IBM Watson Analytics is an advanced data analysis and visualization solution in the cloud that guides you through analysis and discovery of your data.
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IBM Watson Analytics is an advanced data analysis and visualization solution in the cloud that guides you through analysis and discovery of your data.
IBM Watson Analytics is an advanced data analysis and visualization solution in the cloud that guides you through analysis and discovery of your data.
Watson Analytics is a smart data analysis and visualization service you can use to quickly discover patterns and meaning in your data – all on your own. With guided data discovery, automated predictive analytics and cognitive capabilities such as natural language dialogue, you can interact with data conversationally to get answers you understand. Whether you need to quickly spot a trend or you have a team that needs to visualize report data in a dashboard, Watson Analytics has you covered.
In this course, students will learn the fundamentals of Watson Analytics and become proficient with Watson's tools. Students will learn how to use features such as machine learning and predictive analytics.
We will get into how to import and refine data from local or cloud-based sources; build new calculations, hierarchies, and data groups on the fly; and leverage cognitive starting points, natural language queries, and dynamic insights. Find out how to auto-detect trends and correlations and generate predictive models and decision trees quickly. Plus, learn how to create and share visualizations, dashboards, and infographics to bring your insights to life.
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What's inside
Learning objectives
- Learn the fundamentals of watson analytics
- Importing, joining, and refining data
- Using natural language querying
- Understanding key drivers
- Data, discovery, and display
- Displaying insights and interpreting decision trees
- Learn the fundamentals of watson analytics
- Importing, joining, and refining data
- Using natural language querying
- Understanding key drivers
- Data, discovery, and display
- Displaying insights and interpreting decision trees
Syllabus
What is Watson Analytics
Introduction
Welcome
Getting started
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Syllabus
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Activities
Consolidate Course Materials for Easy Reference
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Organize and review course materials to improve comprehension and retention.
Show steps
-
Download and organize lecture slides, assignments, and other course materials
-
Create a study guide or summary sheet to consolidate key concepts
-
Review materials regularly to reinforce understanding
Review Data Analysis Fundamentals
Show steps
Strengthen your foundation in data analysis concepts and techniques to enhance your learning in Watson Analytics.
Browse courses on
Data Analysis
Show steps
-
Review basic data analysis concepts and techniques
-
Practice working with different data structures and data types
-
Use statistical tools and techniques to analyze data
Review Machine Learning Concepts
Show steps
Refresh your knowledge of machine learning concepts and algorithms to enhance your understanding of Watson Analytics' predictive capabilities.
Browse courses on
Machine Learning
Show steps
-
Review supervised learning algorithms, such as linear regression and decision trees
-
Understand the process of training and evaluating machine learning models
-
Explore different machine learning libraries and tools
Five other activities
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Join Discussion Forums for Collaborative Learning
Show steps
Engage with peers to exchange ideas, clarify concepts, and gain diverse perspectives on course topics.
Show steps
-
Join discussion forums related to Watson Analytics
-
Participate in discussions, asking questions and sharing insights
-
Review and contribute to discussions initiated by other participants
Explore Watson Analytics Insights and Key Drivers
Show steps
Enhance your understanding of Watson Analytics' capabilities by following guided tutorials on utilizing insights and identifying key drivers.
Show steps
-
Use natural language queries to ask questions about your data
-
Explore cognitive starting points to uncover hidden insights
-
Identify key drivers that influence your data's behavior
Build Data Visualizations Using Watson Analytics
Show steps
Develop your skills in creating interactive data visualizations using Watson Analytics to bring insights to life.
Browse courses on
Data Visualization
Show steps
-
Create a data visualization from scratch
-
Customize the visualization with different chart types and colors
-
Add interactivity to the visualization using custom filters and drill-downs
Develop a Predictive Model Using Machine Learning
Show steps
Apply your knowledge of machine learning and predictive analytics to build a predictive model that can make forecasts and identify trends.
Browse courses on
Machine Learning
Show steps
-
Choose a suitable machine learning algorithm
-
Train the model using historical data
-
Evaluate the model's performance and make necessary adjustments
Develop a Data Analytics Project
Show steps
Apply your skills by initiating a data analytics project to solve a real-world problem or explore a topic of interest.
Browse courses on
Data Analytics
Show steps
-
Define the project scope and goals
-
Gather and prepare data
-
Analyze data using Watson Analytics and other tools
-
Develop insights and recommendations
-
Present findings and communicate results
Consolidate Course Materials for Easy Reference
Show steps
Organize and review course materials to improve comprehension and retention.
Show steps
- Download and organize lecture slides, assignments, and other course materials
- Create a study guide or summary sheet to consolidate key concepts
- Review materials regularly to reinforce understanding
Review Data Analysis Fundamentals
Show steps
Strengthen your foundation in data analysis concepts and techniques to enhance your learning in Watson Analytics.
Browse courses on
Data Analysis
Show steps
- Review basic data analysis concepts and techniques
- Practice working with different data structures and data types
- Use statistical tools and techniques to analyze data
Review Machine Learning Concepts
Show steps
Refresh your knowledge of machine learning concepts and algorithms to enhance your understanding of Watson Analytics' predictive capabilities.
Browse courses on
Machine Learning
Show steps
- Review supervised learning algorithms, such as linear regression and decision trees
- Understand the process of training and evaluating machine learning models
- Explore different machine learning libraries and tools
Join Discussion Forums for Collaborative Learning
Show steps
Engage with peers to exchange ideas, clarify concepts, and gain diverse perspectives on course topics.
Show steps
- Join discussion forums related to Watson Analytics
- Participate in discussions, asking questions and sharing insights
- Review and contribute to discussions initiated by other participants
Explore Watson Analytics Insights and Key Drivers
Show steps
Enhance your understanding of Watson Analytics' capabilities by following guided tutorials on utilizing insights and identifying key drivers.
Show steps
- Use natural language queries to ask questions about your data
- Explore cognitive starting points to uncover hidden insights
- Identify key drivers that influence your data's behavior
Build Data Visualizations Using Watson Analytics
Show steps
Develop your skills in creating interactive data visualizations using Watson Analytics to bring insights to life.
Browse courses on
Data Visualization
Show steps
- Create a data visualization from scratch
- Customize the visualization with different chart types and colors
- Add interactivity to the visualization using custom filters and drill-downs
Develop a Predictive Model Using Machine Learning
Show steps
Apply your knowledge of machine learning and predictive analytics to build a predictive model that can make forecasts and identify trends.
Browse courses on
Machine Learning
Show steps
- Choose a suitable machine learning algorithm
- Train the model using historical data
- Evaluate the model's performance and make necessary adjustments
Develop a Data Analytics Project
Show steps
Apply your skills by initiating a data analytics project to solve a real-world problem or explore a topic of interest.
Browse courses on
Data Analytics
Show steps
- Define the project scope and goals
- Gather and prepare data
- Analyze data using Watson Analytics and other tools
- Develop insights and recommendations
- Present findings and communicate results
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