Graduate Certificate in Data Analytics in Demand Planning
-- ViewingNowThe Graduate Certificate in Data Analytics in Demand Planning is a comprehensive course designed to meet the growing industry demand for data-driven decision-makers. This certificate course equips learners with essential skills in data analytics, statistical modeling, and demand planning, empowering them to drive business growth and optimize supply chain operations.
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GBP £ 140
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โข Data Analysis for Demand Planning: Introduction to data analysis techniques and tools used in demand planning. Topics include data cleaning, exploration, and visualization using libraries such as Python's Pandas, NumPy, and Matplotlib.
โข Statistical Methods for Demand Forecasting: Overview of statistical methods used in demand forecasting, including time series analysis, regression analysis, and probability distributions. This unit will cover popular forecasting techniques, such as ARIMA and exponential smoothing.
โข Machine Learning for Demand Planning: Exploration of machine learning techniques used for demand planning, including supervised and unsupervised learning algorithms. Topics may include clustering, classification, and regression techniques using libraries such as scikit-learn and TensorFlow.
โข Big Data Analytics for Demand Planning: Overview of big data analytics tools and techniques used for demand planning, including Hadoop, Spark, and NoSQL databases. This unit will cover data processing and analysis using big data frameworks.
โข Supply Chain Management and Demand Planning: Introduction to supply chain management principles and how they relate to demand planning. Topics include inventory management, distribution planning, and supply chain optimization.
โข Data Visualization for Demand Planning: Overview of data visualization techniques and tools used for demand planning, including data dashboards, charts, and graphs. This unit will cover popular data visualization libraries such as D3.js and Tableau.
โข Data Ethics and Privacy for Demand Planning: Exploration of data ethics and privacy considerations in demand planning, including data collection, storage, and analysis. Topics may include data protection regulations, data sharing agreements, and ethical considerations in machine learning.
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