BUSINESS ANALYTICS USING PYTHON

Description

With the integration of social media with businesses, there have emerged new data analytical needs involving unstructured data, especially textual data like online product reviews, Twitter/Facebook messages, transcripts of phone call logs. In this course, we will learn about some of the new analytical needs that businesses have and how we can solve them using Python programming. The course is designed for students with basic-to-average background in programming. Thèmes clés / Key Topics: Data science, data, business analytics, Python programming Organisation du cours – plan détaillé / Course organization - detailed outline: 6 sessions of 3 hours, once per week during one bimester The course consists of six parts: - Part 1: Introduction & Python Basics - Part 2: Data Visualization and Supervised learning (basics) - Part 3: Supervised learning (classification): Logistic Regression - Part 4: Nonlinear Models: Naïve Bayes / Decision trees / Random forest - Part 5: Unsupervised Learning: Clustering and topic modeling - Part 6: Group Project Presentation Contenus ESG / ESG-related content (Environmental – Social – Governance): Environmental-r elated content Social-relat ed content Governance-re lated content 1. Minimal content 2. Moderate content 2. Moderate content Assessment Information: Pondération dans Outils / support / mode d’évaluation Durée et format la notation finale Tool/method of evaluation Duration Weight in the final grading Classroom citizenship & contribution Individual 10% Final Project - Report Group 40% Final Project - Presentation Group 40% Final Project – Individual contribution based on teammate assessment Individual 10%