Executive Program in AI for Operations & Supply Chain Excellence

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Executive Program in AI for Operations & Supply Chain Excellence

COURSE OVERVIEW

The AI for Operations Supply Chain course helps learners understand how Generative AI can transform operations, logistics, planning, and supply chain decision-making. Today, businesses need faster forecasting, smarter resource planning, and more resilient supply networks. Therefore, AI-driven operations knowledge is becoming increasingly important.

Through this course, learners explore how GenAI supports demand forecasting, inventory optimization, process automation, supplier evaluation, route planning, digital twins, and predictive maintenance. In addition, the course shows how AI can improve operational agility, sustainability, and real-time decision-making.

Moreover, this executive program connects theory with practical business applications. As a result, learners become better prepared to design, manage, and support AI-enabled operations and supply chain systems.

WHAT YOU'LL LEARN

By completing this AI for Operations Supply Chain course, learners will understand how Generative AI can improve operational efficiency, planning accuracy, and supply chain resilience.

Apply Generative AI for forecasting, planning, and operational efficiency
Use AI for logistics, supplier management, and real-time decision-making
Leverage AI-driven digital twins and predictive analytics for smarter operations
Build sustainable and resilient AI-enabled supply chains
Understand AI governance, ethics, and responsible use in operations

Overall, this course helps learners optimize, automate, and innovate with Generative AI for modern operations and supply chain excellence.

Optimize, Automate, and Innovate - Redefine Operations with Generative AI.

CURRICULUM

The AI for Operations Supply Chain curriculum is divided into nine practical learning sections. Each section helps learners understand how Generative AI, automation, planning, logistics, and supply chain intelligence work together.

In addition, the course begins with GenAI fundamentals and gradually moves toward operations planning, logistics, digital twins, sustainability, and smart operations. As a result, learners build both conceptual understanding and practical application skills.

Module 1: Introduction to Generative AI and Its Evolution

Topics Covered:

This section introduces Generative AI and explains why it has become important across industries. It also helps learners understand the history, limitations, and ethical concerns connected with AI adoption.

Meaning of Generative AI
History and milestones in AI development
Traditional AI versus Generative AI
Key drivers such as big data, compute power, and neural networks
Real-world applications of GenAI
Limitations and ethical considerations

As a result, learners build a strong foundation before moving into advanced AI applications in operations and supply chain management.

Module 2: Fundamentals of Large Language Models (LLMs)

Topics Covered

Large Language Models are central to many modern GenAI applications. Therefore, this section explains how models such as GPT, BERT, T5, and PaLM work behind the scenes.

Transformers and attention mechanism
GPT, BERT, T5, and PaLM comparisons
Training versus inference
Prompt engineering basics
Zero-shot, few-shot, and fine-tuning approaches
Responsible use of LLMs

In addition, learners understand how LLMs can be used responsibly in business, operations, and supply chain environments.

Module 3: Generative AI Tools and Platforms

Topics Covered

This section introduces popular AI tools and platforms used across professional domains. Instead of focusing only on theory, learners understand how different tools support different operational goals.

ChatGPT, Claude, Bing AI, and GitHub Copilot
Image generation tools such as DALL·E, Midjourney, and Stable Diffusion
AI tools for video, music, and voice
Open-source and proprietary GenAI tools
Tool selection based on professional goals

Moreover, this section helps learners choose suitable GenAI tools for productivity, planning, analysis, and operational decision-making.

Module 4: Prompt Engineering and Task Design

Topics Covered

Prompt engineering helps professionals get better results from AI tools. This section focuses on writing clear prompts, designing useful tasks, and reducing weak or misleading outputs.

Anatomy of an effective prompt
Zero-shot, few-shot, and structured prompting strategies
Task types such as summarization, translation, and code generation
Tool-specific prompting examples
Reducing hallucinations and bias through prompt tuning

Consequently, learners become more confident in using AI tools for planning, documentation, automation, and supply chain-related tasks.

Module 5: Ethical, Legal, and Societal Implications of GenAI

Topics Covered

AI must be used with responsibility, fairness, and professional judgment. Therefore, this section explores the ethical and legal boundaries of Generative AI.

AI hallucinations and misinformation
Plagiarism and content ownership concerns
Bias and fairness in LLMs
AI and job displacement
Global perspectives on AI regulation
Responsible AI frameworks, including OECD and EU AI Act references

Furthermore, learners understand why governance, transparency, and ethical decision-making are important in AI-enabled operations.

Module 6: GenAI in Everyday Productivity & Collaboration

Topics Covered

Generative AI can improve workplace productivity when used correctly. This section explains how professionals can use AI as a practical assistant for communication, documentation, and collaboration.

Writing, summarization, and content creation with AI
AI in Excel, PowerPoint, CRM, and documents
Workflow automation with Zapier and Make
AI for meetings, brainstorming, and reporting
Chatbots and virtual assistants

As a result, learners understand how AI can support everyday work before applying it to advanced operations and supply chain functions.

Module 7: AI in Operations Planning

Topics Covered

This section connects Generative AI with production planning, forecasting, scheduling, and operational efficiency. Learners explore how AI can improve planning accuracy and reduce operational delays.

