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Marketing Analyst: Learn Sales Forecasting & Market Analysis

Mastering AI-Driven Sales Forecasting, Market Analysis, customer Segmentation, Predictive Analytics ML models in Python.

Welcome to Comprehensive Marketing Data Analysis and YouTube Analytics using Python, an in-depth, hands-on course designed to equip you with the practical skills needed to leverage Python for marketing data analysis and analytics across various platforms. This course covers a wide range of topics, from YouTube Analytics and Marketing Data Analysis to more advanced case studies using machine learning in marketing, customer segmentation, churn detection, and AB testing. Whether you’re a marketing professional, data analyst, or a Python enthusiast, this course will take you from beginner to advanced levels, empowering you to make data-driven decisions in marketing.

What you’ll learn

Course Content

Requirements

Welcome to Comprehensive Marketing Data Analysis and YouTube Analytics using Python, an in-depth, hands-on course designed to equip you with the practical skills needed to leverage Python for marketing data analysis and analytics across various platforms. This course covers a wide range of topics, from YouTube Analytics and Marketing Data Analysis to more advanced case studies using machine learning in marketing, customer segmentation, churn detection, and AB testing. Whether you’re a marketing professional, data analyst, or a Python enthusiast, this course will take you from beginner to advanced levels, empowering you to make data-driven decisions in marketing.

 

Part 1: Marketing Data Analysis with Pandas and Python

Building on the foundations of YouTube Analytics, this part focuses on general marketing data analysis using Python, emphasizing practical techniques for data-driven marketing strategies.

Part 2: YouTube Analytics using Python

YouTube is a treasure trove of marketing insights. This section shows you how to collect, process, and analyze YouTube data with Python.

 

Part 3: Banking Data Analysis and Case Study

In this section, you’ll work on a case study using the Kaggle banking dataset, focusing on customer demographics, transaction data, and marketing campaign responses to develop targeted marketing strategies for the banking sector.

 

Part 4: Machine Learning in Marketing

Delve into machine learning applications in marketing, including supervised and unsupervised learning, predictive modeling, and budget optimization.

 

Part 5: Customer Segmentation

Learn advanced customer segmentation techniques to refine marketing strategies, focusing on clustering and customer behavior analysis.

 

Part 6: Churn Detection

Apply machine learning to detect customer churn, understanding how to predict and mitigate potential losses in customer retention.

 

Part 7: Customer Analytics and AB Testing

Master customer analytics with the Google Analytics Customer Revenue Prediction dataset, and gain proficiency in AB testing to measure marketing impact, calculate lift, and perform significance testing with Python.

 

Learning Outcomes:

Requirements:

Intended Audience: This course is ideal for aspiring data analysts, marketers, and professionals who want to enhance their Python skills in a marketing context. It offers insights into YouTube Analytics, customer segmentation, and machine learning for marketing, empowering you to excel in the data-driven marketing field.