt to solve the coding exercises independently, referring to course materials or online resources for guidance when necessary.
-
Review your solutions and identify areas for improvement, seeking feedback from peers or mentors if needed.
Develop a case study or presentation
Show steps
Deepen your understanding by applying IBM Watson to a real-world business scenario.
Browse courses on
Business Use Cases
Show steps
-
Identify a business problem or opportunity that can be addressed using IBM Watson.
-
Research and select the appropriate IBM Watson services for your project.
-
Develop a prototype or solution that demonstrates the application of IBM Watson.
-
Prepare a presentation or case study that showcases your project and its potential impact.
Contribute to open-source AI projects
Show steps
Contributing to open-source AI projects will provide practical experience, expose you to diverse approaches, and enhance your problem-solving skills.
Show steps
-
Identify open-source AI projects that align with your interests and skillset.
-
Review the project documentation to understand its goals, architecture, and codebase.
-
Select a task or issue that you can contribute to and work on it independently.
-
Submit a pull request with your proposed changes or contributions, addressing any feedback or suggestions provided by the project maintainers.
Review basics of IBM Watson
Show steps
Reinforce your foundational knowledge of IBM Watson's capabilities and functionalities by reviewing the basics.
Browse courses on
IBM Watson
Show steps
Show steps
Show steps
- Revisit the course materials from previous courses or online resources that cover IBM Watson's core concepts.
- Attend a webinar or workshop focused on IBM Watson's fundamentals.
- Complete online tutorials or exercises that provide hands-on practice with IBM Watson's services.
Review prerequisite concepts
Show steps
Strengthen your foundational knowledge by reviewing concepts related to this course.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Revisit introductory programming concepts such as variables, data types, and control structures.
- Refresh your understanding of data analysis techniques, including data cleaning and visualization.
- Review the basics of cloud computing platforms and services.
Organize and review course materials
Show steps
Enhance your understanding by organizing and reviewing the materials provided in this course.
Show steps
Show steps
Show steps
- Create a dedicated folder or notebook to store all course materials.
- Regularly review lecture notes, videos, and assigned readings.
- Summarize key concepts and create flashcards for better retention.
11 other activities
Expand to see all activities and additional details
Show all 14 activities
Review artificial intelligence basics
Show steps
Refreshing your knowledge of foundational artificial intelligence principles will facilitate smoother onboarding with learning the concepts in this course.
Show steps
Show steps
Show steps
- Read over the latest articles and blog posts on major advancements in AI over the last 5 years.
- Complete practical exercises covering foundational AI topics to revisit the applications of various AI algorithms.
Follow online tutorials and courses
Show steps
Supplement your learning by exploring additional resources and tutorials.
Browse courses on
Online Courses
Show steps
Show steps
Show steps
- Consult the official IBM Watson documentation for in-depth technical information.
- Enroll in online courses or tutorials offered by IBM or other platforms to gain a structured learning experience.
- Explore community forums and discussion groups to connect with other IBM Watson users and learn from their experiences.
Experiment with IBM Watson services
Show steps
Solidify your understanding of IBM Watson's services by engaging in practical exercises.
Show steps
Show steps
Show steps
- Explore the Watson Discovery Service by building a simple application that analyzes text data.
- Utilize the Watson Assistant service to create a chatbot that interacts with users.
- Experiment with the Watson Speech to Text service by developing an application that converts speech to text.
- Build a project using the Watson Visual Recognition service to classify images.
IBM Watson API tutorials
Show steps
Completing hands-on tutorials using the IBM Watson API will build familiarity with its functionalities and aid in the development of practical skills.
Show steps
Show steps
Show steps
- Explore the IBM Watson API documentation to familiarize yourself with its different services and applications.
- Locate relevant tutorials aligning with your interests or learning objectives.
- Complete the hands-on exercises and activities provided in the tutorials to gain practical experience with the API.
- Build a small project or experiment using the IBM Watson API to apply your acquired knowledge.
Participate in online AI discussion forums
Show steps
Engaging in discussions with peers will provide diverse perspectives, foster critical thinking, and enhance your understanding of AI concepts.
Show steps
Show steps
Show steps
- Identify online forums or communities focused on AI topics relevant to the course.
- Actively participate in discussions by sharing your insights, asking thoughtful questions, and responding to others' posts.
- Engage with the community by providing constructive feedback and support to other members.
Attend AI workshops or webinars
Show steps
Attending AI workshops or webinars will supplement your course learning, provide exposure to industry experts, and offer networking opportunities.
Show steps
Show steps
Show steps
- Research and identify AI workshops or webinars that align with your interests and learning objectives.
- Register and attend the selected events, actively participating in discussions and taking notes of key insights.
Seek guidance from AI experts
Show steps
Connecting with AI experts can provide valuable mentorship, guidance, and support throughout your learning journey.
Show steps
Show steps
Show steps
- Identify potential mentors within your professional network or through online platforms like LinkedIn.
