Purpose
Modern businesses encounter numerous challenges in conducting their regular operations. It takes a lot of work and money to overcome this obstacle. To accomplish more in less time and at less expense, a smart organization fundamentally needs intelligence. The study of artificial intelligence (AI) aims to replicate human intelligence. Although AI is well-known in many sectors, it is still developing and getting better.
You will discover the fundamentals of AI and its contemporary applications in this training course. A wide range of industries, including decision-making, gaming, journalism/media, finance, business operations, medical diagnosis, and science, use AI technology. Fuzzy logic, intelligent agents, expert systems, neural networks, and genetic algorithms are examples of contemporary AI. Delegates will get knowledge of AI’s foundations and applications.
Course Objectives
By completion of the course, participants will be able to:
Develop necessary AI; comprehend how to plan and analyze using logic; describe how to mimic human judgment in clustering and classification; comprehend how to construct machine learning-based applications; analyze and develop AI applications by the end of the course.
Duration: 5 Days
Target Audience
Project managers, office managers, leaders, and all other professionals who need to bridge the gap between the existing corporate environment and the approaching era of artificial intelligence would all substantially benefit from taking this course. This course is appropriate for a wide range of professionals.
Program Outline
Topic 1: Overview of AI
Introduction to AI, Success Stories, Human Intelligence vs. Artificial Intelligence, History of AI, Intelligent Agents and Their Roles, Limits of AI, and Intelligent Decision Making
Topic 2: Intelligent Agents
Knowledge-base and Data Base, Logic Reasoning, Unification, Deduction Processes, Different Types of Agents, Introduction to Agents, and Agents
Topic 3: Machine learning
Supervised and unsupervised learning, classification and clustering, artificial neural networks, learn by doing, object recognition, and features and classes.
Topic 4: Fuzzy Logic
Introduction to Fuzzy Thinking Fuzziness vs. Probability Fuzzy Set and Fuzzy Rules Importance of Fuzzy Logic Real-world application of Fuzzy Controllers Fuzzy set and Fuzzy Rules, Fuzzy Logic
Topic 5: Â Genetic Algorithms
Overview Need for Optimization, Maximization, and Minimization GA Working and Evolving Genetic Algorithms Genetic Algorithms Chromosomes, Genes, Selection, Mutation, and Crossover; How to Use Genetic Algorithms; Real-World Examples of Genetic Algorithms for Business Process Optimization