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 Duration 7 hours

Course Outline

Foundations of Artificial Intelligence

  • Definition and scope of Artificial Intelligence
  • Historical progression and critical advancements in AI
  • Distinguishing AI from Machine Learning and Deep Learning
  • Classifications of AI: Narrow, General, and Superintelligent

Core AI Theoretical Frameworks

  • The role of data, algorithms, and computational models
  • Principles of Machine Learning: Supervised, Unsupervised, and Reinforcement
  • Architectural basics of neural networks and Deep Learning
  • Overview of Natural Language Processing (NLP) capabilities

Operational AI Applications

  • Integration of AI in healthcare, financial services, retail, and transportation
  • Deployment of intelligent virtual assistants and automated chat systems
  • Leveraging AI for advanced business analytics and strategic decision-making

Data Management for AI Systems

  • Ensuring data integrity and effective preprocessing
  • Differentiating structured versus unstructured data formats
  • Addressing data ethics and identifying algorithmic biases
  • Standardized methods for data acquisition and labeling

Governance and Ethical Standards in AI

  • Ethical implications in the development of AI systems
  • Mitigation of bias within AI models and decision algorithms
  • Compliance with regulatory frameworks and governance protocols for government
  • Ensuring AI accountability and operational transparency

AI Technology Ecosystem

  • Survey of leading AI development frameworks
  • Analysis of major AI platforms including Google AI, Microsoft Azure, and IBM Watson
  • Foundations of automation and Robotic Process Automation (RPA)

Risk Management and Security in AI

  • Addressing cybersecurity vulnerabilities in AI infrastructure
  • Evaluating risks associated with over-reliance on automated systems
  • Assessing the socioeconomic impact of AI adoption
  • Monitoring AI model performance and addressing degradation issues

BCS Certification Preparation

  • Structure and format of the BCS examination
  • Review of sample questions and practical assessment tools
  • Identification of critical knowledge areas for exam success
  • Strategic guidelines for final preparation

Conclusion and Professional Development Pathways

Requirements

  • No prior requirements are necessary

Target Audience

  • Information Technology specialists
  • Business analysis professionals
  • Project management staff

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