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Rajvir Dua
and
Neelesh Tiruviluamala
In this course, we'll make predictions on product usage and calculate optimal safety stock storage. We'll start with a time series of shoe sales across multiple stores on three different continents. To begin, we'll look for unique insights and other interesting things we can find in the data by performing groupings and comparing products within each store. Then, we'll use a seasonal autoregressive integrated moving average (SARIMA) model to make predictions on future sales. In addition to making predictions, we'll analyze the provided statistics (such as p-score) to judge the viability of using the SARIMA model to make predictions. Then, we'll tune the hyper-parameters of the model to garner better results and higher statistical significance. Finally, we'll make predictions on safety stock by looking to the data for monthly usage predictions and calculating safety stock from the formula involving lead times.
Register for this course and see more details by visiting:
OpenCourser.com/course/x89u94/capstone
What's inside
Syllabus
Exploratory Data Analysis Using Pandas and Groupby
In this module, we'll get acquainted with our dataset by exploring some of the most obvious groupings and identifying the variation in products. We'll discover which products sell where and prepare ourselves to use timeseries forecasts and safety stock predictions.
Read more
Syllabus
Exploratory Data Analysis Using Pandas and Groupby
In this module, we'll get acquainted with our dataset by exploring some of the most obvious groupings and identifying the variation in products. We'll discover which products sell where and prepare ourselves to use timeseries forecasts and safety stock predictions.
Read more
Demand Predictions Using SARIMA
In this module, we'll use the SARIMA model to make predictions on future sales. We'll then visualize some of these predicted sales before evaluating the accuracy and viability of our chosen model.
Calculating Safety Stock
In this module, we'll finish the project by calculating safety stock from monthly usage and lead times. We'll start by grouping products in order to find more accurate usage numbers. Then, we'll conclude by using the known formula along with our insights from the data in the calculation of safety stock for each product.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suits working professionals who want to specialize in using Python to make predictions on product usage and calculate optimal safety stock storage
Develops skills in data analysis by applying Python libraries, such as Pandas and Groupby
Explores using a seasonal autoregressive integrated moving average (SARIMA) model to make predictions on future sales
Taught by Rajvir Dua and Neelesh Tiruviluamala, who are experts in the field of data analysis and forecasting
Uses a real-world dataset to provide hands-on experience in making predictions and calculating safety stock
Requires familiarity with Python and basic data analysis concepts
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Capstone Project: Predicting Safety Stock with these
activities:
Summarize key concepts from lectures and readings
Show steps
Enhance your understanding and retention by summarizing key concepts from course materials.
Show steps
-
Review lecture notes and assigned readings.
-
Identify the main ideas and supporting details.
-
Create concise summaries in your own words.
Review statistics
Show steps
Review the fundamentals of statistics to strengthen your foundation for understanding the course materials.
Browse courses on
Statistics
Show steps
-
Consult your notes on descriptive statistics or a statistics textbook.
-
Practice solving statistics problems involving mean, median, mode, range, and standard deviation.
-
Review the concepts of probability and hypothesis testing.
Read 'Time Series Analysis and Its Applications'
Show steps
Gain a deeper understanding of time series analysis techniques by reviewing this foundational text.
View
Time Series Analysis and Its Applications: With...
on Amazon
Show steps
-
Read Chapters 1-3 to grasp the basic concepts of time series analysis.
-
Focus on the sections covering SARIMA models in Chapter 4.
-
Complete the practice exercises at the end of each chapter to reinforce your understanding.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow online tutorials on time series forecasting
Show steps
Expand your knowledge and skills by following guided tutorials on time series forecasting.
Browse courses on
Time Series Analysis
Show steps
-
Search for online courses or tutorials on time series forecasting platforms.
-
Choose tutorials that align with your learning goals and skill level.
-
Follow the instructions and complete the exercises provided in the tutorials.
Attend a study group or discussion forum on time series analysis
Show steps
Engage with peers to clarify concepts and exchange insights on time series analysis.
Browse courses on
Time Series Analysis
Show steps
-
Join an online or in-person study group focused on time series analysis.
-
Participate in discussions, ask questions, and share your understanding.
-
Collaborate with others to solve problems or work on projects.
Solve time series analysis problems
Show steps
Enhance your analytical skills by practicing time series analysis problems.
Browse courses on
Time Series Analysis
Show steps
-
Find online resources or textbooks with practice problems.
-
Start with simpler problems and gradually move on to more complex ones.
-
Check your solutions against provided answers or consult with classmates or instructors for feedback.
Create a visual representation of time series data
Show steps
Solidify your understanding of time series data by creating visual representations.
Browse courses on
Data Visualization
Show steps
-
Choose a time series dataset and import it into a visualization tool.
-
Experiment with different chart types, such as line charts, scatter plots, and heatmaps.
-
Analyze the visualizations and identify patterns or trends in the data.
Apply SARIMA models to a real-world dataset
Show steps
Gain practical experience by applying the concepts learned in the course to a real-world dataset.
Browse courses on
Time Series Analysis
Show steps
-
Identify a suitable dataset that exhibits time series patterns.
