Machine Learning for Marketing Specialization

Apply Python as an effective tool for implementing various algorithms.

Describe unsupervised learning and list its various algorithms.

List the various applications and promising areas for the application of unsupervised learning.

Demonstrate a solid understanding of the decision-making process through data analytics.

Visualize and imagine the application of data analytics techniques to real-world marketing problems.

Explain how marketing analytics and decision science approaches for marketing can enhance the quality of marketing decision-making.

Comprehend what text mining is, what it accomplishes, and what use cases it can be put to in the marketing discipline.

Examine how theoretical issues are translated into practical applications in text mining for the marketing domain.

Identify the potent analytical techniques that you can apply to text and other types of data.

Explain what constitutes sound practices and what does not while analyzing texts for decision-making in marketing.

Describe consumer journey, intent, and activity on your business website or landing pages.

Discuss the various digital marketing platforms, their nature, the business elements to create a digital marketing strategy, and various KPIs.

Explain Google Analytics, its importance and data insights that businesses can leverage upon, and how GA4 is different from Universal Analytics.

Analyze how to understand and fine-tune the brand image and market objectives from various KPIs.