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AI-Led Enterprise Transformation: Technologies and Use Cases | DBDA.X423
Artificial Intelligence (AI), already pervasive in our environment, is described as “the new electricity” because it is transforming our lives, the economy, academia, and industry. We ask Siri for directions to the nearest charging station and consider products suggested by Amazon Echo. Advanced AI applications include self-driving cars, medical image analysis and diagnoses, and cyber intelligence. Google, Facebook, Microsoft, and IBM have announced that AI is a central component in all of their product development.
In this sweeping introductory course, students will study the concepts and technologies that comprise AI, its current applications, and the future of the technology. You will obtain a general understanding of enterprise-grade frameworks such as TensorFlow, Keras, Theano, and applied use cases in machine learning and deep learning environments. You will also build an understanding of 'AI at the edge' applications where a huge number of startups are creating new infrastructure. The class prepares you to pursue our developing AI program series.
At the conclusion of the course, you should be able to:
- Describe the differences of AI, Machine Learning and Deep Learning
- Discuss the various applications of AI, Machine Learning and Deep Learning
- Explain the process of developing intelligent applications using AI, Machine Learning and Deep Learning
- Discuss various technologies being used in AI powered intelligent applications
- Overview of artificial intelligence, machine learning, and deep learning
- The current state of artificial intelligence and machine learning
- Applications of artificial intelligence and machine learning
- Deep learning: an advancement in AI
- The development and deployment processes of AI applications
- The technologies behind artificial intelligence and machine learning
- Closing the talent gap
- Future directions in AI
- Industry job opportunities and basic requirements to qualify for these jobs
- Save your seat and help us confirm course scheduling. Enroll at least seven days before your course starts.
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