-
Apply the SARIMA modeling process: data exploration, model selection, and evaluation.
-
Present your findings and insights from the analysis.
Summarize key concepts from lectures and readings
Show steps
Enhance your understanding and retention by summarizing key concepts from course materials.
Show steps
Show steps
Show steps
- Review lecture notes and assigned readings.
- Identify the main ideas and supporting details.
- Create concise summaries in your own words.
Review statistics
Show steps
Review the fundamentals of statistics to strengthen your foundation for understanding the course materials.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Consult your notes on descriptive statistics or a statistics textbook.
- Practice solving statistics problems involving mean, median, mode, range, and standard deviation.
- Review the concepts of probability and hypothesis testing.
Read 'Time Series Analysis and Its Applications'
Show steps
Gain a deeper understanding of time series analysis techniques by reviewing this foundational text.
View
Time Series Analysis and Its Applications: With...
on Amazon
Show steps
Show steps
Show steps
- Read Chapters 1-3 to grasp the basic concepts of time series analysis.
- Focus on the sections covering SARIMA models in Chapter 4.
- Complete the practice exercises at the end of each chapter to reinforce your understanding.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Follow online tutorials on time series forecasting
Show steps
Expand your knowledge and skills by following guided tutorials on time series forecasting.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Search for online courses or tutorials on time series forecasting platforms.
- Choose tutorials that align with your learning goals and skill level.
- Follow the instructions and complete the exercises provided in the tutorials.
Attend a study group or discussion forum on time series analysis
Show steps
Engage with peers to clarify concepts and exchange insights on time series analysis.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Join an online or in-person study group focused on time series analysis.
- Participate in discussions, ask questions, and share your understanding.
- Collaborate with others to solve problems or work on projects.
Solve time series analysis problems
Show steps
Enhance your analytical skills by practicing time series analysis problems.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Find online resources or textbooks with practice problems.
- Start with simpler problems and gradually move on to more complex ones.
- Check your solutions against provided answers or consult with classmates or instructors for feedback.
Create a visual representation of time series data
Show steps
Solidify your understanding of time series data by creating visual representations.
Browse courses on
Data Visualization
Show steps
Show steps
Show steps
- Choose a time series dataset and import it into a visualization tool.
- Experiment with different chart types, such as line charts, scatter plots, and heatmaps.
- Analyze the visualizations and identify patterns or trends in the data.
Apply SARIMA models to a real-world dataset
Show steps
Gain practical experience by applying the concepts learned in the course to a real-world dataset.
Browse courses on
Time Series Analysis
Show steps
Show steps
Show steps
- Identify a suitable dataset that exhibits time series patterns.
- Apply the SARIMA modeling process: data exploration, model selection, and evaluation.
- Present your findings and insights from the analysis.
Career center
Learners who complete Capstone Project: Predicting Safety Stock will develop knowledge and skills
that may be useful to these careers:
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and analytical methods to solve complex problems in various industries, including supply chain management. By understanding the principles of predicting product usage and calculating optimal safety stock storage, as taught in the Capstone Project: Predicting Safety Stock course, individuals can develop valuable skills for this role. The course provides a solid foundation in time series analysis and forecasting techniques, which are essential for optimizing inventory levels and ensuring efficient operations.
Demand Planner
Demand Planner
Demand Planners utilize forecasting models, including seasonal autoregressive integrated moving average (SARIMA) models, to predict future product demand. The Capstone Project: Predicting Safety Stock course offers hands-on experience in applying SARIMA models for this purpose, making it highly relevant for individuals aspiring to become Demand Planners. Understanding how to analyze historical sales data, identify patterns, and make accurate forecasts is crucial for effective demand planning and inventory management.
Supply Chain Analyst
Supply Chain Analyst
Supply Chain Analysts play a critical role in optimizing supply chain efficiency. The Capstone Project: Predicting Safety Stock course provides foundational knowledge in safety stock calculation and inventory management, which are essential skills for this profession. By learning how to analyze product usage patterns and calculate optimal safety stock levels, individuals can contribute to reducing inventory costs and improving supply chain performance.
Inventory Manager
Inventory Manager
Inventory Managers are responsible for managing inventory levels and ensuring product availability. The Capstone Project: Predicting Safety Stock course offers practical insights into predicting product usage and calculating safety stock. This knowledge enables Inventory Managers to optimize inventory levels, reduce waste, and improve customer satisfaction by minimizing stockouts and overstocking.
Business Analyst
Business Analyst
Business Analysts utilize data analysis techniques to identify opportunities for business improvement. The Capstone Project: Predicting Safety Stock course provides a solid foundation in data analysis, forecasting, and statistical modeling. These skills are highly sought after by Business Analysts, who use them to analyze business data, identify trends, and make recommendations for optimizing operations.
Data Scientist
Data Scientist
Data Scientists apply statistical and machine learning techniques to extract insights from data. The Capstone Project: Predicting Safety Stock course introduces foundational concepts of time series analysis and forecasting, which are core skills for Data Scientists. By understanding how to analyze historical data, make predictions, and evaluate model performance, individuals can develop a strong foundation for a career in data science.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. The Capstone Project: Predicting Safety Stock course provides a solid foundation in time series analysis and forecasting techniques, which are essential for Quantitative Analysts. By learning how to analyze historical data, identify patterns, and make accurate predictions, individuals can develop valuable skills for this role.
