Executive Learning • Professional Certificate
Advanced Executive Program in Cyber Security
Hands-on curriculum, industry mentors, and a capstone project to showcase your skills.
Program Overview
This program provides a strong foundation in power electronics and control systems for electric vehicles, covering converter topologies, motor drives, and battery management. It emphasizes conceptual understanding, system design, and control techniques essential for developing efficient and reliable EV powertrains. Designed by IISc faculty, the program enables professionals to gain advanced knowledge and stay aligned with the growing EV industry.
Lakshminarayana Rao
Associate Professor, Centre for Sustainable Technologies (CST), IISc Bangalore
He is an Associate Professor at the Centre for Sustainable Technologies (CST), Indian Institute of Science (IISc), Bengaluru, with expertise in plasma science and engineering for sustainable environmental applications. Trained as a chemical engineer, he earned his Ph.D. from McGill University, Canada, and has over nine years of prior industrial experience in plasma technology development and commercialization. His research focuses on thermal and non-thermal plasma systems, plasma-activated water, decentralized water and wastewater treatment, and sustainable waste-to-energy processes, with applications spanning environmental remediation, public health, and resource sustainability. Dr. Rao has made significant contributions through high-impact research publications, patents, and technology demonstrations, particularly in plasma-based disinfection and wastewater recycling solutions suited for rural and resource-constrained settings. In addition to his research, he is actively involved in teaching and mentoring graduate and doctoral students, contributing to capacity building in sustainable technologies at IISc.
Eligibility / Pre-requisites
Bachelor of Engineering or Science. Inclination to learn mathematical aspects of ML and AI; Python programming
Who can benefit?
Corporate employees willing to up-skill or re-skill, Fresh graduates, Government employees working on big data analysis.
Syllabus
Introduction to data driven problem solving; Data types, collection and curation; Introduction and relevance of Data Analysis (DA), exploratory DA, visualization. Foundational statistics; Introduction to machine learning; types and models of learning. Neural networks and deep learning; Modern AI systems; Real-world case studies.
Important Dates and Details
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₹ 18,054
Program Facts
Reference Books
- Rabczuk, T., & Bathe, K.-J. (2023). Machine Learning in Modeling and Simulation: Methods and Applications. Springer Cham.
- Brunton, S. L., & Kutz, J. N. (2022). Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control (2nd ed.). Cambridge University Press.
- Zhang, A., Lipton, Z. C., Li, M., & Smola, A. J. (2023). Dive into Deep Learning. Cambridge University Press.
- Douglas C. Montgomery, Design and Analysis of Experiments (2012), John Wiley and Sons, Inc
