Curriculum
13 Sections
37 Lessons
10 Weeks
Expand all sections
Collapse all sections
Introduction to Data Science and Digital Marketing
Success stories of data-driven campaigns.
3
0.0
Understanding the data science workflow.
0.1
Relevance of data science in digital marketing.
0.2
Success stories of data-driven campaigns.
Using Chatbots and AI Assistants in Digital Marketing
3
0.0
Integrating conversational AI tools into campaigns.
0.1
Designing interactive chatbot experiences.
0.2
Automating customer interactions with AI.
Data Collection and Preprocessing
3
1.0
Identifying data sources for marketing.
1.1
Techniques for data cleaning and transformation.
1.2
Introduction to web scraping for insights.
Exploratory Data Analysis for Marketing Insights
3
2.0
Visualizing marketing data with Python/R.
2.1
Uncovering trends and patterns in data.
2.2
Optimizing marketing strategies using EDA.
Statistical Methods for A/B Testing and Customer Segmentation
3
3.0
Conducting hypothesis testing and A/B testing.
3.1
Understanding and applying customer segmentation.
3.2
Analyzing marketing experiments statistically.
Machine Learning for Digital Marketing
3
4.0
Basics of supervised and unsupervised learning.
4.1
Implementing models for marketing predictions.
4.2
Clustering techniques for audience segmentation.
Predictive Analytics for Customer Behavior Analysis
3
5.0
Predicting customer churn and lifetime value.
5.1
Building recommendation systems for marketing.
5.2
Evaluating model performance in marketing.
Sentiment Analysis and Social Media Marketing
3
6.0
Extracting insights from social media data.
6.1
Role of sentiment analysis in brand perception.
6.2
Leveraging social media data for campaigns.
Data Visualization and Communication for Marketing Professionals
3
7.0
Advanced data visualization tools like Tableau.
7.1
Storytelling with data to communicate insights
7.2
Planning for the final project.
Natural Language Processing for Marketing
3
8.0
Basics of NLP and its relevance to marketing.
8.1
Using NLP for sentiment analysis and customer feedback.
8.2
Exploring chatbot development for customer support.
Advanced Data Analytics with Google Analytics
3
9.0
Role of web analytics in data-driven marketing.
9.1
Using Google Analytics for insights.
9.2
Leveraging chatbot data for engagement and conversion
Final Project Planning and Preparation
2
10.0
Defining the scope and objectives.
10.1
Identifying data sources and tools required.
Final Project Implementation
2
11.0
Working on comprehensive data-driven marketing projects.
11.1
Integration of data science techniques.
Data Science for Digital Marketers
Search
This content is protected, please
login
and enroll in the course to view this content!
Scan the code
Modal title
Main Content