Professional Certificate in AI Applications: Practical Approaches
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• Introduction to AI and Machine Learning: Understanding the basics of AI, machine learning, and deep learning concepts.
• Data Preprocessing for AI Applications: Data cleaning, transformation, and feature engineering techniques.
• Computer Vision with AI: Image recognition, object detection, and image analysis using convolutional neural networks.
• Natural Language Processing (NLP): Text mining, sentiment analysis, and text classification techniques.
• Reinforcement Learning: Q-learning, Deep Q-Networks, and reinforcement learning applications.
• AI Ethics and Bias: Understanding the ethical implications and biases in AI systems.
• AI Project Management: Managing AI projects, setting up AI teams, and best practices in AI development.
• AI Cloud Solutions: Exploring cloud-based AI solutions, tools, and platforms.
• AI in Business: Implementing AI in business processes, decision making, and strategy.
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- BasicUnderstandingSubject
- ProficiencyEnglish
- ComputerInternetAccess
- BasicComputerSkills
- DedicationCompleteCourse
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- NotAccreditedRecognized
- NotRegulatedAuthorized
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- ThreeFourHoursPerWeek
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- TwoThreeHoursPerWeek
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