Understand the structure and techniques used in Machine Learning, Text Mining, and Decision Science for Marketing.
Explore the fascinating world of Machine Learning and its transformative applications in marketing.
Explain how analytics and decision science approaches for marketing can enhance the quality of marketing decision-making.
Foundation in digital marketing analytics to understand the consumer journey, intent, and activity on your business website.
Machine Learning for Marketing Specialization
Machine Learning for Marketing Specialization
Learn Machine Learning Techniques in Marketing. This 5-course Specialization from Jindal Global Business School (JGBS) is for marketing professionals, and anyone interested in gaining greater knowledge of how to conceptualize effective marketing strategies and decisions using Machine Learning (ML) and Decision Science.
Instructors: Ambica Ghai
Included with 
Get in-depth knowledge of a subject
(12 reviews)
Beginner level
Recommended experience
3 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(12 reviews)
Beginner level
Recommended experience
3 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
You will create a digital marketing plan and an Ad Campaign on Google Ads using KPIs to evaluate the performance of campaigns.
You will use Google Analytics, Google search engine, Python programming language, and Anaconda Navigator to make informed marketing decisions.
You will also use text mining techniques for sentiment analysis and customer feedback analysis in marketing.
Overview
Skills you'll gain
- Supervised Learning
- Digital Marketing
- Text Mining
- Online Advertising
- Search Engine Optimization
- Data Mining
- Web Analytics and SEO
- Unsupervised Learning
- Web Analytics
- Anomaly Detection
- Predictive Analytics
- Search Engine Marketing
- Customer Analysis
- Digital Advertising
- Data Ethics
- Customer Retention
- Dimensionality Reduction
- Marketing Analytics
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
179 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from O.P. Jindal Global University
Specialization - 5 course series
What you'll learn
Apply Python as an effective tool for supervised learning techniques.
Develop and train supervised machine learning models for classification and regression tasks.
Interpret and analyze various applications of supervised learning in marketing.
Describe the deployment of machine learning models and the challenges encountered in the deployment.
Skills you'll gain
Supervised Learning, Customer Retention, Customer Insights, Predictive Analytics, Marketing Analytics, Applied Machine Learning, Marketing, Python Programming, Application Deployment, Predictive Modeling, Artificial Intelligence and Machine Learning (AI/ML), Machine Learning, Regression Analysis, Scikit Learn (Machine Learning Library), Personalized Service, and Marketing Strategies
What you'll learn
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.
Skills you'll gain
Unsupervised Learning, Dimensionality Reduction, Anomaly Detection, Customer Analysis, Machine Learning Algorithms, Marketing, Artificial Neural Networks, Customer Insights, Python Programming, Exploratory Data Analysis, Marketing Analytics, Unstructured Data, Market Analysis, Data-Driven Decision-Making, Algorithms, Target Audience, Applied Machine Learning, Scikit Learn (Machine Learning Library), Data Mining, and Statistical Machine Learning
What you'll learn
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.
Skills you'll gain
Customer Retention, Predictive Analytics, Loyalty Programs, Customer Acquisition Management, Customer experience improvement, Marketing Strategies, Customer Insights, Consumer Behaviour, Data-Driven Decision-Making, Personalized Service, Customer Analysis, Business Analytics, and Marketing Analytics
What you'll learn
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.
Skills you'll gain
Text Mining, Marketing, Unstructured Data, Data Quality, Brand Awareness, Customer Insights, Predictive Analytics, Natural Language Processing, Machine Learning, Data Ethics, Marketing Analytics, and Data Mining
What you'll learn
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.
Skills you'll gain
Digital Marketing, Emerging Technologies, Marketing Planning, Google Analytics, Digital Advertising, Online Advertising, Social Media, Search Engine Optimization, Search Engine Marketing, Google Ads, Blogs, Paid media, Social Media Marketing, Keyword Research, Marketing Analytics, Web Analytics and SEO, Marketing Channel, Advertising, Web Analytics, and Marketing Strategies
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
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Frequently asked questions
You will need approximately 100-120 hours to complete the Specialization.
You should have a basic knowledge of marketing concepts and data analytics techniques, Google search engine, Google Ads, and Google Analytics. An intermediate-level knowledge in Python programming would be beneficial.
No, you can take courses in any order.
More questions
Financial aid available,