This document provides a sample exam for the EXIN BCS Artificial Intelligence Essentials certification. The sample exam includes 10 multiple choice questions related to key concepts in artificial intelligence. It also includes the answers and an evaluation showing the correct response for each question. The full certification exam would include 20 questions to be completed within 30 minutes with a passing score of 13 correct answers or more.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , Categories of AI, Types of AI, disadvantages , benefits , applications .
We hope it to be useful .
Introduction to artifcial intelligence
Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. 'Strong' AI is usually labelled as AGI (Artificial General Intelligence) while attempts to emulate 'natural' intelligence have been called ABI (Artificial Biological Intelligence). Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[3] Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving"
Career Guidance is the process of helping people to choose a career development in making and implementing informed educational and occupational choices.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , Categories of AI, Types of AI, disadvantages , benefits , applications .
We hope it to be useful .
Introduction to artifcial intelligence
Artificial intelligence (AI) is intelligence demonstrated by machines, unlike the natural intelligence displayed by humans and animals, which involves consciousness and emotionality. The distinction between the former and the latter categories is often revealed by the acronym chosen. 'Strong' AI is usually labelled as AGI (Artificial General Intelligence) while attempts to emulate 'natural' intelligence have been called ABI (Artificial Biological Intelligence). Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals.[3] Colloquially, the term "artificial intelligence" is often used to describe machines (or computers) that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving"
Career Guidance is the process of helping people to choose a career development in making and implementing informed educational and occupational choices.
Artificial Intelligence And Machine Learning PowerPoint Presentation Slides C...SlideTeam
Artificial Intelligence And Machine Learning PowerPoint Presentation Slides arrange insightful data using industry-best design practices. Highlight the differences between machine intelligence, machine learning, and deep learning through our PPT format. Utilize this PowerPoint slideshow to present advantages, disadvantages, learning techniques, and types of supervised machine learning. Further, cover the merits, demerits, and types of unsupervised machine learning. Communicate important details concerning reinforcement learning. Familiarize your viewers with the expert system in artificial intelligence. Outline examples, characteristics, constituents, uses, advantages, drawbacks, and other aspects of the expert system. Compile the deep learning process, recurrent neural networks, and convolutional neural networks through this PowerPoint theme. Present an impactful introduction to artificial intelligence. Introduce kinds, algorithms, trends, and use cases of artificial intelligence. This presentation is not only easy-to-follow but also very convenient to edit, even if you have no prior design experience. Smash the download button and start instant personalization. Our Artificial Intelligence And Machine Learning PowerPoint Presentation Slides Complete Deck are explicit and effective. They combine clarity and concise expression. https://bit.ly/3hKg7PV
Artificial Intelligence in e-commerce sector. This ppt explain that how can artificial intelligence helps in the growth of E-commerce industry. It includes pros and cons also.
Ever since the companies have realized that the regular software are not going to address the growing competition and that they need something additional to pull them, concepts like Data Science and Machine Learning have started gaining momentum. Whether it is Voice Recognition based searching, Fraud Detection Systems, or a Recommendation System by Amazon or Netflix, Machine Learning has been the most implemented technology over the period of time.
In software engineering, behavioral design patterns are design patterns that identify common communication patterns between objects and realize these patterns.
Learning to Fingerprint the Latent Structure in Question ArticulationRavindra Guntur
Algorithmic interpretation of question articulation is one of the key steps in a machine-driven question-answering system. Machine understanding of an input question is tightly related to recognition of articulation in the context of the computational capabilities of an underlying processing algorithm. In this paper, a mathematical model to capture and distinguish the latent structure in the articulation of questions is presented. It is argued that an objective-driven approach to represent this latent structure is beneficial when examples of complementary objectives are not available. We show that the latent structure can be represented as a system that maximizes a cost function related to the underlying objective. Further, we show that the optimization formulation can be approximated to building a memory of patterns represented as a trained neural auto-encoder. Experimental evaluation using many clusters of questions, each related to an objective, shows 80% recognition accuracy and a negligible false positive across these clusters of questions. We then extend the same memory to a related task where the goal is to iteratively refine clusters of questions based on latent articulation. We show that the refinement scheme called K-fingerprints achieves nearly 100% cluster recognition with negligible false positive between different clusters.
