Frequently Asked Questions

Digital health uses information and communication technologies to generate knowledge and transform health-related data to information that can be collected, shared and used to improve health and healthcare outcomes. The broad scope of digital health includes categories such as mobile health (mHealth), health information technology (IT), wearable devices, telehealth and telemedicine, and personalized medicine. The digital tools provide a more holistic view of patient health through access to data and give patients more control over their health.

The Digital Health market in India is estimated to reach INR 485.43 Bn by 2024, expanding at a compound annual growth rate of ~27% during the 2019-2024 period. ~Research and Markets

Accordingly, adoption of digital tools has grown significantly among all physicians regardless of gender, speciality or age. Adoption of remote care tools such as tele-visits and remote monitoring have become significant. Awareness of most of the emerging technologies such as artificial or augmented intelligence is fairly high.

India is at the cusp of a ‘digital health’ revolution and is poised to create new milestones. By 2022, the healthcare market will potentially have a worth of $370 Bn, promising returns up to 35-40%, according to several investors. Currently, there are nearly 4,892 start-ups in the Indian health-tech space. These digital health start-ups are bringing novel technologies such as wearable tech, telemedicine, genomics and artificial intelligence to the Indian healthcare system. These provide a vast backdrop for solutions as they go well beyond a specific disease, therapeutic area, geography, type of product and service or business model. All this indicates that digital health is here to stay.

COVID-19 could spur a paradigm shift in how patients receive treatment, moving from traditional in-office treatment to eVisits, telehealth and remote monitoring. Acceleration in adoption of digital tools can provide more effective and safer ways of addressing health and wellness.

Digitization is impacting the medical industry like never before. AI and Machine Learning are taking this field to a new level.

Medical professionals and caregivers are being encouraged to utilize datasets to extract clinically relevant information for patient diagnosis, drug development, precision treatment and more. Accordingly Data Science has created profound uses in Healthcare, which early adopters can capitalize in the future.

Digital Health Professionals working on eHealth, mHealth, Telehealth, Medical Imaging, Medical Devices, Signal Processing, Health Monitoring, Data Communication, BioTech, MedTech and more using cutting-edge technology like AI, Machine Learning, Analytics, and IoT.

For medical professionals, the programme enables

  • Enhance your commitment to patient care with precision medicine, personalized treatment and informed care to significantly reduce the death rate and predictable medical outcomes.
  • To collect, structure and process a high volume of data and gain better insights from it.
  • Improve diagnostic accuracy and efficiency.

Biotech professionals

  • Reduce human suffering and disease by sifting through large, complex data sets and understanding the interconnectivity of genetic codes and diseases.
  • Can help generate a unique health and wellness profile based on both genomic and lifestyle data. For instance, if this is tied to a health and wellness app - the user can be alerted on foods or activities that increase their risk of a particular disease, thereby taking precautions at an early stage of detection.
  • Can help create new combinations of pharmaceutical compounds, perform predictive diagnosis, or even create genetically modified seeds.

Pharma professionals

  • Cure diseases by accelerating drug discovery and development process.
  • Optimize and improve the efficacy of clinical trials.
  • Helps spot trends and patterns in data (diseases, how patients respond to treatment of the same) and allows in formulating more targeted medications for patients that share common features

Other benefits

  • Build Electronic Health Records (EHRs) where patients have their own digital records that include demographics, medical history, allergies, laboratory test results etc.
  • Enhance patient engagement: Build smart devices that record every step patient takes, their heart rates, sleeping habits, etc., on a permanent basis. All this vital information can be coupled with other trackable data to identify potential health risks lurking.

Digital Health and Imaging solutions are the biggest beneficiaries of Data Science, AI and Machine Learning. From saving lives to cutting down costs, data science has a huge role to play in the healthcare system. Take a look at some of the important use cases in healthcare.

  • Improve Diagnostic Accuracy:

    According to the recent research by the National Academies of Sciences, Engineering, and Medicine, about 5 percent of adult patients are misdiagnosed each year in the US continent that causes approximately 10 percent of patient deaths. Targeting this problem, a deep learning startup, Enlitic, built a deep learning algorithm that reads imaging data (such as x-rays, CT scans, etc.), and analyzes it, checks the given results against an extensive database of clinical reports and laboratory studies. This way the company could deliver up to 70 percent more accurate results, 50,000 times faster
  • Advanced pharmaceutical research to find cure for cancer:

