Implementing Supply Chain Analytics
- Offered byCoursera
Implementing Supply Chain Analytics at Coursera Overview
Duration | 18 hours |
Start from | Start Now |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Go to Website  |
Credential | Certificate |
Implementing Supply Chain Analytics at Coursera Highlights
- Earn a certificate from Coursera
- Add to your LinkedIn profile
- 19 assignments
Implementing Supply Chain Analytics at Coursera Course details
- SQL foundation
- Descriptive, diagnostic, predictive, and prescriptive analytics
- Python foundation
- In the Implementing Supply Chain Analytics: Descriptive, Diagnostic, Predictive and Prescriptive course, you'll discover how implementing analytical methods, models, and tools helps decision-making become more efficient
- You'll use different types of methods, models, and tools, depending on specific business scenarios or needs, to help you analyze the current state of the supply chain and to lead you to insightful solutions
- You'll also explore the utilization of supply chain models to evaluate and question the data to optimize the flow of goods, information, and cost in a supply chain to help identify potential improvements, determine the most efficient or practical course of action, and to communicate the impact to the customer
Implementing Supply Chain Analytics at Coursera Curriculum
Progamming languages: Python and SQL
Welcome to supply chain data analyst professional certificate
Welcome to implementing supply chain analytics: Descriptive, diagnostic, predictive and prescriptive
Programming languages
Introduction to Python and SQL
The difference between Python and SQL
When to use SQL
Use basic commands to query data for summarization
Filter out "noise" from available information
Build and standardize a structure for future usage
Optimize search from queries
Test query against sources
When to use Python
Use Python to collect and import data
Use Python to prepare and format data
Use Python to build and evaluate data models
How Python and SQL work together
Unilever positioning statement
Supply chain data analyst professional certificate syllabus
Common features of Python and SQL
Common tools that use SQL
Using Python for data analysis in practice
Programming languages and tools I use
SQL and Python
Using SQL to manage large amounts of data
Using SQL and Python for data analysis
Programming languages in the Supply Chain Analyst role
Data analytics that drive impactful decision making
Welcome to data analytics that drive impactful decision making
Four levels of data analytics
How the four levels of data analytics help drive expected outcomes
Identify the best way to communicate analytics
Descriptive anaytics
Conducting descriptive analytics
Visualizing descriptive analytics
How to identify the root cause
Visualizing diagnostic analytics
Applying predictive algorithms in Python
Applying predictive business rules in Python
Applying predictive algorithims with business rules in Python
Applying prescriptive algorithms to Python
Applying prescriptive business rules in Python
Applying prescriptive algorithms with business rules in Python
Types of data needed for all four levels
Communicating descriptive analytics
Diagnostic Analytics
Communicating diagnostic analytics
Predictive analytics
Visualizing Predictive Analytics
Communicating predictive analytics
Prescriptive analytics
Visualizing prescriptive analytics
Communicating prescriptive analytics
Prosacco Exemplar: Apply predictive and prescriptive analytics
Four levels of data analytics
Descriptive and diagnostic analytics
Predictive analytics
Prosacco Activity: Apply descriptive and diagnostic analytics
Prosacco Activity: Apply predictive and prescriptive analytics
Four levels of analytics
Your recommendations
Supply chain models: Inventory, Continuous Flow, Fast Chain
Welcome to supply chain models: Inventory, Continuous Flow, Fast Chain
Introduction to the Inventory Model
Inventory theory
Most common inventory models
Introduction to Continuous Flow Model
Continuous flow model fundamentals
Continuous flow model applications
Introduction to Fast Chain Model
Fast Chain Model fundamentals
Fast Chain Model applications
Trends and demand
Common constraints in inventory management
Continuous flow success cases
Challenges and constraints
Fast chain success cases
Prosacco Exemplar: Identify inventory strategy
Inventory model
Continuous Flow Model
Prosacco Activity: Identify inventory strategy
Supply Chain Models: Inventory, Continuous Flow, Fast Chain
Supply Chain Models: Efficient Chain, Agile, Custom-Configured, Flexible
Welcome to Supply Chain Models: Efficient Chain, Agile, Custom-Configured, Flexible
Introduction to the Efficient Chain Model
Manufacturing principles
Introduction to the Agile Model
Introduction to the custom-configured model
Custom-configured model fundamentals
Introduction to the Flexible Model
Efficient Chain Model Fundamentals
Introduction to procurement and storage
Efficient Chain Model applications
Efficient chain model success story
Efficient chain model challenges and constraints
Introduction to Project Management
Agile Model Fundamentals and Structure
Agile model success story
Agile model challenges and constraints
Agile model advantages and disadvantages
Custom-Configured Model Applications
Custom-configured model success story
Custom-configured model challenges and constraints
Flexible model fundamentals
Flexible Model Applications
Flexible model success story
Flexible model challenges and constraints
Choosing a Model
Presenting the action plan
What I like most about my job as a Supply Chain Analyst
Continue building your portfolio
Summary
Efficient chain model
Agile model
Custom-configured model
Flexible Model
Prosacco Activity: Supporting the supply chain
Supply chain models: Efficient chain, Agile, custom-configured, flexible
Implementing Supply Chain Analytics at Coursera Admission Process
Important Dates
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