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IBM C1000-012 Exam Syllabus Topics:

Topic	Details
Topic 1	Explain Machine Learning Technologies (Supervised, Unsupervised, Reinforcement Learning Approaches) Explain Neural Nets
Topic 2	Define Common Design Patterns For Composing Multiple Watson Services Together (Across Apis) Explain And Configure The IBM Watson Assistant Service
Topic 3	Provide Examples Of Text Classification Using The NLC Describe The IBM Watson Discovery Service Describe The Watson Conversational Agent
Topic 4	Explain The Advantages Of Using IBM Cloud As The Cloud Platform For AI Application Development And Deployment Call A Watson API To Analyze Content
Topic 5	Developing AI Applications Using IBM Watson AI Services On IBM Cloud Explain How The Tone Analyzer Service Works
Topic 6	Measure Accuracy Of A Watson AI Service Define Precision, Recall, And Accuracy Define Intents And Classes
Topic 7	Explain And Execute IBM Watson Natural Language Understanding Service Explain, Setup, Configure And Query The IBM Watson Discovery Service
Topic 8	Select An Appropriate Combination Of AI Technologies Based On Use-Case And Data Format Use Cases For Artificial Intelligence
Topic 9	Explain And Configure The Natural Language Classification Service Explain And Configure The Visual Recognition Service
Topic 10	Explain The Process To Provision And Use An Instance Of An IBM Watson AI Service Instance On IBM Cloud Explain How The Personality Insights Service Works
Topic 11	Explain The Watson REST Apis Available As Part Of The Watson AI Services On IBM Cloud Fundamentals Of IBM Watson AI Services
Topic 12	Fundamentals Of Artificial Intelligence (AI) Computing Define A Common Set Of Use Cases For AI Systems