    Being one of the most common and most deadly diseases, cancer has been a regular subject of scientific research. A Boston healthcare startup, BERG Health, reshapes the cancer medication market through extensive use of data science. Using powerful machine learning algorithms the company extracts and analyzes biological samples from over 1,000 patients in one go. The company has developed BPM 31510, the drug, that detects and triggers the natural death of cells damaged by the disease. Thus, the cancer cells can be removed from the human body naturally, without extensive medication and further damage to the patient’s health. While the drug is still being carefully tested, it gives us a clear understanding of the transformation potential that Data Science and deep technologies can provide to the pharmaceutical industry.
  • Taking the risk out of prescription medicine:

    MedAware, aims to eliminate prescription errors. The company claims that it has tools to help hospitals save up to $5.6 million, not to mention the reduced risk of lethal outcomes. A self-learning software system, provided by MedAware, checks all prescriptions against similar cases in the database and informs the doctor when the prescription contains any deviations from the typical treatment plan.
  • Disease Prevention:

    Omada Health is a digital therapeutics company that uses smart devices to create personalized behavior plans and online coaching to help prevent chronic health conditions, such as diabetes, hypertension, and high cholesterol.

And there are many such organizations who have opened up new opportunities using Data Science and Deep Learning for better healthcare.

  1. Learn from Leading IISc Faculty
  2. Reinforce Learning by Applying Concepts
  3. Network with Current and Future Digital Health Industry Practitioners
  4. Executive Programme Certificate by IISc
  • Prof. Phaneendra Yalavarthy
    Programme Coordinator
    Ph.D. Engineering Sciences, Dartmouth College, USA

    An Associate Professor at the Department of Computational and Data Sciences, IISc. and a Faculty Associate for Interdisciplinary Mathematical Sciences and Convenor for Medical Imaging Group, CDS at IISc. Subject expert in Computational methods in Medical Imaging, Medical Image Processing, and Physiological Signal Processing.

  • Prof. Jaya Prakash
    Programme Faculty
    Ph.D. Medical Imaging, Indian Institute of Science, India

    Assistant Professor at the Department of Instrumentation and Applied Physics, IISc. His prior experience is with companies like Shell Technology Center, and iThera Medical-Munich. His key research areas include: Optical/Optoacoustic Imaging and Multi-Modal Imaging Systems.

  • Prof. Ambedkar Dukkipati
    Programme Faculty
    Ph.D. Indian Institute of Science, India

    Associate Professor at Department of Computer Science and Automation, an IIT Madras and IISc alumni. His research publications include ‘Winning an Election: On Emergent Strategic Communication in Multi-Agent Networks’ (AAMAS: 2020), ‘Networked Multi-Agent Reinforcement Learning with Emergent Communication’ (AAMAS: 2020).

  • Prof. Venkatesh Babu R
    Programme Faculty
    Ph.D. Electrical Engineering, Indian Institute of Science, India

    An Associate Professor in Computational and Data Sciences, IISc. He has held postdoctoral positions at Universities across Europe and worked in industry before taking active interest in academics. His research interests include: Signal Processing, Compression, Machine Vision, Image/Video Processing, Pattern Recognition and Multimedia.

  • Prof. Sriram Ganapathy
    Programme Faculty
    Ph.D. Speech Signal Processing, Johns Hopkins University, USA

    Assistant Professor at the Department of Electrical Engineering, IISc. His research areas include: Signal Processing, Machine Learning, Deep Learning and Neuroscience with applications to Robust Speech Recognition, Speech Enhancement, Speech Coding and Audio Analytics including Biometrics.

  • Prof. Yogesh Simmhan
    Programme Faculty
    Ph.D. Computer Science, Indiana University, USA

    Assistant Professor at the Department of Computational and Data Sciences, IISc. His research interests include: Temporal Graphs: Abstractions, Platforms and Algorithms, Edge Computing and Storage & Scalable Data Management and Analytics for Science and Engineering.


Given the current crisis due to Covid-19, we understand that participants may have a challenge with cash flows. In order to enhance the programme fee payment flexibility, we have increased the tenure of our interest-free (0% EMI) loan from the current 9 months to 18 months. As a result of this, you will now be able to pay the programme Fee in up to 18 interest-free instalments. You may contact your Relationship Manager for more details.

You will need the following infrastructure to access our platform:
Device: A Desktop/Laptop/Tablet/Smartphone with camera and mic.
Internet: A regular broadband/wifi connection or a mobile 4G connection
Note: Proctored online assessments can be taken only on a Desktop/Laptop with a web camera and mic (not allowed on tablets/smartphones).

Groups can conveniently connect among themselves at an appointed time for group work, outside the online classes. This feature comes in handy during group activities and projects.
Students can also use the platform 24 x 7 to engage and learn from their peers using our interactive discussion forums available under each course of the programme.
Our platform also has the provision of group-specific discussion forums for offline discussion among the group members.

