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Rav Ahuja
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
Read more
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
Read more
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
In this course, you will learn how to quickly and easily get started with Artificial Intelligence using IBM Watson. You will understand how Watson works, become familiar with its use cases and real-life client examples, and be introduced to several Watson AI services from IBM that enable anyone to easily apply AI and build smart apps.
You will also work with several Watson services including Watson studio, Watson assistant and Watson discovery to demonstrate AI in action.
This course does not require any programming or computer science expertise and is designed for anyone whether you have a technical background or not.
Register for this course and see more details by visiting:
OpenCourser.com/course/c8c6o0/introduction
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What's inside
Learning objectives
- Fundamentals of ai and watson machine learning
- How ibm watson ai works
- Watson ai services offered on the ibm cloud and how organizations use these services
- Common use cases for ai
- Experience and demonstrate ai in action yourself using watson
- Fundamentals of ai and watson machine learning
- How ibm watson ai works
- Watson ai services offered on the ibm cloud and how organizations use these services
- Common use cases for ai
- Experience and demonstrate ai in action yourself using watson
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a strong foundation for beginners who want to learn about AI and its applications
Features hands-on labs and interactive materials to enhance practical understanding
Leverages IBM Watson AI services, which are widely used in industry
Offered by Rav Ahuja, an experienced instructor known for AI expertise
Requires no prior programming or computer science knowledge, making it accessible to a broad audience
Does not require extensive background knowledge, making it suitable for learners with various backgrounds
Save this course
Save Introduction to Watson AI to your list so you can find it easily later:
Save
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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 Introduction to Watson AI with these
activities:
Read Artificial Intelligence for Dummies
Show steps
Familiarize yourself with the fundamentals of AI and machine learning.
View
Artificial Intelligence For Dummies (For...
on Amazon
Show steps
-
Scan the introduction and table of contents.
-
Read chapters 1-3.
-
Complete the practice exercises at the end of each chapter.
Organize your notes and materials
Show steps
Keep your notes and materials well-organized for easy review.
Show steps
-
Create a dedicated folder for course materials.
-
File all notes, assignments, and quizzes in the folder.
-
Review your materials regularly.
Join an AI study group
Show steps
Learn from and collaborate with other students who are interested in AI.
Show steps
-
Find a study group or create your own.
-
Meet regularly to discuss course material.
-
Work on projects together.
Three other activities
Expand to see all activities and additional details
Show all six activities
Complete the IBM Watson Tutorial
Show steps
Gain hands-on experience with Watson's AI services.
Show steps
-
Sign up for an IBM Cloud account.
-
Follow the steps in the IBM Watson Tutorial.
-
Experiment with the different AI services.
Contribute to an open-source AI project
Show steps
Gain practical experience and learn from the AI community.
Browse courses on
Collaborative Learning
Show steps
-
Find an open-source AI project that you are interested in.
-
Read the project documentation.
-
Start contributing to the project.
Build an AI chatbot
Show steps
Apply your AI knowledge to build a working chatbot.
Show steps
-
Choose a chatbot platform.
-
Design the chatbot's conversation flow.
-
Build the chatbot using AI techniques.
-
Test and deploy the chatbot.
Read Artificial Intelligence for Dummies
Show steps
Familiarize yourself with the fundamentals of AI and machine learning.
View
Artificial Intelligence For Dummies (For...
on Amazon
Show steps
Show steps
Show steps
- Scan the introduction and table of contents.
- Read chapters 1-3.
- Complete the practice exercises at the end of each chapter.
Organize your notes and materials
Show steps
Keep your notes and materials well-organized for easy review.
Show steps
Show steps
Show steps
- Create a dedicated folder for course materials.
- File all notes, assignments, and quizzes in the folder.
- Review your materials regularly.
Join an AI study group
Show steps
Learn from and collaborate with other students who are interested in AI.
Show steps
Show steps
Show steps
- Find a study group or create your own.
- Meet regularly to discuss course material.
- Work on projects together.
Three other activities
Expand to see all activities and additional details
Show all six activities
Complete the IBM Watson Tutorial
Show steps
Gain hands-on experience with Watson's AI services.
Show steps
Show steps
Show steps
- Sign up for an IBM Cloud account.
- Follow the steps in the IBM Watson Tutorial.
- Experiment with the different AI services.
Contribute to an open-source AI project
Show steps
Gain practical experience and learn from the AI community.
Browse courses on
Collaborative Learning
Show steps
Show steps
Show steps
- Find an open-source AI project that you are interested in.
- Read the project documentation.
- Start contributing to the project.
Build an AI chatbot
Show steps
Apply your AI knowledge to build a working chatbot.
Show steps
Show steps
Show steps
- Choose a chatbot platform.
- Design the chatbot's conversation flow.
- Build the chatbot using AI techniques.
- Test and deploy the chatbot.
Career center
Learners who complete Introduction to Watson AI will develop knowledge and skills
that may be useful to these careers:
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and maintain AI systems. They typically have a strong background in computer science and mathematics. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI engineering.
AI Researcher
AI Researcher
AI Researchers develop new AI algorithms and techniques. They typically have a strong background in computer science, mathematics, and statistics. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI research.
AI Consultant
AI Consultant
AI Consultants help organizations adopt and implement AI solutions. They typically have a strong background in computer science, mathematics, and business. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI consulting.
AI Architect
AI Architect
AI Architects are responsible for designing and implementing AI solutions that meet the needs of an organization. They typically have a strong background in computer science, mathematics, and business. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI architecture.
AI Project Manager
AI Project Manager
AI Project Managers plan and execute AI projects. They typically have a strong background in project management and computer science. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI project management.
