Data Science for Marketing Analytics

Data Science for Marketing Analytics equips you with the skills to transform raw data into actionable marketing insights. This comprehensive course covers the entire data analytics lifecycle, from data acquisition and manipulation to predictive modeling and reporting.

Key Skills You'll Master:

• Data Wrangling with Python: Learn to use powerful Python libraries like pandas and Matplotlib to efficiently read, clean, and manipulate data, including both categorical and continuous variables. You'll gain proficiency in data transformation and visualization.
• Customer Segmentation: Discover and implement effective customer segmentation strategies using various clustering techniques. Evaluate and select the optimal segmentation approach for targeted marketing campaigns.
• Predictive Modeling: Build and interpret linear regression models to predict customer lifetime value (CLTV). Understand regression techniques and evaluate model performance.
• Classification Algorithms: Explore and apply classification algorithms to predict customer choice, enabling more effective targeting and personalized marketing.
• Churn Prediction: Develop a robust churn model to identify customers at risk of leaving, allowing for proactive retention strategies.
• Marketing Reporting & Dashboards: Gain practical experience building interactive marketing reports and dashboards to visualize key performance indicators (KPIs) and track campaign effectiveness.

Who Should Take This Course?

This course is ideal for marketing professionals, data analysts, and anyone seeking to leverage data science for improved marketing outcomes.

Meet the Instructors:

• Tommy Blanchard: Ph.D. from the University of Rochester and postdoctoral training at Harvard. Leads the data science team at Fresenius Medical Care North America, specializing in advanced analytics and predictive modeling.
• Debasish Behera: Data Scientist at a large Japanese corporate bank, applying machine learning/AI to solve complex business challenges. Expertise in AML, predictive analytics, customer segmentation, and natural language processing. Holds a Master’s in Business Analytics (MITB) from Singapore Management University.
• Pranshu Bhatnagar: Data Scientist with experience in telematics, insurance, and mobile software. Previously a Quantitative Analyst in FinTech. Writes extensively on algorithms, time series analysis in Python, and machine learning. Holds a degree in Mathematics and Computer Science and certifications in Machine Learning and AI.
• Candas Bilgin: Experienced Data Science Specialist with a strong background in the hospital & healthcare industry. Proficient in Python, R, Machine Learning, Predictive Analytics, and Data Science. Microsoft Certified Data Scientist and Certified Tableau Developer.