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Big Data Analytics for Supply Chain Optimization

$199.00
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Big Data Analytics for Supply Chain Optimization



Course Overview

This comprehensive course is designed to equip supply chain professionals with the skills and knowledge needed to harness the power of big data analytics and drive optimization in their supply chain operations. Through interactive and engaging lessons, participants will gain hands-on experience with real-world applications and projects, and receive a certificate upon completion.



Course Objectives

  • Understand the fundamentals of big data analytics and its application in supply chain optimization
  • Learn how to collect, process, and analyze large datasets to inform supply chain decisions
  • Develop skills in data visualization and reporting to communicate insights to stakeholders
  • Apply machine learning and predictive analytics to improve supply chain forecasting and risk management
  • Optimize supply chain operations using data-driven insights and analytics


Course Curriculum

Module 1: Introduction to Big Data Analytics

  • Defining big data and its relevance to supply chain management
  • Overview of big data analytics tools and technologies
  • Understanding data types and sources in supply chain operations
  • Case studies: Big data analytics in supply chain success stories

Module 2: Data Collection and Processing

  • Data sources and collection methods in supply chain operations
  • Data processing and cleaning techniques
  • Data storage and management options
  • Hands-on exercise: Data collection and processing using Python

Module 3: Data Analysis and Visualization

  • Descriptive statistics and data visualization techniques
  • Inferential statistics and hypothesis testing
  • Data visualization tools and software (Tableau, Power BI, etc.)
  • Hands-on exercise: Data analysis and visualization using Excel and Tableau

Module 4: Machine Learning and Predictive Analytics

  • Introduction to machine learning and predictive analytics
  • Supervised and unsupervised learning techniques
  • Model evaluation and selection
  • Hands-on exercise: Building a predictive model using Python and scikit-learn

Module 5: Supply Chain Optimization

  • Introduction to supply chain optimization techniques
  • Linear and integer programming
  • Dynamic programming and stochastic optimization
  • Hands-on exercise: Optimizing supply chain operations using Python and PuLP

Module 6: Case Studies and Project Work

  • Real-world case studies of big data analytics in supply chain optimization
  • Guided project work: Applying big data analytics to a supply chain problem
  • Peer review and feedback


Course Features

  • Interactive and engaging lessons with real-world applications and projects
  • Comprehensive curriculum covering all aspects of big data analytics for supply chain optimization
  • Personalized learning experience with expert instructors and peer feedback
  • Up-to-date content with the latest tools and technologies
  • Practical hands-on exercises and projects
  • High-quality content with expert instructors
  • Certification upon completion
  • Flexible learning with lifetime access to course materials
  • User-friendly and mobile-accessible platform
  • Community-driven discussion forums and peer feedback
  • Actionable insights and takeaways
  • Hands-on projects with real-world applications
  • Bite-sized lessons for easy learning
  • Gamification and progress tracking


Certificate of Completion

Upon completing all course modules and achieving a passing grade, participants will receive a Certificate of Completion. This certificate is a testament to the participant's expertise in big data analytics for supply chain optimization and can be showcased on resumes, LinkedIn profiles, and other professional platforms.

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