Demand forecasting with Generative AI
Inventory optimization using AI-driven insights
AI-generated scheduling and workforce planning
AI in lean manufacturing and process optimization
Just-in-time operations supported by AI use cases

In addition, this section shows how AI can help teams make faster, more informed, and data-supported planning decisions.

Module 8: Supply Chain & Logistics with AI

Topics Covered

Supply chain performance depends on visibility, coordination, supplier reliability, and logistics efficiency. Therefore, this section focuses on how AI can improve sourcing, routing, and risk management.

AI-powered supplier evaluation
Sourcing automation with Generative AI
Route optimization and logistics planning
AI-driven risk management in global supply chains
AI-enabled warehouse automation use cases

Moreover, learners understand how AI can support stronger supply chain visibility and more resilient logistics operations.

Module 9: Future of Smart Operations

Topics Covered

The future of operations will depend on automation, sustainability, digital simulation, and intelligent decision-making. This section explores next-generation AI tools for smarter and more responsible operations.

AI digital twins for operations simulation
Predictive maintenance with GenAI-generated insights
Sustainable operations and green AI supply chains
Ethics and governance in AI-driven operations
Future-ready operational intelligence practices

Finally, learners understand how to prepare for smarter, faster, and more sustainable operations using Generative AI responsibly.

Live and Interactive Workshop on GenAI

This course includes a live and interactive GenAI workshop led by an expert trainer. Through this workshop, learners get real-time exposure to GenAI tools, techniques, and practical use cases across different domains.

In addition, the workshop helps learners connect course concepts with hands-on practice. Whether learners choose a generic GenAI course or a specialized track such as finance, marketing, HR, data science, cybersecurity, IoT, or operations, the workshop adds practical value to the certification journey.

See real-world GenAI applications through live demonstrations
Practise AI tools through guided hands-on activities
Interact with expert trainers and clarify important concepts
Understand how GenAI can be applied in work, studies, and projects
Build confidence to use AI tools in practical professional situations

As a result, this live workshop makes the certification more practical, industry-ready, and valuable for learners who want applied exposure to Generative AI.

WHO SHOULD ENROLL

The AI for Operations Supply Chain course is suitable for learners and professionals who want to understand how artificial intelligence can improve operations, logistics, production planning, and supply chain performance.

Moreover, the course is useful for people who want to build future-ready skills in forecasting, supplier management, warehouse automation, digital twins, and sustainable operations.

Operations and supply chain managers aiming to improve efficiency with AI
Manufacturing, logistics, and procurement professionals
Business analysts and data strategists exploring AI in operations
Students and professionals aspiring to enter AI-driven industrial roles
Technology leaders working on operational transformation initiatives

Therefore, this course is ideal for learners who want to design, manage, or support AI-enabled operations and supply chain systems.

WHAT YOU'LL GET

Learners receive structured course resources, practical exposure, and certification support throughout the program. In addition, the course provides learning material that helps participants revise concepts and apply them beyond the classroom.

Industry-recognized certification upon completion
Live and interactive workshop on GenAI
Hands-on exposure to GenAI tools for operational decision-making
Templates and frameworks for AI-led planning and forecasting
Real-world case studies on AI in manufacturing and logistics
Online access to course content

Furthermore, these resources help learners understand how AI-powered operations are used in real-world industries such as manufacturing, logistics, procurement, warehousing, and supply chain management.

PROJECT SUBMISSION

Choose Your Project Topic

- Explore the project topics available in the LMS.
- Check the project description, learning outcomes, and required skills.
- Ask your guide/mentor if you need help selecting a topic.
- Finalize your topic and proceed.

Submit Your Project

- Follow the Project Submission Guidelines (format, font, spacing, citations).
- Your report will go through a plagiarism check, so keep it original.
- Upload your final PDF report and any supporting files to the LMS.

Project Evaluation

- Your project is evaluated by:
  - Organization Mentor
  - Internal Faculty Supervisor
- They assess you on:
  - Quality and clarity of your report
  - Depth of understanding
  - Application of concepts to real tasks
  - Problem-solving skills
  - Professional behaviour and timely submission
  - Viva/Presentation (if required)
- Credits (2–4) are awarded as per UGC NEP 2020 guidelines.

Certificates & Results

- Your Internship Certificate will be issued after:
  - Report approval
  - Evaluation completion
  - Uploading the organization certificate
- Download your Internship Completion Certificate directly from the LMS.

OUTCOME

After completing the AI for Operations Supply Chain course, learners will be ready to apply Generative AI to enhance operational agility, forecasting accuracy, and supply chain resilience.

In addition, participants will understand how AI supports logistics optimization, supplier management, inventory planning, digital twins, predictive maintenance, and sustainable operations.

Overall, this course prepares learners to design AI-driven strategies that make organizations smarter, faster, more resilient, and future-ready.

KNOW MORE ABOUT

Explore Skilling Courses – Benefits and Offerings to understand how SkillGroom programs support practical learning, certification, career growth, and professional development.

Also, learners can browse related GenAI courses to build wider expertise in artificial intelligence, data science, cybersecurity, finance, marketing, IoT, and business strategy.

Finally, choose the course that best matches your career goals and begin building practical skills for the future of work.

SkILLING COURSES - BENEFITS AND OFFERINGS