This Specialization is intended for beginners seeking to enter the artificial intelligence world. Through five courses, you will cover artificial intelligence technical groundings (including machine learning and technologies), ethical and legal issues, which will give you a clear picture of what artificial intelligence is and what opportunities artificial intelligence will provide in the next future.
Artificial Intelligence: an Overview Specialization
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Artificial Intelligence: an Overview Specialization
Enter the artificial intelligence world
Instructors: Marcello Restelli
8,003 already enrolled
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Get in-depth knowledge of a subject
4.6
(238 reviews)
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
4.6
(238 reviews)
Beginner level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Skills you'll gain
- Regulation and Legal Compliance
- Intellectual Property
- Artificial Intelligence and Machine Learning (AI/ML)
- Applied Machine Learning
- Computer Science
- General Data Protection Regulation (GDPR)
- Deep Learning
- Unsupervised Learning
- Machine Learning
- Computer Vision
- Dimensionality Reduction
- Machine Learning Algorithms
- Legal Risk
- Cloud Platforms
- Supervised Learning
- Law, Regulation, and Compliance
- Hardware Architecture
- Reinforcement Learning
- Artificial Intelligence
Tools you'll learn
What’s included
Shareable certificate
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Taught in English
16 practice exercises
Advance your subject-matter expertise
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Specialization - 5 course series
What you'll learn
Explain the seminal ideas leading to the birth of AI, the major difficulties and how the international community overtook them.
Describe what AI is today in terms of goals, scientific community, companies’ interests
Describe the taxonomy of the know-how on AI in terms of techniques, software and hardware methodologies.
Explain the need for national strategies on AI and identify the major Italian and European players on AI
Skills you'll gain
Category: Artificial Intelligence
Category: Technology Strategies
Category: Natural Language Processing
Category: Computer Vision
Category: Computer Hardware
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Computer Science
Category: Innovation
What you'll learn
Describe the reasons for an ethical analysis applied to AI.
Identify the ethical and social impacts and implications of AI.
Use critical skills in clarifying and ethically analyzing AI in different domains of life.
Critically analyze the current policies for AI and use ethical and socially responsible principles in your professional life.
What you'll learn
Recognize that the use of AI requires to be analysed, evaluated and addressed also from a legal point of view.
Indicate the main legal concepts of liability for choices made by or through intelligent systems and compensation for any consequential damage.
Verify whether and which criminal law principles apply when an offence is committed by an AI system.
Recognize the difference between copyright and patent and recognize the risks to fundamental rights and freedoms deriving from AI.
Skills you'll gain
Category: Law, Regulation, and Compliance
Category: Intellectual Property
Category: General Data Protection Regulation (GDPR)
Category: Artificial Intelligence
Category: Civil Law
Category: Regulation and Legal Compliance
Category: Lawsuits
Category: Information Privacy
Category: Legal Strategy
Category: Legal Risk
What you'll learn
Describe the technological scenario of AI (Cloud, Edge, IoT) from an IT perspective.
Identify the Machine and Deep Learning techniques and solutions developed for IoT and Edge Computing systems.
Explain the main challenges and opportunities of technologies and platforms for AI.
Skills you'll gain
Category: Cloud Computing
Category: Internet Of Things
Category: Cloud Platforms
Category: Artificial Intelligence
Category: Data Centers
Category: Information Technology Architecture
Category: Artificial Intelligence and Machine Learning (AI/ML)
Category: Embedded Systems
Category: Emerging Technologies
Category: Information Technology
Category: Application Development
Category: Deep Learning
Category: Hardware Architecture
Category: Cloud Computing Architecture
What you'll learn
Classify machine learning problems, supervised learning problems and describe the limitations of machine learning techniques in supervised learning
Classify machine learning problems in unsupervised learning, describe the utility of dimensionality reduction techniques
Formulate a sequential decision-making problem, explain what a value function is and describe how to optimize a policy in reinforcement learning
Skills you'll gain
Category: Unsupervised Learning
Category: Reinforcement Learning
Category: Dimensionality Reduction
Category: Supervised Learning
Category: Machine Learning Algorithms
Category: Applied Machine Learning
Category: Data Mining
Category: Classification And Regression Tree (CART)
Category: Machine Learning
Category: Algorithms
Category: Regression Analysis
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Frequently asked questions
The specialization is composed by 5 courses with a total estimated workload of around 25 hours
No recommended background/knowledge is required
No specific order required
More questions
Financial aid available,