A chatbot is Artificial Intelligence (AI) software that can simulate a conversation (or a chat)
with a user in natural language through messaging applications, websites, and mobile apps or through
the telephone.
It is often described as one of the most advanced and promising expressions of interaction
between humans and machines. However, from a technological point of view, a chatbot only
represents the natural evolution of a Question Answering system leveraging Natural Language
Processing (NLP). Formulating responses to questions in natural language is one of the most typical
Examples of Natural Language Processing applied in various enterprises’ end-use applications.
Chatbot applications streamline interactions between people and services, enhancing customer
experience. At the same time, they offer companies new opportunities to improve the customers
engagement process and operational efficiency by reducing the typical cost of customer service.
To be successful, a chatbot solution should be able to effectively perform both of these tasks. Human
support plays a key role here: Regardless of the kind of approach and the platform, human
intervention is crucial in configuring, training and optimizing the chatbot system.
Artificial Intelligence
What is Intelligence?
Intelligence Composed of
Goals of AI
Philosophy of AI
Types of Intelligence
Contributes to AI
AI Fields of Study
Applications of AI
Advantages of Artificial Intelligence
Disadvantages / Limitation / Drawbacks of Artificial Intelligence
Issues of Artificial Intelligence
Artificial Intelligence And Machine Learning PowerPoint Presentation Slides C...SlideTeam
Artificial Intelligence And Machine Learning PowerPoint Presentation Slides arrange insightful data using industry-best design practices. Highlight the differences between machine intelligence, machine learning, and deep learning through our PPT format. Utilize this PowerPoint slideshow to present advantages, disadvantages, learning techniques, and types of supervised machine learning. Further, cover the merits, demerits, and types of unsupervised machine learning. Communicate important details concerning reinforcement learning. Familiarize your viewers with the expert system in artificial intelligence. Outline examples, characteristics, constituents, uses, advantages, drawbacks, and other aspects of the expert system. Compile the deep learning process, recurrent neural networks, and convolutional neural networks through this PowerPoint theme. Present an impactful introduction to artificial intelligence. Introduce kinds, algorithms, trends, and use cases of artificial intelligence. This presentation is not only easy-to-follow but also very convenient to edit, even if you have no prior design experience. Smash the download button and start instant personalization. Our Artificial Intelligence And Machine Learning PowerPoint Presentation Slides Complete Deck are explicit and effective. They combine clarity and concise expression. https://bit.ly/3hKg7PV
Artificial Intelligence in e-commerce sector. This ppt explain that how can artificial intelligence helps in the growth of E-commerce industry. It includes pros and cons also.
Ever since the companies have realized that the regular software are not going to address the growing competition and that they need something additional to pull them, concepts like Data Science and Machine Learning have started gaining momentum. Whether it is Voice Recognition based searching, Fraud Detection Systems, or a Recommendation System by Amazon or Netflix, Machine Learning has been the most implemented technology over the period of time.
In software engineering, behavioral design patterns are design patterns that identify common communication patterns between objects and realize these patterns.