Our recorded videos have Digital Health and Imaging Table of Content (TOC) to help easy and smart navigation within the videos. Students can click on the items under TOC to directly jump to the relevant section in a video. Video archives also have a Phrase Cloud of keywords/phrases used in the video. Students can click on a particular keyword/phrase to find yellow markers, indicating the points where the selected keyword/phrase was covered on the video timeline.

Selection Process

IISc Bangalore conducts the selection process for the programme. Candidates will be selected based on the details of education, work experience and motivation submitted by you along with your application.

Candidates must have completed their graduation or post-graduation with at least 50% marks and relevant experience of at least 1 years

Programme Fee

Participants who are not holding an Indian Passport or are not residing in India will be considered as an International Participant.

Yes, the programme fee can be paid in 18-month interest-free instalments.

Details Domestic Participants International Participants
Programme Fee ₹2,40,000 $4,000
18-month interest-free EMI ₹11,800/Month

No, the application fee is non-refundable.

No, the application fee is non-refundable.

Building deep-tech expertise is an absolute necessity for professionals in this fast-changing world that is constantly disrupted by technology.

Professionals have multiple options for funding.

  1. Sponsored by employer
  2. Self-funded

Based on our experience in enabling 3000 professionals who have participated in our executive programs, self-funding seemed to be the most preferred option with over 80% choosing this.

Three key reasons why professionals opt for it:

  1. Freedom: To opt for a program of their choice, at a time of their choice, with an institution of their choice and not be restrained by organisation’s policy.
  2. Flexibility: To pursue greater career opportunities well even beyond their current employer or to nurture their entrepreneurial ambitions.
  3. Funding: Access to flexible EMI schemes (Paying as low as Rs. 5,550 per lac per month).

We have also observed that the commitment levels were higher among self-funding participants.


  • Module-1: Digital Health: Introduction
    Pre-requisites: Understanding of Digital Technology

    • Need, case studies, basics - mHealth and eHealth, Impact
    • Informatics: Health Level Seven (HL7), Integrating the Healthcare Enterprise (IHE), Vendor Neutral Archives (VNAs)
    • Open source/data/innovation - opportunities
    • IT infrastructure (IoT/Cloud computing)
  • Module-2: Wearable Devices and Physiological Signal Processing
    Pre-requisites: Basics of Signals & Systems, Basics of Fourier Transforms and Z-Transforms, Basics of Physiology.

    • Signal Processing: Sampling, Basic Filters, Decimation, Interpolation, STFT, Wavelets
    • Physiology: ECG Signal Acquisition (Electrical activity of heart, chest leads/montage, action potential in pacemaker and other regions; action potential relation to ECG Waveform; Reading ECG); EEG Signal Acquisition (Neural activity in the brain, Action potential, post-synaptic potential, Signal Propagation in the brain, EEG montage, EEG Signal Acquisition); EEG and ECG data processing
    • Wearable Sensors for health monitoring: Accelerometers (data acquisition and interpretation), glucose sensing (acquisition methods and comparison), Wearable ECG & EEG based on dry electrodes
    • Speech and audio signal processing: From signal capture to data pre-processing and feature modelling.
  • Module-3: Machine Learning Basics for Real-world
    Pre-requisites: Basic of Probability and Linear Algebra: Bayes Theorem, Random Variables, Expectation, Variance, Matrices, Inverse, Eigenvalues and Eigenvectors

    • Basic Mathematics for ML, What is Data and Model? Machine Learning Workflow and Applications
    • Introduction to real-world signals - text, speech, image, video; Feature extraction and front-end signal processing - information-rich representations, robustness to noise and artifacts
    • Learning as optimization, Linear Regression, Regularization and Logistic Regression
    • Basics of pattern recognition, Generative modelling - Gaussian and mixture Gaussian models
    • Machine Learning for physiological signal processing. Time series modelling
  • Module-4: Deep Learning in Digital Health
    Pre-requisites: Basic Machine Learning that is part of Module 3

    • Deep Learning: Basics, MLPs, Back propagation, CNNs
    • Deep Learning for physiological signal processing. Recurrent neural models
    • Discussion on Depth Versus Width. Practical considerations in Deep Learning. Avoiding Overfitting- Regularization, Dropout. Convolutional Neural Networks. Recurrent Neural Networks. Forward and Backward propagation. Various Architectures for sequence to sequence and sequence to vector mapping.
    • Applications of Deep, Convolutional and Recurrent models in healthcare. (Instructor: SG)
    • Nature Language Processing: LSTMs, Language Models, Knowledge Graphs, Q&A (Demo)
  • Module-5: Deep Learning in Imaging/Vision
    Pre-requisites: Modules-1,2,3, and 4

    • Medical Imaging Modalities: Introduction, Protocols, Work Flows, Applications
    • Medical Image Analysis: Basics, Imaging Physics-Based Methods, and Need for Deep Learning & Neuroimaging: Introduction, Challenges
    • Vision - Deep learning: Loss function, Optimization, CNNs, Training Convolutional Neural Networks, Object Detection, Segmentation
    • Deep Learning models: AlexNet, VGG, GoogleNet, ResNet, RNN/LSTM

Schedule and Details

The online sessions will be held during the weekends, preferably Saturdays.