- Reach out to your selected mentors, expressing your interest in AI and requesting their guidance.
- Schedule regular meetings or calls with your mentor to discuss your progress, seek advice, and gain insights from their experiences.
IBM Watson Toolkit Compilation
Show steps
Creating a compilation of tools and resources focused on IBM Watson can deepen your knowledge of the subject and provide a quick reference guide for future use.
Show steps
Show steps
Show steps
- Gather resources such as articles, tutorials, and documentation related to IBM Watson.
- Organize the resources into categories such as getting started, use cases, and best practices.
- Develop a brief summary or description for each resource.
- Consider including your own insights and experiences with IBM Watson.
Coding exercises on AI platforms
Show steps
Engaging in coding exercises on AI platforms will reinforce the concepts learned in the course and enhance your practical abilities.
Show steps
Show steps
Show steps
- Identify AI platforms that offer coding exercises or challenges relevant to the topics covered in the course.
- Select exercises that align with your skill level and learning objectives.
- Attempt to solve the coding exercises independently, referring to course materials or online resources for guidance when necessary.
- Review your solutions and identify areas for improvement, seeking feedback from peers or mentors if needed.
Develop a case study or presentation
Show steps
Deepen your understanding by applying IBM Watson to a real-world business scenario.
Browse courses on
Business Use Cases
Show steps
Show steps
Show steps
- Identify a business problem or opportunity that can be addressed using IBM Watson.
- Research and select the appropriate IBM Watson services for your project.
- Develop a prototype or solution that demonstrates the application of IBM Watson.
- Prepare a presentation or case study that showcases your project and its potential impact.
Contribute to open-source AI projects
Show steps
Contributing to open-source AI projects will provide practical experience, expose you to diverse approaches, and enhance your problem-solving skills.
Show steps
Show steps
Show steps
- Identify open-source AI projects that align with your interests and skillset.
- Review the project documentation to understand its goals, architecture, and codebase.
- Select a task or issue that you can contribute to and work on it independently.
- Submit a pull request with your proposed changes or contributions, addressing any feedback or suggestions provided by the project maintainers.
Career center
Learners who complete Iniciación A La IA con IBM Watson will develop knowledge and skills
that may be useful to these careers:
AI Engineer
AI Engineer
AI Engineers design, develop, and maintain AI systems. This course introduces the principles of AI with Watson, equipping you with the knowledge and skills needed to succeed in this emerging field. By learning about Watson's capabilities and case studies, you will gain insights into the practical applications of AI.
Data Scientist
Data Scientist
Data Scientists are experts in extracting knowledge and insights from data, enabling organizations to make informed decisions. This course introduces the fundamentals of AI with IBM Watson, an essential tool for modern Data Scientists. By learning about Watson's capabilities and real-world applications, you will gain a competitive edge in this rapidly evolving field.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and deploy ML models to solve complex problems. This course provides a foundation in AI and Watson, empowering you to create intelligent applications. By working with Watson's ML services, you will gain hands-on experience essential for success in this in-demand role.
Data Analyst
Data Analyst
Data Analysts transform raw data into meaningful insights. This course provides an introduction to AI with IBM Watson, empowering you to enhance your data analysis skills. By learning about Watson's capabilities and examples of its use, you will gain a competitive edge in the modern data analytics landscape.
Software Developer
Software Developer
Software Developers create and maintain software programs. This course provides a foundation in AI with IBM Watson, a valuable tool for modern Software Developers. By learning about Watson's capabilities and how it can be integrated into applications, you will gain the skills needed to build cutting-edge software solutions.
AI Researcher
AI Researcher
AI Researchers explore new frontiers in artificial intelligence. This course introduces the fundamentals of AI with IBM Watson, a powerful tool for AI research. By learning about Watson's capabilities and case studies, you will gain insights into the latest AI advancements and contribute to shaping the future of this field.
Product Manager
Product Manager
Product Managers bring new products and features to market. This course provides foundational knowledge in AI with IBM Watson, an essential technology for modern products. By learning about Watson's capabilities and use cases, you will gain the insights needed to develop innovative AI-powered products that meet market demands.
Business Analyst
Business Analyst
Business Analysts identify and solve business problems. This course introduces the concepts of AI with IBM Watson, a powerful tool for modern Business Analysts. By learning about Watson's capabilities and applications, you will gain the skills needed to analyze business data, identify opportunities, and recommend AI-driven solutions.
Consultant
Consultant
Consultants advise businesses on various aspects of their operations. This course provides an introduction to AI with IBM Watson, a valuable tool for modern Consultants. By learning about Watson's capabilities and case studies, you will gain insights into the practical applications of AI and become a trusted advisor to businesses seeking to transform their operations.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation. This course provides foundational knowledge in AI with IBM Watson, an emerging technology relevant to technical documentation. By learning about Watson's capabilities and examples of its use, you will be able to effectively communicate complex AI concepts and contribute to the dissemination of AI knowledge.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing strategies. This course provides an overview of AI with IBM Watson, a tool that can enhance marketing campaigns. By learning about Watson's capabilities and case studies, you will gain insights into using AI to personalize marketing messages, analyze customer data, and optimize campaign performance.