Learning to Fingerprint the Latent Structure in Question ArticulationRavindra Guntur
Algorithmic interpretation of question articulation is one of the key steps in a machine-driven question-answering system. Machine understanding of an input question is tightly related to recognition of articulation in the context of the computational capabilities of an underlying processing algorithm. In this paper, a mathematical model to capture and distinguish the latent structure in the articulation of questions is presented. It is argued that an objective-driven approach to represent this latent structure is beneficial when examples of complementary objectives are not available. We show that the latent structure can be represented as a system that maximizes a cost function related to the underlying objective. Further, we show that the optimization formulation can be approximated to building a memory of patterns represented as a trained neural auto-encoder. Experimental evaluation using many clusters of questions, each related to an objective, shows 80% recognition accuracy and a negligible false positive across these clusters of questions. We then extend the same memory to a related task where the goal is to iteratively refine clusters of questions based on latent articulation. We show that the refinement scheme called K-fingerprints achieves nearly 100% cluster recognition with negligible false positive between different clusters.
A chatbot is Artificial Intelligence (AI) software that can simulate a conversation (or a chat)
with a user in natural language through messaging applications, websites, and mobile apps or through
the telephone.
It is often described as one of the most advanced and promising expressions of interaction
between humans and machines. However, from a technological point of view, a chatbot only
represents the natural evolution of a Question Answering system leveraging Natural Language
Processing (NLP). Formulating responses to questions in natural language is one of the most typical
Examples of Natural Language Processing applied in various enterprises’ end-use applications.
Chatbot applications streamline interactions between people and services, enhancing customer
experience. At the same time, they offer companies new opportunities to improve the customers
engagement process and operational efficiency by reducing the typical cost of customer service.
To be successful, a chatbot solution should be able to effectively perform both of these tasks. Human
support plays a key role here: Regardless of the kind of approach and the platform, human
intervention is crucial in configuring, training and optimizing the chatbot system.
Artificial Intelligence
What is Intelligence?
Intelligence Composed of
Goals of AI
Philosophy of AI
Types of Intelligence
Contributes to AI
AI Fields of Study
Applications of AI
Advantages of Artificial Intelligence
Disadvantages / Limitation / Drawbacks of Artificial Intelligence
Issues of Artificial Intelligence
Priti Srinivas Sajja is an Associate Professor working with Post Graduate Department of Computer Science, Sardar Patel University, India since 1994. She specializes in Artificial Intelligence especially in knowledge-based systems, soft computing and multiagent systems. She is co-author of Knowledge-Based Systems (2009) and Intelligent Technologies for Web Applications (2012). She is Principal Investigator of a major research project funded by UGC, India.
She has 113 publications in books, book chapters, journals, and in the proceedings of national and international conferences. Her four publications have won best research paper awards. for more detail, please visir pritisajja.info.
A brief introduction to DataScience with explaining of the concepts, algorithms, machine learning, supervised and unsupervised learning, clustering, statistics, data preprocessing, real-world applications etc.
It's part of a Data Science Corner Campaign where I will be discussing the fundamentals of DataScience, AIML, Statistics etc.
1 The ability of a computer to perform tasks that require h.pdfacecomputertcr
1. The ability of a computer to perform tasks that require human intelligence. a) Artificial
Intelligence b) Vision c) Deep learning 2. Artificial Intelligence [Ai] is the science of making
machines that a) Artificial Intelligence b) Think like human c) Act like machine 3. Out of the
following options, which AI approach came first?. a) Fuzzy logic b) Machin Learning c) Deep
learning 4. If you have to pick one best definition that reflect the current state of artificial
intelligence. a) Think like human b) Acting like human c) Learning like human 5. Fuzziness occurs
when the boundary of a piece of information is a) clear-cut b) clear identify c) not clear-cut 6.
Machine learning ML came after a) Artificial Intelligence b) Vision c) Deep learning 7. Deep
learning DL came after. a) Artificial Intelligence b) Machine learning c) Deep learning 8. The entity
that perceives its environment and acts upon that environment. a) Agent b) State c) Initial State 9.
Fuzzy logic can capture the degree of a) Belongingness b) Working c) Truthfulness 10. In the
machine is trained using the labelled dataset a) Supervised learning b) Unsupervised learning c)
Reinforcement Learning.
