Fundamentals of Applied Artificial Intellgience#400324

• Explain the core concepts of AI, including machine learning, deep learning, and natural language processing.
• Identify the key benefits and limitations of using AI for problem-solving in various contexts.
• Explore real-world applications of AI across different industries, such as healthcare, manufacturing, finance, and retail.
• Analyse the impact of future trends on the development and application of AI through future studies methodologies.
• Develop a basic understanding of machine learning algorithms and how they are used to train AI models.
• Utilize basic tools and techniques for data preparation and analysis relevant to AI applications.
• Communicate effectively about AI concepts and applications to colleagues and stakeholders.
• Formulate a future-oriented perspective on AI and consider its potential implications for their careers and industries.

• Professionals from any background seeking an introduction to AI and its potential applications in their work.
• Business leaders and managers interested in exploring how AI can transform their operations and improve decision-making.
• Project managers and team leads looking to integrate AI into existing projects and workflows.
• Anyone curious about the future of AI and its potential impact on society.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

Day 1: Demystifying Artificial Intelligence
• Welcome and program overview.
• What is AI? An introductory session exploring the history, core concepts, and different types of AI, including machine learning and deep learning.
• AI in Action: Interactive demonstrations showcasing real-world applications of AI across various industries, such as image recognition, fraud detection, and personalized recommendations.
• The Ethics of AI: Discussing the ethical considerations surrounding AI development and deployment, focusing on bias, fairness, and transparency.
Day 2: Machine Learning for AI Applications
• Understanding Machine Learning: Delving into the basics of machine learning algorithms and how they are used to train AI models.
• Supervised Learning: Exploring supervised learning algorithms like linear regression and decision trees for tasks like classification and prediction.
• Unsupervised Learning: Learning about unsupervised learning techniques like clustering for data exploration and pattern recognition.
• Hands-on Machine Learning Lab: Participants will gain practical experience using a user-friendly platform or introductory coding environment to train simple machine learning models on pre-prepared datasets, focusing on understanding the training process and model evaluation.
Day 3: AI Applications Across Industries
• AI in Healthcare: Exploring applications of AI in medical diagnosis, drug discovery, and personalized patient care.
• AI in Manufacturing: Learning how AI is used for predictive maintenance, optimizing production processes, and improving robot capabilities within smart factories.
• AI in Finance: Discussing the use of AI for fraud detection, algorithmic trading, and personalized financial recommendations.
• AI in Retail: Exploring how AI is utilized for customer segmentation, personalized product recommendations, and optimizing inventory management.
• Guest Speaker: An industry expert working in a field where AI is actively applied can be invited to share their insights and answer participant questions.

Day 4: The Future of AI & Future Studies
• Future Studies for Applied AI: Learning how to incorporate scenario planning and horizon scanning to anticipate potential disruptions and opportunities related to AI in various sectors.
• The Impact of AI on Jobs: Exploring the potential impact of AI on job displacement and the transformation of work roles across different industries.
• The Human-Machine Collaboration: Discussing how AI can complement human capabilities and drive innovation, focusing on the importance of human oversight and ethical considerations.
• Case Study: analysing a real-world example of how an organization successfully implemented AI to address a future challenge within their industry.
Day 5: Building Your AI Future
• Communicating the Value of AI: Developing strategies for effectively communicating the benefits of AI to colleagues, managers, and stakeholders with varying levels of technical understanding.
• Building Your AI Skillset: Exploring resources and educational opportunities for further learning and skill development in AI, catering to different interests and career aspirations.
• Developing an AI Action Plan: Participants create personalized action plans outlining steps to explore and potentially implement AI solutions within their work environment or personal projects. This may include:
o Identifying potential applications of AI relevant to their role or industry.
o Researching readily available AI tools and resources for addressing specific challenges.
o Advocating for the adoption of responsible and ethical AI practices.
• The Future of AI: A Foresight Discussion: Exploring cutting-edge research and potential future advancements in AI, discussing how these advancements might further transform our lives and different sectors.
• Course Wrap-Up & Ongoing Learning: Reviewing key takeaways from the program, addressing any remaining questions, and discussing ongoing learning resources for staying informed about the latest developments in AI.
• Networking & Knowledge Sharing: Participants engage in a facilitated discussion to share their AI action plans, ask questions, and network with other professionals interested in exploring the future of applied AI.