AI Academy

Supervised Learning and Its Applications in Marketing

Instructor: Ambica Ghai Duration: 2 weeks to complete at 10 hours a week
Objective 1 Apply Python as an effective tool for supervised learning techniques.
Objective 2 Develop and train supervised machine learning models for classification and regression tasks.
Objective 3 Interpret and analyze various applications of supervised learning in marketing.
Objective 4 Describe the deployment of machine learning models and the challenges encountered in the deployment.
Supervised Learning
Predictive Analytics
Regression Analysis
Application Deployment
Personalized Service
Scikit Learn (Machine Learning Library)
Customer Insights
Marketing Analytics
Artificial Intelligence and Machine Learning (AI/ML)
Applied Machine Learning
Customer Retention
Machine Learning
Python Programming
Marketing Strategies

Unsupervised Learning and Its Applications in Marketing

Instructor: Ambica Ghai Duration: 2 weeks to complete at 10 hours a week
Objective 1 Apply Python as an effective tool for implementing various algorithms.
Objective 2 Describe unsupervised learning and list its various algorithms.
Objective 3 List the various applications and promising areas for the application of unsupervised learning.
Target Audience
Customer Insights
Statistical Machine Learning
Python Programming
Anomaly Detection
Market Analysis
Marketing Analytics
Algorithms
Scikit Learn (Machine Learning Library)
Unsupervised Learning
Dimensionality Reduction
Exploratory Data Analysis
Customer Analysis
Machine Learning Methods
Applied Machine Learning
Data-Driven Decision-Making
Data Mining
Unstructured Data
Marketing
Machine Learning Algorithms

Introduction to Decision Science for Marketing

Instructor: Prof. Lalit Pankaj Duration: 2 weeks to complete at 10 hours a week
Objective 1 Demonstrate a solid understanding of the decision-making process through data analytics.
Objective 2 Visualize and imagine the application of data analytics techniques to real-world marketing problems.
Objective 3 Explain how marketing analytics and decision science approaches for marketing can enhance the quality of marketing decision-making.
Customer Insights
Loyalty Programs
Customer Acquisition Management
Business Analytics
Personalized Service
Marketing Analytics
Customer Analysis
Customer experience improvement
Customer Retention
Data-Driven Decision-Making
Predictive Analytics
Marketing Strategies
Consumer Behaviour

Text Mining for Marketing

Instructor: Prof. Lalit Pankaj Duration: 20 hours to complete 3 weeks at 6 hours a week
Objective 1 Comprehend what text mining is, what it accomplishes, and what use cases it can be put to in the marketing discipline.
Objective 2 Examine how theoretical issues are translated into practical applications in text mining for the marketing domain.
Objective 3 Identify the potent analytical techniques that you can apply to text and other types of data.
Objective 4 Explain what constitutes sound practices and what does not while analyzing texts for decision-making in marketing.
Predictive Analytics
Data Quality
Machine Learning
Brand Management
Natural language processing
Data Mining
Data Ethics
Customer Insights
Unstructured Data
Marketing
Marketing Analytics
Text Mining

Digital Marketing Analytics

Instructor: Dr. Janardan Krishna Yadav Duration: 2 weeks to complete at 10 hours a week
Objective 1 Describe consumer journey, intent, and activity on your business website or landing pages.
Objective 2 Discuss the various digital marketing platforms, their nature, the business elements to create a digital marketing strategy, and various KPIs.
Objective 3 Explain Google Analytics, its importance and data insights that businesses can leverage upon, and how GA4 is different from Universal Analytics.
Objective 4 Analyze how to understand and fine-tune the brand image and market objectives from various KPIs.
Blogs
Google Ads
Digital Advertising
Marketing Channel
Google Analytics
Social Media
Marketing Planning
Search Engine Optimization
Web Analytics
Web Analytics and SEO
Keyword Research
Marketing Analytics
Online Advertising
Advertising
Digital Marketing
Marketing Strategies
Paid media
Emerging Technologies
Social Media Marketing
Search Engine Marketing