AI Developer
AI Developer
AI Developers design, develop, and maintain AI applications. They typically have a strong background in computer science and mathematics. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI development.
AI Analyst
AI Analyst
AI Analysts gather, analyze, and interpret data to identify trends and patterns. They typically have a strong background in mathematics, statistics, and business. This course provides an introduction to IBM's Watson, a collection of AI services. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in AI analysis.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, implement, and maintain machine learning systems. They typically have a strong background in computer science, mathematics, and statistics. This course provides an introduction to IBM's Watson, a collection of AI services, and also introduces machine learning fundamentals. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in machine learning engineering.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. They typically have a strong background in computer science and engineering. This course provides an introduction to IBM's Watson, a collection of AI services that are available on the cloud. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in cloud architecture.
Business Analyst
Business Analyst
Business Analysts gather and analyze data to identify business problems and opportunities. They typically have a strong background in business and mathematics. This course provides an introduction to IBM's Watson, a collection of AI services that can be used to analyze data and solve business problems. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in business analysis.
Data Architect
Data Architect
Data Architects design and implement data management solutions. They typically have a strong background in computer science and mathematics. This course provides an introduction to IBM's Watson, a collection of AI services that can be used to manage and analyze data. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in data architecture.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They typically have a strong background in computer science. This course provides an introduction to IBM's Watson, a collection of AI services that can be used to develop AI-powered applications. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in software engineering.
Data Analyst
Data Analyst
As a Data Analyst, your job is to examine data and translate it into useful, actionable insights. Expertise in AI and machine learning is strongly desired. The knowledge acquired in this Introduction to Watson AI course may help build a foundation for a career in data analysis. The course will help you understand how Watson AI works, and you will also gain experience using Watson services such as Watson Studio, Watson Assistant, and Watson Discovery.
IT Consultant
IT Consultant
IT Consultants help organizations adopt and implement new technologies. They typically have a strong background in computer science and business. This course provides an introduction to IBM's Watson, a collection of AI services that can be used to solve a variety of business problems. It covers a variety of topics including: natural language processing, computer vision, and predictive analytics. This course may be useful for someone seeking a career in IT consulting.
Data Scientist
Data Scientist
A Data Scientist specializes in extracting insights and solving business problems through data analysis. Familiarity with AI and machine learning is a requirement for success in this role. This course provides an introduction to IBM's Watson, a collection of AI services. It covers the fundamentals of AI, including machine learning, and provides hands-on experience with Watson services. This course may be useful for someone seeking a career in data science.
For more career information including salaries, visit:
OpenCourser.com/course/c8c6o0/introduction
Reading list
We've selected 12 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
Introduction to Watson AI.
Provides a comprehensive overview of AI, including its history, different types, and applications. It good starting point for learners who want to understand the basics of AI before diving deeper into Watson AI.
Provides a comprehensive overview of machine learning from a probabilistic perspective, covering a wide range of topics from Bayesian inference to Markov chain Monte Carlo. It good choice for learners who want to learn how to use probabilistic methods to build real-world applications.
Provides a comprehensive overview of pattern recognition and machine learning, covering a wide range of topics from supervised learning to unsupervised learning. It good choice for learners who want to learn how to use pattern recognition and machine learning to build real-world applications.
Provides a comprehensive overview of information theory, inference, and learning algorithms, covering a wide range of topics from entropy to Bayesian networks. It good choice for learners who want to learn how to use information theory to build real-world applications.
Save
Provides a comprehensive overview of deep learning, covering the basics of neural networks, convolutional neural networks, and recurrent neural networks. It good choice for learners who want to learn more about the mathematical and computational foundations of AI.
Provides a hands-on guide to machine learning using popular Python libraries such as Scikit-Learn, Keras, and TensorFlow. It good choice for learners who want to learn how to use machine learning to build real-world applications.
Provides a practical guide to deep learning using the Python programming language. It covers the basics of deep learning, as well as more advanced topics such as convolutional neural networks and recurrent neural networks. It good choice for learners who want to learn how to use deep learning to build real-world applications.
Provides a comprehensive overview of reinforcement learning, covering a wide range of topics from Markov decision processes to deep reinforcement learning. It good choice for learners who want to learn how to use reinforcement learning to build real-world applications.
Provides a comprehensive overview of Bayesian reasoning and machine learning, covering a wide range of topics from Bayesian probability to Gaussian processes. It good choice for learners who want to learn how to use Bayesian reasoning to build real-world applications.
Provides a gentle introduction to machine learning, covering the basics of supervised and unsupervised learning. It good choice for learners who have no prior experience with machine learning.
Provides a comprehensive overview of speech and language processing, covering a wide range of topics from speech recognition to natural language understanding. It good choice for learners who want to learn how to use speech and language processing to build real-world applications.
Provides a comprehensive overview of natural language processing, covering a wide range of topics from text classification to machine translation. It good choice for learners who want to learn how to use natural language processing to build real-world applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/c8c6o0/introduction
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Effort
4 to 8 hours per week for 8 weeks
Level
Introductory
Via
edX
Institution
IBM
Instructor
Rav Ahuja
Language
English
Transcript
English
Good to know
Provides a strong foundation for beginners who want to learn about AI and its applications
Features hands-on labs and interactive materials to enhance practical understanding
Leverages IBM Watson AI services, which are widely used in industry
Offered by Rav Ahuja, an experienced instructor known for AI expertise
Requires no prior programming or computer science knowledge, making it accessible to a broad audience
Does not require extensive background knowledge, making it suitable for learners with various backgrounds
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