This course syllabus outlines a practical, tool-driven introduction to using artificial intelligence in data analytics without requiring extensive coding skills. The course covers the full analytics lifecycle, including data collection, automated cleaning and preprocessing, exploratory data analysis, visualization, and predictive modeling. Learners are introduced to widely used AI platforms such as IBM Watson, Google AI, Tableau, and Microsoft Azure AI. Advanced topics include AI-driven feature engineering, natural language processing, time series forecasting, and model evaluation. The course culminates in a capstone project where participants apply AI tools to analyze real datasets, generate insights, and present results through interactive dashboards and reports.

Join for free to read