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
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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
- Digital Marketing
- Dimensionality Reduction
- Web Analytics and SEO
- Online Advertising
- Unsupervised Learning
- Search Engine Optimization
- Text Mining
- Customer Retention
- Data Mining
- Customer Analysis
- Supervised Learning
- Anomaly Detection
- Digital Advertising
- Search Engine Marketing
- Marketing Analytics
- Web Analytics
- Data Ethics
- Predictive 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
Category: Supervised Learning
Category: Customer Retention
Category: Customer Insights
Category: Marketing Analytics
Category: Predictive Analytics
Category: Python Programming
Category: Applied Machine Learning
Category: Machine Learning
Category: Marketing Strategies
Category: Scikit Learn (Machine Learning Library)
Category: Personalized Service
Category: Application Deployment
Category: Regression Analysis
Category: Artificial Intelligence and Machine Learning (AI/ML)
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
Category: Unsupervised Learning
Category: Anomaly Detection
Category: Dimensionality Reduction
Category: Machine Learning Algorithms
Category: Scikit Learn (Machine Learning Library)
Category: Customer Analysis
Category: Data-Driven Decision-Making
Category: Customer Insights
Category: Statistical Machine Learning
Category: Marketing Analytics
Category: Applied Machine Learning
Category: Machine Learning Methods
Category: Data Mining
Category: Unstructured Data
Category: Algorithms
Category: Python Programming
Category: Market Analysis
Category: Target Audience
Category: Exploratory Data Analysis
Category: Marketing
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
Category: Customer Retention
Category: Predictive Analytics
Category: Loyalty Programs
Category: Customer Acquisition Management
Category: Customer Analysis
Category: Customer Insights
Category: Marketing Strategies
Category: Customer experience improvement
Category: Marketing Analytics
Category: Data-Driven Decision-Making
Category: Consumer Behaviour
Category: Personalized Service
Category: Business 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
Category: Text Mining
Category: Natural Language Processing
Category: Brand Management
Category: Unstructured Data
Category: Marketing Analytics
Category: Data Ethics
Category: Customer Insights
Category: Predictive Analytics
Category: Data Mining
Category: Machine Learning
Category: Data Quality
Category: Marketing
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
Category: Digital Marketing
Category: Social Media
Category: Digital Advertising
Category: Emerging Technologies
Category: Marketing Planning
Category: Google Analytics
Category: Search Engine Marketing
Category: Search Engine Optimization
Category: Marketing Strategies
Category: Paid media
Category: Blogs
Category: Google Ads
Category: Web Analytics
Category: Advertising
Category: Web Analytics and SEO
Category: Marketing Analytics
Category: Social Media Marketing
Category: Keyword Research
Category: Marketing Channel
Category: Online Advertising
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,