Certificate in Market Share Analysis with Machine Learning

• Introduction to Market Share Analysis: Understanding the basics of market share analysis, its importance, and the different methods to calculate market share.
• Data Collection and Preparation: Gathering and cleaning data for market share analysis, including web scraping techniques and data preprocessing.
• Exploratory Data Analysis (EDA): Analyzing data to identify trends, patterns, and outliers, and to gain insights into the market.
• Machine Learning Fundamentals: An overview of machine learning concepts, algorithms, and techniques, including supervised and unsupervised learning.
• Feature Engineering and Selection: Techniques for creating and selecting the most relevant features for market share analysis using machine learning algorithms.
• Market Share Analysis with Machine Learning: Applying machine learning algorithms to market share analysis, including regression, decision trees, and neural networks.
• Model Evaluation and Validation: Techniques for evaluating and validating machine learning models for market share analysis, including cross-validation and statistical tests.
• Data Visualization: Techniques for visualizing market share analysis results, including charts, graphs, and dashboards.
• Market Share Analysis Best Practices: Best practices for conducting market share analysis, including data privacy considerations and ethical guidelines.

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