This specialization is intended for students who wish to use machine language to analyze and predict product usage and other similar tasks. There is no specific prerequisite but some general knowledge of supply chain will be helpful, as well as general statistics and calculus.
Machine Learning for Supply Chains Specialization
Machine Learning for Supply Chains Specialization
Use Machine Learning in the Supply Chain. You will learn to use machine language techniques to analyze and predict retail stock in the supply chain.
Instructors: Neelesh Tiruviluamala
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Get in-depth knowledge of a subject
(66 reviews)
Intermediate level
Recommended experience
1 month at 10 hours a week
Flexible schedule
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Share your expertise with employers
Get in-depth knowledge of a subject
(66 reviews)
Intermediate level
Recommended experience
1 month at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Skills you'll gain
- Image Analysis
- Data Visualization
- Demand Planning
- Data Science
- Supervised Learning
- Operations Research
- Inventory Management
- Data Wrangling
- Data Analysis
- Applied Machine Learning
- Data Manipulation
- Trend Analysis
- Time Series Analysis and Forecasting
- Machine Learning
- Supply Chain
- Machine Learning Methods
- Exploratory Data Analysis
- Feature Engineering
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
17 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from LearnQuest
Specialization - 4 course series
What you'll learn
Learn to merge, clean, and manipulate data using Python libraries such as Numpy and Pandas
Gain familiarity with the basic and advaned Python functonalities such as importing and using modules, list compreohensions, and lambda functions.
Solve a supply chain cost optimization problem using Linear Programming with Pulp
Skills you'll gain
Python Programming, Data Structures, NumPy, Data Manipulation, Data Analysis, Programming Principles, Pandas (Python Package), Data Transformation, Computer Programming, Data Cleansing, Data Wrangling, Supply Chain, Applied Machine Learning, Exploratory Data Analysis, Data Science, Operations Research, and Plot (Graphics)
What you'll learn
Building ARIMA models in Python to make demand predictions
Developing the framework for more advanced neural netowrks (such as LSTMs) by understanding autocorrelation and autoregressive models.
Skills you'll gain
Time Series Analysis and Forecasting, Correlation Analysis, Trend Analysis, Regression Analysis, Forecasting, Pandas (Python Package), Predictive Modeling, Customer Demand Planning, Exploratory Data Analysis, Demand Planning, Machine Learning, Plot (Graphics), Data Visualization, Applied Machine Learning, Data Analysis, Matplotlib, Statistical Modeling, Predictive Analytics, Python Programming, and Supply Chain Management
What you'll learn
Skills you'll gain
Image Analysis, Machine Learning Methods, Computer Vision, Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, Natural Language Processing, Supply Chain, Supervised Learning, Machine Learning, Anomaly Detection, Supply Chain Management, Applied Machine Learning, Demand Planning, Machine Learning Algorithms, Random Forest Algorithm, Deep Learning, Statistical Modeling, Predictive Modeling, Customer Demand Planning, and Classification And Regression Tree (CART)
What you'll learn
Calcualte safety stock using SARIMA predictions combined with manipulaitng lead times.
Skills you'll gain
Predictive Modeling, Exploratory Data Analysis, Pandas (Python Package), Time Series Analysis and Forecasting, Predictive Analytics, Machine Learning, Feature Engineering, Matplotlib, Data Transformation, Forecasting, Inventory Management System, Data Analysis, Data Manipulation, Demand Planning, Inventory Management, Inventory Control, Data Visualization, Statistical Modeling, and Data Wrangling
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Frequently asked questions
To complete all four courses, you will spend 3-5 hours per week for 13 weeks.
Machine learning is mathematical. There are no specific background requirements, but knowledge of algebra and calculus will be helpful, as well as a general understanding of supply chain concepts.
Yes, the courses build knowledge as they progress so we recommend taking them in order.
More questions
Financial aid available,