Post Graduate level Advanced Certification Course in Deep Learning

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Course Features

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Duration

10 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Advanced

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Teaching Type

Instructor Paced

Course Description

The PG Level Advanced Certification Programme in Deep Learning (Foundations and Applications) enables professionals to build expertise in Deep Learning, starting from essential theoretical foundations to learning how to apply them in the real world effectively. The 10-month weekend programme is best suited for aspiring and practising AI and Machine Learning professionals with programming knowledge.

The programme creates a practical understanding of how Machine Learning algorithms can be developed and optimized for hardware. Such systems can be used in edge computing where power and performance are the major constraints. The interactive sessions will cover fundamentals of deep learning and its applications including speech, text, image, and video processing.

It is delivered in a unique 5-step learning process of LIVE online interactive sessions by IISc and TalentSprint faculty, capstone projects which start in the middle of the programme and continue till the end, mentorship, case studies, and campus visits to ensure fast-track learning.

IISc, with its expertise in multi-disciplinary sciences, is best positioned to offer this programme. Delivered in association with TalentSprint, the programme also connects you to its Deep Tech alumni network so that you can reap life-long career benefits.

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Highlights

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Pedagogy

Top 10 Percentile

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Hands on training

Top 20 Percentile

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Course Credibility

Top 20 Percentile

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Parameters

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Course Credibility

Delivered through TalentSprint a renowned institution in the field, this course offers a comprehensive learning experience.

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Pedagogy

This comprehensive course equips you with all major Deep Learning skills applicable to your daily life. Personalized teaching ensures one-on-one doubt resolution with faculty, maximizing skill acquisition. These practical skills empower you to confidently apply your knowledge and thrive in various real-life situations. With a focus on cultivating industry-relevant skills, this course ensures that learners attain a skillset aligned with current industry demands.

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Hands on training

This course stands out as one of the top 20 percentile options in Deep Learning, offering unparalleled hands-on training. Learners gain practical experience and skills through immersive learning, preparing them for real-world challenges. It ensures a well-rounded skill set, catering to a range of learning preferences. With a focus on Hands on training and Capstone Projects / Industry-Simulation as well as essential Case Based Learning, this course is tailored to meet diverse educational needs.

Course Overview

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Live Class

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Alumni Network

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Human Interaction

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Personlized Teaching

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Case Based Learning

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Post Course Interactions

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Case Studies,Hands-On Training,Instructor-Moderated Discussions

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Case Studies, Captstone Projects

Skills You Will Gain

Prerequisites/Requirements

Education: Graduation (four years or equivalent)

Experience: Working professionals with active hands-on coding experience aspiring to build expertise in Deep Learning

Coding Experience: Programming experience is mandatory to join this programme

What You Will Learn

Machine Learning

Deep Learning

Computer vision

Target Students

Aspiring and practising AI and Machine Learning professionals.

Course Instructors

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Prof. Chiranjib Bhattacharyya

Ph.D., Computer Science and Automation, IISc, India, Programme Coordinator

Professor and Chairperson of the Dept. of Computer Science and Automation, IISc. He is a fellow of the Indian Academy of Engineering. His research areas include Unsupervised Learning, Optimization, Autonomous Systems.
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Prof. Ambedkar Dukkipati

Statistics, Machine Learning, Ph.D., IISc, India

Associate Professor at the Dept. of Computer Science and Automation, IISc. His research interests include Statistical Network Analysis, Network Representation Learning, Spectral Graph Methods, Machin...
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Prof. Chandramani Singh

Ph.D., Electrical Communication Engineering, IISc, India

Assistant Professor in the Dept. of Electronic Systems Engineering, IISc. Previously a Postdoctoral Research Associate at University of Illinois at Urbana-Champaign. Recipient of Microsoft Research I...
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Prof. Chetan Singh Thakur

Ph.D., Neuromorphic Engineering, MARCS Research Institute, Western Sydney University, Australia

Assistant Professor at the Dept. of Electronic Systems Engineering, IISc. Before joining IISc, he worked as a Research Fellow at Johns Hopkins University. In addition, he worked with Texas Instrument...
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