Testing AI and Bias Questionnaire ChecklistTariq King
The goal of the questionnaire is to ensure that people building AI-based systems are aware of unwanted bias, stability, or quality problems. If an engineer cannot answer these questions, it is likely that the system produced contains unwanted, and possibly even liable versions of bias.
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At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
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This Digital Transformation and IT Strategy Toolkit was created by ex-McKinsey, Deloitte and BCG Management Consultants, after more than 5,000 hours of work. It is considered the world's best & most comprehensive Digital Transformation and IT Strategy Toolkit. It includes all the Frameworks, Best Practices & Templates required to successfully undertake the Digital Transformation of your organization and define a robust IT Strategy.
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4. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 4
Introduction
This is the sample exam EXIN BCS Artificial Intelligence Essentials (AIE.EN). The Rules and
Regulations for EXIN’s examinations apply to this exam.
This exam consists of 10 multiple-choice questions. Each multiple-choice question has a number
of possible answers, of which only one is the correct answer.
The maximum number of points that can be obtained for this exam is 10. Each correct answer is
worth one point. If you obtain 7 points or more, you will pass.
The time allowed for this exam is 15 minutes.
This is a specimen paper only. The full exam is 20 multiple choice questions with a pass mark of
13/20. The full exam duration is 30 minutes.
Good luck!
5. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 5
Sample Exam
1 / 10
Who is often quoted as having defined Machine Learning?
A) Marvin Minsky
B) Tom Mitchell
C) Alan Turing
D) Sir James Lighthill
2 / 10
What is an example of Human Intelligence?
A) Applying for a job
B) Watching a movie
C) Describing the taste of food
D) Identifying a horse in a foggy field
3 / 10
What is not used to define Heuristic?
A) Child's play
B) Discovery
C) Trial and Error
D) Experimentation
4 / 10
Which of the following is an Artificial Neural Network a form of?
A) Machine Learning that learns unsupervised from structured and un-structured data
B) Automation that learns from sensors and the Internet of Things
C) Scripting that learns randomly from unstructured data
D) Biological computing that learns from human emotions
5 / 10
What part of the human body is the Artificial Neural Network based on?
A) Digestive system
B) Brain
C) Spinal Cord
D) Endocrine System
6. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 6
6 / 10
What is a form of Artificial Intelligence?
A) Deep Learning
B) Statistics
C) Linear Algebra
D) Graph Theory
7 / 10
Optical Character Recognition (OCR) uses machine learning to interpret which of the following?
A) Images of hand writing and text
B) Images and hand writing
C) Technical drawings and text
D) Road signs and markings
8 / 10
In the specific context of Artificial Intelligence, what does NLP stand for?
A) Neuro Linguistic Programming
B) Natural Language Processing
C) Natural Linear Processing
D) Non-Linear Programming
9 / 10
Swarm Intelligence and optimization are used in what type of machine learning?
A) Revision Learning
B) Repeat Learning
C) Reinforcement Learning
D) Reflective Practice Learning
10 / 10
Artificial Intelligence is associated with which industrial revolution?
A) Fourth
B) Third
C) Second
D) First
7. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 7
Answer Key
1 / 10
Who is often quoted as having defined Machine Learning?
A) Marvin Minsky
B) Tom Mitchell
C) Alan Turing
D) Sir James Lighthill
A) Incorrect.
B) Correct. Taken from the standard textbook by Tom Mitchell. Public recognition can be seen on sites
such as Wikipedia. The other answers are key figures in AI and Machine Learning. (Literature: Syllabus
Section 1)
C) Incorrect.
D) Incorrect.
2 / 10
What is an example of Human Intelligence?
A) Applying for a job
B) Watching a movie
C) Describing the taste of food
D) Identifying a horse in a foggy field
A) Incorrect.
B) Incorrect.
C) Incorrect.
