Intermediate Course

Python for Data Analysis & Forecast

Master Python programming for supply chain analytics and forecasting

All Industries E-commerce Manufacturing Retail Logistics
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Duration
20 Hours
Level
Intermediate
Format
Online / In-Person
Certificate
Included

Course Overview

This hands-on course teaches you how to leverage Python for supply chain analytics and forecasting. You will learn essential Python libraries, data manipulation techniques, visualization skills, and how to build predictive forecasting models using machine learning approaches.

What You'll Achieve

Develop autonomous data analysis workflows
Improve forecast accuracy using advanced algorithms
Generate actionable insights from complex data
Build interactive dashboards and reports
Automate repetitive analytical tasks

Course Curriculum

Master the following skills through our comprehensive modules:

Introduction to Python Fundamentals and Crash Course
4 topics
4 hours
Topics Covered:
  • Python syntax and data types
  • Control flow and functions
  • Data structures (lists, dictionaries, sets)
  • File handling and I/O operations
NumPy, Pandas, Matplotlib, Descriptive Statistics, Visualization
5 topics
6 hours
Topics Covered:
  • NumPy arrays and operations
  • Pandas DataFrames and Series
  • Data cleaning and preprocessing
  • Descriptive statistics with Pandas
  • Data visualization with Matplotlib
Data Management, Data Analysis, Excel and Python
4 topics
4 hours
Topics Covered:
  • Reading data from various sources (CSV, Excel, SQL)
  • Data merging and joining
  • Excel integration with Python
  • Automating Excel reports with Python
Demand Management and Forecasting, Excel Holt-Winter Method
4 topics
2 hours
Topics Covered:
  • Forecasting fundamentals
  • Time series components
  • Holt-Winters method in Excel
  • Seasonality handling
Python Forecasting Data Preparation and Holt-Winter in Python
4 topics
2 hours
Topics Covered:
  • Time series data preparation in Python
  • Implementing Holt-Winters in Python
  • Model evaluation metrics
  • Forecast accuracy measurement
Auto Regressive Integrated Moving Average (ARIMA)
4 topics
2 hours
Topics Covered:
  • ARIMA model fundamentals
  • Stationarity and differencing
  • ACF and PACF analysis
  • ARIMA implementation in Python

Practical Applications

  • Analyze large supply chain datasets using Python libraries (Pandas, NumPy)
  • Build predictive forecasting models using machine learning techniques
  • Create data visualizations and dashboards for supply chain insights
  • Automate report generation and data refresh processes

Certification

Receive an official 'Python for Supply Chain Analytics' certificate from Think Supply Chain upon successful completion

Career Impact

Python skills are in high demand across industries. Supply chain professionals with programming skills can command 30-50% higher salaries.

Your Instructor

Instructor

Hazem Hamza

Supply Chain & Data Science Consultant

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With over 12 years of experience in supply chain management across manufacturing, retail, and logistics industries, Data Science and Software Engineering projects, Hazem brings practical expertise and academic excellence to help professionals advance their careers.

Ready to Enroll?

20 Hours
Limited seats available
20 Hours Training
Official Certificate
Expert Instructor
Practical Projects
1-on-1 Support

Contact us via WhatsApp for inquiries

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