Professional Certificate Program in Artificial Intelligence and Data Science with GenAI: Applications in Rail

Program Description

•   Develop AI Proficiency: Equip participants with comprehensive knowledge of AI concepts and technologies, focusing on their applications in rail and smart mobility sectors.
•   Enhance Operational Efficiency: Teach the implementation of AI-driven solutions to optimize rail operations, improve safety, and increase the efficiency of smart transportation systems.
•   Foster Innovation: Encourage innovative thinking by exploring emerging AI trends and their potential to revolutionize rail and smart mobility, preparing participants to drive future advancements in the industry.
•   Hands-on Experience: Provide practical, hands-on experience with AI tools and techniques through real-world projects and case studies, ensuring participants can apply their learning effectively in professional settings.

 

Key Highlights

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As part of the Course in AI Applications for Railways and Smart Mobility, we offer an immersive Hands-On experience using latest AI Tool and popular in the industry.

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This practical component is designed to bridge theoretical knowledge with real-world applications, providing participants with direct experience using cutting-edge AI tools.

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Engage in interactive sessions where you will work on industry-relevant projects, guided by expert mentors. Gain proficiency in AI software and platforms essential for developing innovative solutions in rail and smart mobility. This hands-on approach ensures you are well-prepared to tackle challenges and drive advancements in the field.

Learning Format

Online

Duration

6 Months

Certified by

IITM Pravartak Technologies Foundation
Technology Innovation Hub (TIH) of IIT Madras and
Zenith Railway

Program Fee

(For Indian Residents)

80,000 + GST

For installment options kindly go through the brochure

Program Description

Education Qualification


  • For Indian Participants Graduates (10+2+3) or Diploma Holders (10+2) from a recognized university in any discipline.

  • For International Participants - Graduation or equivalent degree from any recognized University or Institution in their respective country

  • Preference shall be given to professionals with rail industry experience

Suggested Prerequisites

Basic understanding of rail technology, while not mandatory, will be an added advantage.

Teaching Hours

Twice a week on Saturdays & Sundays from 10.00a.m.to 12.00p.m.

Lead Faculty

M.U.MVaraprasad Rao 

Rail Expert

Experienced Rolling Stock &Traction expert with a demonstrated history of working on several railway and Metro projects in India and Skilled  in railway systems design, planning and management with Masters' degree in computer science from IIT Kanpur and a Bachelors in electrical Engg from Andhra University (India). Currently employed in Urban Mass Transit Company UMTCas Rolling stock expert.

 

Prof. Madhusudhanan Baskaran

Adjunct Faculty IIT Madras

Professional with a Ph.D. in AIML and working towards a Post – Doctoral in the field of Large Language Models with 31 years of experience in business and technical aspects of product development from the discovery/innovation stage to product launch.

Learning Module

• Overview of the course objectives and structure
• Introduction to AI and its applications in the rail domain
• Importance of data in railways and its future implications
• Understanding the digitization requirements for railways

• Analysis of data sources currently used in railways
• Exploring data from edge devices: drones, POS terminals, digital signaling equipment
• Understanding customer feedback data and its significance

• Introduction to Python for data analysis
• Basic data visualization techniques using Matplotlib
• Case studies on descriptive analysis in railways

• Introduction to Power BI for data visualization
• Creating interactive dashboards for railway data
• Case studies on Power BI applications in railways

• Overview of descriptive and statistical analytics
• Application of analytics in coach optimization and queuing optimization
• Resource allocation techniques in railways

• Understanding the importance of customer service in railways
• Introduction to automated customer chat systems
• Building a simple chatbot for railway customer queries

• Introduction to predictive analytics
• Predictive maintenance in railway hardware and software
• Case studies on track quality monitoring and defect detection

• Understanding electric and electronic data in railways
• Introduction to predictive systems based on electric and electronic data
• Case studies on predictive maintenance using electric and electronic data

• Overview of deep learning technologies
• Application of deep learning in railway systems
• Understanding generative AI and its implications in railways

• Exploring generative AI techniques for railway applications
• Case studies on generative AI in rail domain problem-solving
• Hands-on exercise on building generative models for rail domain data

• Deep learning applications in safety monitoring
• Detecting cracks in tracks using deep learning
• Identifying defective signaling using deep learning techniques

• Understanding the role of pilot attention in railways
• Using deep learning to enhance pilot attention
• Case studies on improving safety with deep learning-based pilot attention
systems

• Exploring advanced deep learning architectures
• Application of advanced techniques in railway domain problems
• Hands-on workshop on implementing advanced deep learning models

• Overview of integrating AI technologies into railway operations
• Challenges and opportunities in AI integration
• Case studies on successful AI integration in rail operations

• Understanding ethical issues in AI applications for railways
• Discussion on bias, privacy, and transparency
• Developing ethical guidelines for AI implementation in railways

• Overview of regulatory frameworks governing AI in railways
• Compliance requirements for AI applications in railways
• Case studies on regulatory challenges and solutions

• Identifying real-world implementation challenges in AI for railways
• Strategies for overcoming implementation challenges
• Group discussion on potential solutions

• Introduction to project management principles
• Project planning and execution in AI implementation for railways
• Case studies on successful AI project management in railways

• Understanding the cost implications of AI implementation
• Assessing the benefits of AI in railways
• Conducting a cost-benefit analysis for AI projects in railways

 Developing a business case for AI projects in railways
• Identifying key stakeholders and their roles
• Presenting a business case for AI implementation in railways

• Exploration of future trends in AI for railways
• Emerging technologies and their implications
• Discussion on the future of AI in the rail domain

• Guest lecture from industry experts on AI adoption in railways
• Sharing industry insights and best practices
• Q&A session with industry professionals

• Overview of career opportunities in AI for rail professionals
• Skills and qualifications required for AI roles in railways
• Guidance on career development in the AI field

• Presentation of capstone projects by mentees
• Feedback and evaluation from peers and instructors
• Recognition of outstanding projects

• Review of key concepts covered in the course
• Reflection on personal learning journey
• Guidance on next steps for continued learning and professional development
in AI for rail domain



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