D) Correct. A human can identify a horse in a foggy field with only a few examples. Machine learning on
the other hand requires an order of magnitude more examples to learn the same thing. The other
answers are actions or subjective actions. (Literature: Syllabus Section 1)
8. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 8
3 / 10
What is not used to define Heuristic?
A) Child's play
B) Discovery
C) Trial and Error
D) Experimentation
A) Correct. Playing is what children do for fun and often involves learning. Discovery, Trial and Error and
Experimentation are what humans do to understand a problem and learn from. In machine learning, a
Heuristic can be used to guide an algorithm to the right answer or learn quicker. (Literature: Syllabus
Section 1)
B) Incorrect.
C) Incorrect.
D) Incorrect.
4 / 10
Which of the following is an Artificial Neural Network a form of?
A) Machine Learning that learns unsupervised from structured and un-structured data
B) Automation that learns from sensors and the Internet of Things
C) Scripting that learns randomly from unstructured data
D) Biological computing that learns from human emotions
A) Correct. From a general description of an ANN, the candidate should recall the definitions of
unsupervised, structured and unstructured data and know that the distractors are not examples of
machine learning. (Literature: Syllabus Section 2)
B) Incorrect.
C) Incorrect.
D) Incorrect.
9. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 9
5 / 10
What part of the human body is the Artificial Neural Network based on?
A) Digestive system
B) Brain
C) Spinal Cord
D) Endocrine System
A) Incorrect.
B) Correct. The candidate can recall that Machine Learning models can be simple mathematical
representations of the human body. (Literature: Syllabus Section 2)
C) Incorrect.
D) Incorrect.
6 / 10
What is a form of Artificial Intelligence?
A) Deep Learning
B) Statistics
C) Linear Algebra
D) Graph Theory
A) Correct. The candidate can give an example of AI; the other answers are fundamental subjects on
which machine learning is based. (Literature: Syllabus Section 2)
B) Incorrect.
C) Incorrect.
D) Incorrect.
7 / 10
Optical Character Recognition (OCR) uses machine learning to interpret which of the following?
A) Images of hand writing and text
B) Images and hand writing
C) Technical drawings and text
D) Road signs and markings
A) Correct. The candidate can remember that OCR is now about identifying hand written and type text.
The other answers are plausible examples. (Literature: Syllabus Section 3)
B) Incorrect.
C) Incorrect.
D) Incorrect.
10. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 10
8 / 10
In the specific context of Artificial Intelligence, what does NLP stand for?
A) Neuro Linguistic Programming
B) Natural Language Processing
C) Natural Linear Processing
D) Non-Linear Programming
A) Incorrect.
B) Correct. The candidate can recall the definition of NLP in the context of AI. NLP can be used in other
fields, so the candidate needs to understand this. (Literature: Syllabus Section 3)
C) Incorrect.
D) Incorrect.
9 / 10
Swarm Intelligence and optimization are used in what type of machine learning?
A) Revision Learning
B) Repeat Learning
C) Reinforcement Learning
D) Reflective Practice Learning
A) Incorrect.
B) Incorrect.
C) Correct. The candidate can remember that reinforcement learning is used in swarm intelligence and
optimization. This is an important part of why machine learning has developed into a large industry.
Deep Mind's success in beating the World Go champion is a typical example often quoted. The other
answers are plausible but not relevant. (Literature: Syllabus Section 3)
D) Incorrect.
10 / 10
Artificial Intelligence is associated with which industrial revolution?
A) Fourth
B) Third
C) Second
D) First
A) Correct. The candidate can recall that the Fourth industrial revolution has embraced AI. (Literature:
Syllabus Section 4)
B) Incorrect.
C) Incorrect.
D) Incorrect.
11. Sample Exam EXIN BCS Artificial Intelligence Essentials (AIE.EN) 11
Evaluation
The table below shows the correct answers to the questions in this sample exam.
Question Answer
1 B
2 D
3 A
4 A
5 B
6 A
7 A
8 B
9 C
10 A
