TypeScript vs. JavaScript: A Guide
September 30, 2024
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Recommended experience
Intermediate level
Learners will need basic Python (Pandas dataframes, aggregation, filtering) and principles of data analysis (histograms, summary statistics).
Recommended experience
Intermediate level
Learners will need basic Python (Pandas dataframes, aggregation, filtering) and principles of data analysis (histograms, summary statistics).
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Who are your customers? What are they like? How do they interact with your business? This Short Course was created to help analysts better understand their customer behaviour through the power of machine learning.
In this course, you will apply two different machine learning techniques to segment customers according to their purchasing behaviour and provide actionable insights for each group. Along the way, you'll also examine some other retail case studies, including web visitor analysis for marketing and store clustering for logistics. By the end, you'll be able to use customer purchase data to group customers using machine learning, analyse your results to extract business insights and apply multiple types of machine learning to generate business value. This course is unique because it focuses strongly on interpreting your data within a retail context and supports you in identifying opportunities for machine learning in your workplace. To be successful in this project, you should already be familiar with Python Pandas for data manipulation, filtering and aggregation. You should also have some experience with basic principles of data analysis, like histograms and summary statistics.
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O.P. Jindal Global University
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