Welcome to Lenovo Pro Academy's 'AI PCs for Business' online course! This course is designed to provide you with the knowledge and practical skills needed to navigate the rapidly evolving world of artificial intelligence (AI) and harness its power in business settings. Whether you're new to AI or looking to deepen your understanding, this course will equip you with the tools necessary to thrive in today's AI-driven marketplace. Course goals include:
1. Develop a Comprehensive Understanding of AI and Its Components
Learners will gain a thorough knowledge of the history, key concepts, and future trends in AI, including machine learning, deep learning, neural networks, and generative AI. This will equip them with a foundational understanding necessary for navigating and utilizing AI technologies effectively in various business contexts.
2. Foster Awareness and Strategies for Ethical AI Use
Through modules focused on the societal implications of AI, ethical concerns, and emerging regulations, learners will understand the importance of transparency, fairness, and accountability in AI. They will learn to identify and mitigate biases, prevent AI mishaps, and promote ethical AI practices within their organizations, ensuring responsible and sustainable AI adoption.
3. Equip Learners with Practical Skills for Implementing AI in Business, Specifically Through the Use of AI PCs
Learners will be equipped with practical skills for leveraging AI PCs to enhance business productivity and decision-making. This includes understanding the benefits and functionalities of AI PCs compared to traditional PCs, the role of Neural Processing Units (NPUs), and the significance of TOPS (Tera Operations Per Second) in AI performance. By learning to effectively integrate AI PCs into their business strategies, learners will be able to optimize processes, automate high-impact tasks, and drive innovation using advanced AI capabilities.
In Module 1: Understanding AI, we will cover:
· Key milestones in AI development (1950s - present)
· Significant breakthroughs in machine learning and neural networks
· The role of AI in modern technology (smartphones, internet, etc.)
· Future outlook: Where is AI heading?
Introduction to Machine Learning and Bots
· Definition and types of bots (chatbots, virtual assistants, etc.)
· Overview of machine learning (ML) concepts
· Common applications of bots in business (customer service, sales, etc.)
· Real-world examples of successful bot implementations
· Overview of AI algorithms and models
· Role of big data in AI development
· How AI makes decisions (inference process)
· Common misconceptions about AI functionality
Machine Learning, Deep Learning, Neural Networks
· Differences between machine learning, deep learning, and neural networks
· Structure of neural networks (neurons, layers, activation functions)
· Training neural networks (forward and backward propagation)
· Applications of deep learning (image recognition, natural language processing)
· Common fears and misconceptions about AI
· The importance of transparency and explainability in AI
· The concept of AI singularity and its implications
· Balancing innovation with ethical responsibility