Market Research Analyst
Market Research Analyst
Market Research Analysts study market trends and consumer behavior to identify opportunities for businesses. The Capstone Project: Predicting Safety Stock course offers a practical understanding of forecasting techniques and data analysis, which are valuable skills for Market Research Analysts. By learning how to analyze historical data, make predictions, and interpret market trends, individuals can gain insights into consumer behavior and develop effective marketing strategies.
Financial Analyst
Financial Analyst
Financial Analysts evaluate financial data to make investment recommendations and assess the financial health of companies. The Capstone Project: Predicting Safety Stock course provides a foundation in statistical modeling and forecasting, which are useful skills for Financial Analysts. By understanding how to analyze historical data, identify trends, and make predictions, individuals can enhance their ability to make informed investment decisions.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty in various fields, including insurance and finance. The Capstone Project: Predicting Safety Stock course provides a foundation in statistical modeling and forecasting, which are valuable skills for Actuaries. By learning how to analyze historical data, make predictions, and evaluate model performance, individuals can develop a strong foundation for a career in actuarial science.
Business Consultant
Business Consultant
Business Consultants provide advice and guidance to businesses on a range of operational and strategic issues. The Capstone Project: Predicting Safety Stock course offers insights into data analysis, forecasting, and inventory management, which are relevant to Business Consultants. By understanding how to analyze business data, identify trends, and make recommendations for improvement, individuals can develop valuable skills for this role.
Operations Manager
Operations Manager
Operations Managers oversee the day-to-day operations of an organization. The Capstone Project: Predicting Safety Stock course provides a practical understanding of inventory management and forecasting techniques, which are essential for Operations Managers. By learning how to analyze product usage patterns, predict demand, and optimize inventory levels, individuals can develop valuable skills for this role.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. The Capstone Project: Predicting Safety Stock course offers insights into product demand forecasting, which is a critical aspect of product management. By understanding how to analyze historical sales data, make predictions, and identify trends, individuals can gain valuable skills for this role.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns to promote products and services. The Capstone Project: Predicting Safety Stock course provides a foundation in forecasting and market research, which are useful skills for Marketing Managers. By understanding how to analyze historical data, make predictions, and identify market trends, individuals can enhance their ability to develop effective marketing strategies.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to provide insights for businesses. The Capstone Project: Predicting Safety Stock course offers a practical understanding of data analysis and forecasting techniques, which are valuable skills for Data Analysts. By learning how to analyze historical data, make predictions, and identify trends, individuals can develop a strong foundation for a career in data analytics.
For more career information including salaries, visit:
OpenCourser.com/course/x89u94/capstone
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Capstone Project: Predicting Safety Stock .
Save
Provides a comprehensive overview of time series analysis techniques, including advanced topics such as state-space models and machine learning algorithms.
Save
Provides a comprehensive overview of forecasting methods, including time series analysis techniques such as SARIMA. It offers a practical approach to forecasting, with examples and exercises to help readers apply the concepts to real-world problems.
Save
This classic textbook provides a rigorous foundation in time series analysis and forecasting methods. It covers a wide range of topics, including SARIMA models, exponential smoothing, and other advanced techniques.
This classic textbook provides a thorough introduction to time series analysis, covering both theoretical and practical aspects. It includes detailed explanations of SARIMA models and other time series forecasting techniques.
Save
This comprehensive handbook provides an in-depth overview of forecasting techniques and applications. It includes chapters on time series analysis, SARIMA models, and other advanced forecasting methods.
Save
Focuses on the practical aspects of demand forecasting for business managers. It provides step-by-step guidance on how to develop and implement forecasting models, with a focus on accuracy and reliability.
Presents a collection of case studies on forecasting in various industries. It provides real-world examples of how forecasting models are developed and implemented, highlighting the challenges and successes encountered.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/x89u94/capstone
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Effort
3 weeks of study, 3-4 hours/week
Level
Intermediate
Via
Coursera
Institution
LearnQuest
Instructors
Rajvir Dua
Neelesh Tiruviluamala
Language
English
This course belongs to a
collection
called
Machine Learning for Supply Chains. It's comprised of four courses:
- Advanced AI Techniques for the Supply Chain
- Capstone Project: Predicting Safety Stock (viewing)
- Demand Forecasting Using Time Series
- Fundamentals of Machine Learning for Supply Chain
Good to know
Suits working professionals who want to specialize in using Python to make predictions on product usage and calculate optimal safety stock storage
Develops skills in data analysis by applying Python libraries, such as Pandas and Groupby
Explores using a seasonal autoregressive integrated moving average (SARIMA) model to make predictions on future sales
Taught by Rajvir Dua and Neelesh Tiruviluamala, who are experts in the field of data analysis and forecasting
Uses a real-world dataset to provide hands-on experience in making predictions and calculating safety stock
Requires familiarity with Python and basic data analysis concepts
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