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

200+ hours | Online & Live | Weekend Program

700+ hours | Hybrid Program | in Campus Immersion

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

In collaboration with IIT Madras Pravartak

Developed by IIT Madras faculty in collaboration with Zenith Railway Academy and industry proponents, the 6-month intensive program weaves together academic lectures from IIT faculty, domain experts from Industries with hands-on practical sessions, assignments and capstone project to provide as experiential learning in artificial intelligence with focus on rail communication, application and safety and rail safety.

Are You Interested In the Program?

Connect with an advisor for a 1:1 Session.

Batch

01 Learning Format

Online/Live

Live Classes

6 Months

Starts

19th April 2025 | Weekend Program

IITM Pravartak

About Program

Developed by IIT Madras faculty in collaboration with Zenith Railway Academy and industry proponents, the 6-month intensive program weaves together academic lectures from IIT faculty, domain experts from Industries with hands-on practical sessions, assignments and capstone project to provide as experiential learning in artificial intelligence with focus on rail communication, application and safety and rail safety. This 6-month weekend online program is designed for working professionalsin the railway industry and tech graduates aiming to build a career in AI applications within the rail and smart mobility sectors. Gain in-depth knowledge and practical skills from industry experts, exploringcutting-edge technologies and their implementation in enhancing rail operations and smart transportation systems. Elevate your career prospects with this comprehensive course, merging theoretical foundations with real-world applications to revolutionize the future of mobility. As the rail industry evolves towards digitalization, this program addresses the growing need for AI expertise, preparing professionals to lead in innovation, improve operational efficiency, and ensure safety. Graduates will be well-positioned for advanced roles in AI applications within the rail and smart mobility sectors, driving future advancements and sustainable solutions.

Key Highlights

01. 200 hours of live online training
02. Certification from IITM Pravartak
03. India’s Top Faculties.
04. Weekend online & interactive Classes
05. Career & Placement Assistance
06. Industry interactions
07. Case Based Sessions

Are You Interested In the Program?

Connect with an advisor for a 1:1 Session.

Who should Apply ?

The program is designed for engineers/ who wish to learn and apply AI knowledge in their respective roles, across the globe in various rail projects.
Engineers/professionals currently working in organizations that provide solutions to either railway products & services, or design or implement railway or transport solutions may also consider applying to this program.
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.

Who should Apply ?

The program is designed for engineers/ who wish to learn and apply AI knowledge in their respective roles, across the globe in various rail projects.
Engineers/professionals currently working in organizations that provide solutions to either railway products & services, or design or implement railway or transport solutions may also consider applying to this program.
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.

ABOUT THE INSTITUTE

IIT Madras Pravartak

The Institute is set up with the objective of providing quality management education while sensitizing students towards the needs of the society.
The faculty at IIT Madras Pravartak represent the best mix of academic and industrial experiences.
The Institute is located in one of the most densely industrialized regions in the country with over 180 industries having plants in and around the region. This places the Institute at a vantage point when it comes to ‘Learning by Doing’ via frequent industry interactions and live projects.
The rigorous curriculum seeks to instil a passion for knowledge and ability to apply that knowledge to real life scenarios.

There will be a huge demand for rail professionals who understand and appreciate artificial intelligence as an integral part of rail operations; Application areas where professionals will be needed

AI and Data Science Engineer (Railways)

Rail Predictive Maintenance Engineer

Generative AI Specialist (Rail)

Rail Traffic Optimization Analyst

Data Scientist (Rail Operations)

Get Certified by IIT Madras Pravartak

Railway Academy has collaborated with IIT Madras Pravartak to bring you a globally recognised certificate which you can use across the globe.

Meet Our Faculty

David Cuesta Teaches ERTMS for Railways

Dr. P Raja Goundan Teaches RAMS & Safety

V G Ramesh Kumar Teaches Signaling & Telecom Systems

Sreevas Vasudevan Teaches EMI and EMC

Surendranath Bopparaju Teaches Safety Critical Product development

Mr. Teaches NSW signaling & IRSE Modules

A . V. R. Subbarao Teaches signaling & signaling design

Narayan Parvatikar Teaches Signaling & IRATP

Dr. Ajeet Pandey Teaches RAMS & functional Safety

Mohan Bidkar Teaches Overhead electrification(OHE)

B. Sambireddy Teaches axle counters & interlocking

Kirtivasan Vaidyanathan Teaches UK signaling & IRSE Modules

M.U.M. V P RAO Teaches rolling stock & traction

J. S Korla Teaches signaling and interlocking

Are You Interested In the Program?

The application is free and will only take 5 minutes to complete

Curriculum (25 Sessions)

• 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

Session 1: Introduction to AI and Data Science in Rail Domain
Session 2: Current Data Ingestion in Railways
Session 3: Descriptive Analysis with Python-Matplotlib
Session 4: Advanced Data Visualization with Power BI Session
5: Descriptive and Statistical Analytics in Railways
Session 6: Automated Customer Chat
Session 7: Predictive Analytics in Railway Hardware/Software Ecosystem
Session 8: Electric and Electronic Data-Based Predictive Systems
Session 9: Introduction to Deep Learning in Rail Domain
Session 10: Generative AI for Rail Domain Applications
Session 11: Applications of Deep Learning in Rail Safety
Session 12: Deep Learning for Enhanced Pilot Attention
Session 13: Advanced Deep Learning Techniques for Railways
Session 14: Integration of AI Technologies in Rail Operations
Session 15: Ethical Considerations in AI Applications for Railways
Session 16: Regulatory Framework for AI in Railways
Session 17: Real-world Implementation Challenges
Session 18: Project Management in AI Implementation for Railways
Session 19: Cost-Benefit Analysis of AI Implementation in Railways
Session 20: Business Case Development for AI Projects in Railways
Session 21: Future Trends in AI for Rail Domain
Session 22: Industry Perspectives on AI Adoption in Railways
Session 23: Career Opportunities in AI for Rail Professionals
Session 24: Capstone Project Presentation
Session 25: Course Conclusion and Next Steps

Curriculum (25 Sessions)

Session 1: Introduction to AI and Data Science in Rail Domain

Session 2: Current Data Ingestion in Railways

Session 3: Descriptive Analysis with Python-Matplotlib

Session 4: Advanced Data Visualization with Power BI

Session 5: Descriptive and Statistical Analytics in Railways

Session 6: Automated Customer Chat

Session 7: Predictive Analytics in Railway Hardware/Software Ecosystem

Session 8: Electric and Electronic Data-Based Predictive Systems

Session 9: Introduction to Deep Learning in Rail Domain

Specialization : Session 10: Generative AI for Rail Domain Applications

Session 11: Applications of Deep Learning in Rail Safety

Specialization : Session 12: Deep Learning for Enhanced Pilot Attention

Specialization : Session 13: Advanced Deep Learning Techniques for Railways

Session 14: Integration of AI Technologies in Rail Operations

Session 15: Ethical Considerations in AI Applications for Railways

Session 16: Regulatory Framework for AI in Railways

Session 17: Real-world Implementation Challenges

Session 18: Project Management in AI Implementation for Railways

Session 19: Cost-Benefit Analysis of AI Implementation in Railways

Session 20: Business Case Development for AI Projects in Railways

Session 21: Future Trends in AI for Rail Domain

Session 22: Industry Perspectives on AI Adoption in Railways

Session 23: Career Opportunities in AI for Rail Professionals

Session 24: Capstone Project Presentation

Session 25: Course Conclusion and Next Steps

Session Summary