[Free] Marketing Analytics: Digital Analytics
Digital Analytics
Requirements
- No prior Digital Analytics experience is required. Basic knowledge of marketing or business is helpful, and all concepts are explained step by step with practical examples.
Description
This course contains the use of Artificial Intelligence (AI).
Welcome to Marketing Analytics: Digital Analytics a comprehensive course designed to equip learners with the knowledge and practical skills required to leverage digital analytics, artificial intelligence, and machine learning for effective marketing decision-making. This course provides a structured understanding of the digital marketing analytics ecosystem, covering essential topics such as Search Engine Marketing (SEM), Search Engine Optimization (SEO), Social Media Analytics, and the transformative role of AI in modern marketing strategies.
Learners will explore key machine learning concepts, including Random Forest algorithms, Model Evaluation using Confusion Matrix, ROC Curves and AUC, Feed-Forward Neural Networks, Deep Neural Networks, Recommendation Systems, and Data Visualization techniques. Complex concepts are presented in a simple, easy-to-understand manner using real-world business examples and industry case studies from leading organizations such as Amazon, Google, Netflix, Spotify, and YouTube.
Designed for students, marketing professionals, business analysts, entrepreneurs, and researchers, this course emphasizes practical applications that bridge theory and industry practice. By the end of the course, learners will be able to analyze digital marketing data, evaluate AI-driven marketing models, understand recommendation engines, create meaningful visualizations, and make confident, data-driven marketing decisions that enhance customer engagement, optimize campaigns, and improve business performance across diverse industries.
Author(s): Dr J Dhanalakshmi
