Number of questions: 60
Number of questions to pass: 44
Time allowed: 90 mins
Status: Live This exam consists of 5 sections described below.
Section 1 – Fundamentals of Artificial Intelligence (AI) Computing
Define the main characteristics of an AI system.
Explain neural nets.
Explain Machine Learning technologies (supervised, unsupervised, reinforcement
learning approaches).
Define a common set of use cases for AI systems.
Define Precision, Recall, and Accuracy
Explain the importance of separating training, validation and test data.
Measure accuracy of a Watson AI service.
Perform Domain Adaption using Watson Knowledge Studio (WKS).
Define Intents and Classes.
Identify the difference between the user question and the user intent.
Section 2 – Use Cases for Artificial Intelligence
Select an appropriate combination of AI technologies based on use-case and
data format.
Explain the uses of the Watson AI services in the Starter Kits.
Describe the Watson Conversational Agent.
Explain use cases for integrating external systems (such as Twitter, Weather
API).
Describe the IBM Watson Discovery Service
Section 3 – Fundamentals of IBM Watson AI services
Distinguish the Watson AI services on IBM Cloud for which training is
required.
Provide examples of text classification using the NLC.
Explain the Watson SDKs available as part of the Watson AI services on IBM
Cloud.
Explain the Watson REST APIs available as part of the Watson AI services on IBM
Cloud.
Explain and configure the Natural Language Classification service.
Explain and configure the Visual Recognition service.
Explain how the Personality Insights service works.
Explain how the Tone Analyzer service works.
Explain and execute IBM Watson Natural Language Understanding service.
Explain, setup, configure and query the IBM Watson Discovery service.
Explain and configure the IBM Watson Assistant service
Section 4 – Developing AI applications using IBM Watson AI Services on IBM
Cloud
Call a Watson API to analyze content.
Describe the tasks required to implement the Conversational Agent / Digital Bot.
Transform service outputs for consumption by other services.
Define common design patterns for composing multiple Watson services together
(across APIs).
Design and execute a use case driven service choreography (within an API).
Explain the process to provision and use an instance of an IBM Watson AI service
instance on IBM Cloud.
Explain the advantages of using IBM Cloud as the cloud platform for AI
application development and deployment.
Section 5 �?? Administration & DevOps for applications using IBM Watson AI
services on IBM Cloud
Describe the process of obtaining credentials for Watson AI services on IBM
Cloud.
Examine application logs provided on IBM Cloud.
Use the study guide to help pass this exam. A study guide is an easy to
follow document that will help you prepare for this exam. The guide is free and
can be downloaded immediately.
This exam has an Assessment Exam option: A1000-012 Assessment: IBM Watson
Application Developer V3.1
Assessment exams are web-based exams that provides you, at a cheaper costs, the
ability to check your skills before taking the certification exam.
This assessment exam is available in: English
Passing the exam does not award you a certification, and it is only used to help
you assess if you are ready or not to take the certification exam.
You can register for it at Pearson VUE and it will provide you a score report,
showing you how you did in each section.
Courses and publications are offered to help you prepare for the certification
tests. The courses are recommended, but not required, before taking a
certification test. When preparing for the certification test, keep in mind that
real world experience is required to stand a reasonable chance of passing the
certification test. Courseware does not replace the requirement for experience.
Please note that course offerings are continuously being added and updated. If
you want to purchase a training course, feel free to contact an IBM Global
Training Provider.
1 Web Resource
Course Title: IBM Watson Application Developer Certification Bootcamp
Course Duration: 24 hours
Course Number: U66971G
Course Abstract: This course provides a basic understanding of AI technologies,
practical knowledge of the core Watson APIs, and how your application can use
these services. You will also review additional concepts included in the IBM
Derivative Works Courses are developed by an IBM authorized Global Training
Provider. The content of the course is based on IBM products and services. It
offers skills or services that IBM does not offer in the course catalog today an
are intended to compliment our existing portfolio. The course is developed by
the Training Provider. IBM solely provides a market place to advertise the
courses on our external websites, ibm.com/training and lists the Global Training
Provider who owns the content.
Overview
PartnerWorld Code: 60000101
Replaces PW Code: 60000101
Status: Live
This intermediate level technical professional is an individual who
understands concepts essential to the development of applications using IBM
Watson AI services. They will have experience using the IBM Cloud and are able
to consume IBM Watson AI services in an application. This individual is able to
perform these tasks with little to no assistance from product documentation,
support or peers.
Key Areas of Competency:
Fundamentals of IBM Watson AI services on IBM Cloud
Use cases of Artificial Intelligence and Machine Learning
Developing AI applications using IBM Watson AI services
Administering applications using IBM Watson AI services
Recommended Prerequisite Skills
Working knowledge of developing an application using IBM Watson AI services
Working knowledge of core IBM Cloud services (monitoring, logging, scaling), and
security
Working knowledge with designing, developing and deploying RESTful APIs
Working knowledge of use cases using IBM Watson AI services
Working knowledge of AI concepts such as intent, relationships, entities, and
ground truth
Working knowledge of the application starter kits and demos available on the IBM
Cloud
Working knowledge of open technologies like Cloud Foundry and Git like
repositories
Basic knowledge of application development using common web technologies such as
Node.js, Javascript, HTML, and CSS
Basic knowledge of machine learning methods and technologies
Question: 1
What Watson solution can answer common support questions typically handled by a
live agent?
A. Tone Analyzer
B. Watson Assistant
C. Natural Language Understanding
D. Language Translator
Answer: C
Question: 2
An AI solution is implemented to detect what the user wants to do. The user
mentions that he wants to buy a ski jacket for an upcoming vacation in Colorado.
How can the entities be derived from the conversation using IBM Watson services?
A. Upload training data to the Discovery service and use the Discovery API to
query the results
B. Use the Tone Analyzer service to retrieve the level of openness in the
utterance
C. Pass the utterance from the user to the Natural Language Understanding
service Entities API
D. Pass the utterance from the user through Speech to Text then apply Tradeoff
Analytics
Answer: C
Question: 3
What are examples of the information the IBM Watson Natural Language
Understanding service extract from html, or web-based content when it analyzes
entities?
A. text and title information
B. people, companies, organizations
C. subject-action-object relations
D. topic keywords
Answer: C
Question: 4
Built into the IBM Watson Discovery service is the Watson Discovery News
data set. How is this collection different from other collections?
A. The Watson Discovery News configuration and documents cannot be adjusted
B. Documents from the Watson Discovery News collection can be ingested as sample
documents to better configure a private collection
C. The Watson Discovery News collection is specific to the company news domain,
whereas a collection is specific to a domain.
D. The Watson Discovery News data set and a private collection can be queried
with a single query call
Answer: B
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