Ethical AI applications of deep learning and computer vision
Few other AI technologies carry as much promise and controversy, as computer vision. Adopting responsible AI is a must as companies rely on user’s trust. Understanding how computer vision works and what are the ethical practices surrounding its enterprise applications, is a future-proof career choice.
IBM SkillsBuild for Academia
As AI adoption becomes ubiquitous, policies and compliance laws for AI Ethics are being drafted to safeguard the use and application of Artificial Intelligence technologies.
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Join an exciting evolving field of study, that is impacting every industry — from agriculture, healthcare, transportation, and government, giving rise to a new wave of opportunities in the job-market.
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Leverage your current domain expertise, augment it with new highly-sought-after technical skills, and the ethical acumen needed to lead teams into a safe adoption of AI technologies. Become eligible for advanced new high-paying jobs available in your profession.
Introduce advanced concepts for adopting AI in the enterprise:
- Machine learning
- Deep learning
- Visual recognition
- AI ethics
- Real world use-cases.
- Explore machine learning algorithms and develop a deep understanding of ML techniques
- Understand deep learning and its industry applications
- Understand computer vision and its relationship with deep learning
- Explore computer vision industry implementations through simulations and experiments
- Hands-on experience with IBM Watson Visual Recognition to classify and train deep learning models
- Explore an end-to-end use case, where a leading law firm assists a traffic monitoring entity on the ethical adoption of computer vision technology; role-play the personas involved in the scenario, including Chief Policy Officer, AI ethics consultant, AI developers, and AI ethics official
- Identify the sociocultural impact of visual recognition technology, and embrace an ethical roadmap for adoption which leads to benefits for society.
About this course
This course is divided into two practice levels. Each level covers more advanced topics and builds up on top of the concepts, practice, and skills addressed in the previous practice levels.
Level 1 — Deep learning and computer vision
Explore the innerworkings of ML and DL, and AI vision implementations.
- 1. Machine learning and deep Learning
- 2. Computer vision
Level 2 — Trustworthy VR and AI research trends
Adopt an ethical approach to visual recognition and learn future AI predictions.
- 1. Visual recognition in practice (interactive case study)
- 2. AI future trends
Skills you will need to have before joining this course offering.
Complete the Building Trustworthy AI Enterprise Solutions course from the AI Practitioner series.
Alternatively, you will need prior knowledge on the following subjects before joining this course:
- Understand the evolution and relevance of Artificial Intelligence for the enterprise, and implementation trends across several industries, including autonomous vehicles, robotics, and the job market
- Using low-code cloud-based AI tools with pre-built ML algorithms
- Hands-on experience with IBM Cloud services, IBM Watson Discovery, IBM Watson Assistant, IBM Language Translator, Text-to-Speech, Speech-to-Text, IBM Tone Analyzer
- Study the impact of COVID-19 on a law firm, and the internal dynamics as they embark on a digital transformation AI journey to explore new legal service offerings
- Understand interdepartmental responsibilities within a law firm, between C-Level executives, lawyers, and AI ethic consultants, and their interactions with client teams including design researchers, AI developers, and Business liaisons
- Understand AI ethical practices including fairness, accountability, user data rights, value alignment and explain ability.
Ethical AI Applications of Deep Learning and Computer VisionSee badge
About this badge
This badge earner has completed all the learning activities included in this online learning experience, including hands-on experience, concepts, methods, and tools related to the advanced concepts for AI adoption in the enterprise. The individual has demonstrated the application of advanced skills in the field of AI, including Machine learning, Deep learning, Visual recognition, AI ethics, and their application in real-world use cases.
AI, AI ethics, AI in transportation, AI policy, Decision trees, Deep learning, Deep learning frameworks, D&I, Gradient descent, Image classification, Machine learning, Multilayer perceptron, Neural networks, Object identification, Watson visual recognition.
- Must attend a training session at a higher education institution implementing the IBM Skills Academy program.
- Must have completed the self-paced online course activities, and knowledge checks validating understanding of the covered topics.