Business and Data Analytics in Python

Mastering Data-Driven Insights and become a Business Analytics Practitioner

Created by: Dr. Giancarlo Crocetti
University Professor and Instructor at Udemy

What Will I Learn?

• Master Business Analytics Basics: Understand fundamental concepts and data-driven decision-making techniques.
• Python Proficiency: Gain skills in Python for data analysis with key libraries like Pandas and NumPy.
• Statistical Decision Making: Learn inferential statistics to support business insights.
• Econometrics & Regression: Master econometric models and regression analysis for predicting outcomes.
• Time-Series Analysis: Acquire forecasting skills using Python for economic and business trends.
• Customer Segmentation: Analyze customer behavior and market segments for targeted strategies.
• Cultivate a Data-Driven Mindset: Develop critical thinking for data interpretation and decision-making.
• Real-World Data Practice: Apply business analytics techniques to industry-specific datasets.
• High Academic Quality: Experience content and methods at the level of graduate classes in U.S. universities.
• Career Preparation: Equip yourself for roles in business analytics with in-demand skills and knowledge.

Requirements

• An understanding of Python programming at the most basic level. You should be comfortable with variables, basic data types, loops, and functions.
• Willingness to Learn: Approach the course with enthusiasm for learning new analytical techniques and applying them to real-world business scenarios.

Target audience

• Aspiring Data Analysts and Business Analysts: Beginners or those transitioning from other fields who want to build a career in data analytics or business analytics.
• Professionals in Business and Finance: Individuals in business, finance, marketing, or related fields seeking to enhance their decision-making with data-driven insights.
• Entrepreneurs and Small Business Owners: Those looking to leverage data to make informed decisions, understand market trends, and drive business growth.
• Business Managers in Analytical Departments: Managers and supervisors looking to deepen their analytical capabilities to drive decision-making and strategy.
• Students in Business, Economics, or IT: Undergraduates or postgraduates desiring to enhance their academic knowledge with practical analytics and Python skills.
• IT Professionals and Software Developers: Those looking to expand their skills into business analytics to support data-driven projects or transition into analytics roles.
• Curious Learners: Anyone interested in applying Python to tackle real-world business challenges and to inform decisions with data.