No placement assistance is provided to the participants. This programme caters to working professionals who aspire to hone their skills to better adapt and grow in the constantly evolving Digital Health and Imaging sector.

The programme will be delivered through faculty-led interctive live sessions on TalentSprint’s direct to device platform.

All reading material (pre/post session) will be shared regularly through the Online Learning Management System.

To be announced soon.

The total duration of the programme is 6 months, excluding Key Takeaways.

A certificate of successful completion is provided upon completion of all requirements of the programme. All examinations and evaluations related to the certification are carried out by IISc Bangalore.

The batch will consist of 50 participants.

All sessions are conducted by IISc Bangalore faculty. Industry experts may be invited for sharing their valuable experience.

Career Accelerator

Program participants of all the DeepTech programs by TalentSprint are eligible to join the Career Accelerator.

Our Career Support platform will provide you the resources to help you showcase your professional profile with certification and capstone project experience on TalentSprint Alumni Network, LinkedIn, GitHub, Kaggle, among other platforms.

After the successful completion of your cohort of the program, you will get priority access to career opportunities in the industry through an exclusive Alumni portal. This will include internal job postings, job opportunities notifications shared by your peers, and personalized mentorship based on industry and experience.

Guidance on building a compelling professional profile with a DeepTech edge on various platforms., interview preparation and more.

Program participants can apply for startup mentorship. If selected, they get mentorship from experts and like-minded professionals.

You will find openings from leading global companies and exciting startups and others within the Career Accelerator.

No, TalentSprint will not be conducting placement drives. However you will get access to job opportunities and right guidance to help you in getting selected.

Career opportunities are updated as and when a program alumni posts it or when there is a suitable opportunity through our wide industry, alumni and peer network.

You get inputs from the alumni and peer network.

Yes, they can always update their profile at TalentSprint's alumni page. In case they come across any issues doing that, then our Career Accelerator Executive will be happy to help.

With TalentSprint's exclusive DeepTech community, you get a chance to network with industry peers and peers from different programs of TalentSprint. You get to find complementing synergies of common interests and learn about market developments and opportunities. Plus, you can get exclusive invitations for the DeepTalk Interactive Series, where leaders discuss all things DeepTech.

No, this is an exclusive initiative of TalentSprint and not connected with our partner institutions.

About the Platform

Do not worry. In case you miss a session, you will be given access to view the recorded version of the session within a specified timeframe.

No, there isn’t any minimum attendance criteria for the programme. However, it is recommended to not miss any of the sessions. To complete the programme you need to successfully complete and submit all program submissions that may be due at your end.

An internet-connected device, Computer/Laptop/Tablet/Smartphone, is enough to access the platform.

Web-camera and Mic with necessary power backup will be needed for proctored online assessments.

All participants are required to execute, before the start of the program, an agreement that consists of the standard Program Terms and Conditions. It has the following components:

  • Part A: Etiquette and Platform Rights
    • Classroom Etiquette & General Policy Guidelines
    • Tools and Platforms in Use
    • Tools and Platforms: Terms of Use
  • Part B: Honor Code
  • Part C: Certification
  • Part D: Program Fee, Refund and Termination Policy


IISc (Indian Institute of Science) is India's foremost academic institution for the pursuit of excellence in higher education & research. It offers world-class education in science, engineering, design, and management. IISc became a deemed university in 1958. It is one of the first six institutes to be awarded the Institute of Eminence status. The alumni of this Institute hold significant academic and industry positions around the globe. For more information visit

TalentSprint brings high-end and deep-tech education to aspiring and experienced professionals. It partners with world-class academic institutions and global corporations to develop and offer disruptive programmes. TalentSprint's hybrid platform delivers unique online and onsite experiences that help build cutting-edge expertise, for today and tomorrow. Funded by Nexus Venture Partners and the NSDC, it is the recipient of several national and international awards including Dream Company To Work For 2017, Best Innovative Technology Organisation In Education Sector Award 2016, World HRD Congress HR Tech Leader Award 2014, CIO Review Company of the Year Award 2014, Silicon India Industry Performer of the Year Award 2014 and others. For more information please visit