Python for Business Analytics in Logistics 4.0
Learn the fundamentals of Python for business analytics applications in Logistics 4.0 and transform data into actionable knowledge for smarter decision-making.
Learn the fundamentals of Python for business analytics applications in Logistics 4.0 and transform data into actionable knowledge for smarter decision-making.
This comprehensive course introduces Python programming for business analytics in Logistics 4.0 applications. Python, one of the most widely used open-source programming languages in the scientific community since its 1991 launch, offers powerful analytical capabilities through various packages for probability, statistics, graphing, big data, machine learning, and optimization. The course focuses on using Python to apply analytics to typical Logistics 4.0 problems, covering introduction to business analytics for decision-making, application in Logistics 4.0, defining key business questions, fundamental Python programming elements, and important features of the Pandas library for data manipulation and analysis. This introductory course equips participants with the essential knowledge to continue learning independently and create value for organizations by transforming data into knowledge.
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What you'll learn
Learn to apply business analytics for decision-making in logistics operations
Master fundamental Python programming concepts and syntax
Use the Pandas library for effective data manipulation and analysis
Develop skills to define key business questions for logistics challenges
Apply analytical techniques to Logistics 4.0 problems
Gain the foundation needed for continued independent learning in Python
Skills you'll gain
This course includes:
PreRecorded video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
Shareable certificate
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There are 4 modules in this course
This course covers essential topics in both Python programming and business analytics for logistics applications. It begins with an introduction to business analytics for decision-making in Logistics 4.0, helping students understand how data analysis can solve real-world logistics problems. The course then transitions to Python fundamentals, teaching core programming concepts and syntax. Students learn how to apply these programming skills through the Pandas library for effective data manipulation and analysis. The curriculum emphasizes practical applications in logistics, preparing students to define key business questions and implement analytical solutions. The course serves as a foundation for continued independent learning in the field of data-driven logistics.
Analítica de datos aplicada a la Logística
Module 1
Fundamentos de Python
Module 2
Fundamentos de programación en Python
Module 3
Fundamentos de manipulación y análisis de datos en Python
Module 4
Fee Structure
Payment options
Financial Aid
Instructor
1 Course
Expert in Advanced Data Analytics and Business Intelligence
Julián David Reyes Rueda is a professor at Pontificia Universidad Javeriana and a seasoned leader in AI and Analytics, with over a decade of experience spanning retail, security and defense, and logistics. He specializes in advanced data analytics, including data visualization, KPI definition, statistical and predictive modeling, machine learning, simulation, and optimization. Julián has led interdisciplinary teams in AI, BI, and Business Analytics, with a talent for translating complex technical concepts for non-technical stakeholders. As an educator in statistics and business analytics, he teaches courses like Analítica de negocio en Python para Logística 4.0 on edX, equipping learners with the tools to drive data-driven decision-making in the digital age.
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