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Duration 14 hours
Course Outline
Introduction to AI Personal Assistants
- Defining the AI-powered personal assistant
- Industrial applications of personal assistants
- Essential components and technologies underpinning smart assistants
Foundations of AI Models for Personal Assistants
- Overview of Natural Language Processing (NLP)
- Exploring language models: GPT, Gemini, and alternatives
- Selecting the optimal AI model for specific applications
Developing a Personal Assistant: Practical Implementation
- Configuring the development environment
- Connecting AI models to user interfaces
- Implementing voice and text-based interaction capabilities
Advanced Capabilities of Personal Assistants
- Refining AI responses to enhance user experience
- Leveraging APIs and third-party services to expand functionality
- Incorporating security measures and data privacy features
Deployment and Scalability of AI Personal Assistants
- Strategies for deploying personal assistants
- Optimising performance for scalable solutions
- Examples of real-world use cases and deployments
Ethics, Privacy, and Building User Trust in AI Assistants
- Analyzing the ethical implications of AI assistants
- Safeguarding user data privacy and fostering trust
- Adhering to data protection regulations (such as GDPR)
Summary and Path Forward
- Reflecting on key concepts and skills acquired during the course
- Identifying additional resources for continuous learning
- Next steps for deploying personal assistants in various industries
Requirements
- Familiarity with fundamental Python programming
- Conceptual understanding of machine learning
- Practical experience with basic AI tools and frameworks
Target Audience
- Product developers
- AI engineers
- UX/UI designers