Project Manager
Project Manager
Project Managers plan and execute projects. This course introduces the basics of AI with IBM Watson, a technology that can enhance project management processes. By learning about Watson's capabilities and applications, you will gain insights into using AI to improve project planning, resource allocation, and risk management.
Customer Success Manager
Customer Success Manager
Customer Success Managers ensure customer satisfaction and retention. This course provides an introduction to AI with IBM Watson, a tool that can enhance customer support. By learning about Watson's capabilities and applications, you will gain insights into using AI to personalize customer experiences, resolve issues quickly, and build strong customer relationships.
Sales Manager
Sales Manager
Sales Managers lead and motivate sales teams. This course introduces the principles of AI with IBM Watson, a technology that can improve sales processes. By learning about Watson's capabilities and applications, you will gain insights into using AI to identify potential customers, optimize sales pipelines, and close deals more effectively.
Financial Analyst
Financial Analyst
Financial Analysts provide insights into financial data. This course introduces the concepts of AI with IBM Watson, a tool that can enhance financial analysis. By learning about Watson's capabilities and applications, you will gain insights into using AI to analyze market trends, identify investment opportunities, and make informed financial decisions.
For more career information including salaries, visit:
OpenCourser.com/course/5pw1rk/iniciacion
Reading list
We've selected 15 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
Iniciación A La IA con IBM Watson.
Provides a comprehensive and beginner-friendly introduction to artificial intelligence (AI). It covers the basics of AI, including machine learning, deep learning, and natural language processing, making it a great starting point for those with little to no background in the field.
A classic textbook that covers a broad range of topics in AI, including search, logic, planning, and machine learning. It provides a comprehensive overview of the field and serves as a valuable reference for both students and practitioners.
Save
An authoritative reference for deep learning, providing a thorough understanding of deep neural networks, convolutional neural networks, and recurrent neural networks. Ideal for those interested in exploring the theoretical foundations of deep learning.
A classic textbook that provides a comprehensive overview of AI, covering topics such as knowledge representation, reasoning, and problem-solving. It serves as a valuable reference for both students and practitioners.
A practical guide to natural language processing (NLP) using Python. It covers a wide range of NLP tasks, including text classification, sentiment analysis, and machine translation, making it suitable for those interested in developing NLP applications.
A practical guide to machine learning using popular Python libraries. It covers data preprocessing, model training, and evaluation, making it suitable for those who want to apply machine learning techniques to real-world problems.
A practical guide to deep learning using the Fastai and PyTorch libraries. It provides hands-on examples and exercises, making it suitable for both beginners and experienced practitioners who want to build deep learning models quickly and efficiently.
A practical guide to building and training deep learning models using the Keras library. It's written by the creator of Keras and provides valuable insights into the design and implementation of deep learning models.
A comprehensive guide to machine learning using Python. It covers a wide range of topics, from data preprocessing to model evaluation, and provides practical examples and exercises, making it suitable for both beginners and experienced practitioners.
A practical guide to machine learning for non-programmers. It provides an accessible introduction to the concepts and techniques of machine learning, making it suitable for those with little to no technical background.
Focuses on understanding and explaining the inner workings of machine learning models. It provides techniques for visualizing and interpreting models, helping practitioners gain confidence in their predictions and make informed decisions.
A comprehensive reference for statistical learning, which is the foundation for many machine learning algorithms. It covers topics such as linear and generalized linear models, regression, and classification, making it a valuable resource for practitioners who want to understand the statistical underpinnings of machine learning.
An introduction to reinforcement learning, a type of machine learning that involves training an agent to make optimal decisions in an environment. It's a valuable resource for those interested in developing AI systems that can learn from their interactions with the world.
Provides a comprehensive overview of the mathematical foundations of machine learning. It covers topics such as linear algebra, probability theory, and optimization, making it suitable for those interested in understanding the theoretical underpinnings of the field.
Provides a comprehensive overview of probabilistic graphical models, a powerful tool for representing and reasoning about complex relationships among variables. It's a valuable resource for those interested in the theoretical foundations of AI.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5pw1rk/iniciacion
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Via
Coursera
Institutions
IBM
IBM Skills Network
Instructor
Rav Ahuja
Good to know
Teaches introductory artificial intelligence (AI) concepts and IBM Watson's AI services
Provides a good starting point for beginners in AI
Emphasizes practical applications of AI in various fields
Involves hands-on activities and demonstrations with IBM Watson services
Accessible to learners without prior programming or computer science experience
Course materials are a mix of English (videos and narration) and Spanish (lecture titles, transcripts, readings, labs, and quizzes)
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