IISc Certification | Interactive Live Online Programme | Classes start in May 2021 | Early Bird 2 Scholarship Closing on Mar 10
Early Bird 2 Scholarship Closing on Mar 10
Information is the oil of the 21st century, and analytics is the combustion engine
Top Data Science Career Opportunities
The Advanced Certification Programme in Computational Data Science enables working professionals to gain practical hands-on experience in solving real-life challenges. The programme will teach participants how to build powerful models to generate actionable insights, necessary for making data-driven decisions.
The 10 month programme will be taught by world class faculty from a global institution and supplemented with industry learnings. It offers a unique 5-step learning process of LIVE online faculty-led interactive sessions, capstone projects, mentorship, case studies and data stories to ensure fast-track learning.
Indian Institute of Science (IISc), with its expertise in multi-disciplinary science, is best positioned to offer the programme on Computational Data Science. Delivered in association with TalentSprint, this executive friendly programme is best suited for professionals who are willing to gain an in-depth understanding of the mechanics of working with data and identifying insights.
IISc (Indian Institute of Science) tops among the oldest and the finest higher education institutes of India. It pursues excellence in research and education in several fields of Science and Engineering and is one of the first three publicly funded institutes to be awarded the Institute of Eminence status. The alumni of IISc hold significant academic and industry positions around the globe. For more information visit https://www.iisc.ac.in.
The Advanced Programme in Computational Data Science will be delivered by IISc’s Centre for Continuing Education (CCE). CCE delivers courses suitably designed to meet the requirements of various target groups, eg: research & development (R&D) laboratories and industries, research scientists and engineers, to enable them to grow into competent managers of technology-intensive and data-driven organizations. For more information visit http://cce.iisc.ac.in.
IISc faculty members are an impressive group bearing academic accreditation from premier institutions around the world
Ph.D. Computational Mathematics, OvGU Germany
Chairman, Department of Computational and Data Sciences, previously Postdoc at Imperial College London and WIAS Berlin. Research areas include Finite Element Analysis, Parallel Algorithms, Data-Driven Modeling, ML/NN for CFD.
Ph.D. Aerospace Engineering, Texas A&M University, USA
Assistant Professor in the Department of Computational and Data Sciences, IISc, and previously a postdoctoral researcher at Sandia National Laboratories, USA. His research focuses on ML/AI for fluid mechanics, anomaly/extreme event detection, high performance scientific computing and combustion applications.
Ph.D. Computer Science, Indiana University, USA
Associate Professor in the Department of Computational and Data Sciences, IISc, and previously a Research Faculty at the University of Southern California (USC), Los Angeles, and a Postdoc at Microsoft Research, San Francisco. His research explores abstractions, algorithms and applications on distributed systems. These span Cloud and Edge Computing, Big Data Platforms and Internet of Things (IoT).
PhD Applied Mathematics, TU Delft, Netherlands
BTech and MTech IIT Madras
Assistant Professor at the Department of Management Studies, IISc. Before joining IISc he worked as a Quantitative analyst at ING, Amsterdam. His research interests include quantitative finance, investment decisions related to energy and environmental sectors and Real options.
Ph.D. Mechanical Engineering and Computation, MIT USA,
B.Tech and M.Tech, IIT Madras
Assistant Professor in the Dept. of Computational and Data Sciences, IISc. His research focuses on ML/AI for Environmental Forecasting, Data-Driven Routing of Autonomous Vehicles, Bayesian Learning and Data Assimilation, Uncertainty Quantification, and Computational Optimization.
Ph.D. Mechanical Engineering , University of Michigan, Ann Arbor, USA
B.Tech, NITK Surathkal, M.Tech, IISc Bangalore
Assistant Professor in Department of Computational and Data Sciences, IISc, and previously Research Faculty at the University of Michigan. Research interests include algorithms for quantum-mechanical material modelling at extreme-scale, ML/AI frameworks for accelerating materials-physics simulations, Multi-scale modeling. Lead developer of 2019 Gordon-Bell prize finalist code DFT-FE.
Ph.D. TU Delft, Netherlands
Assistant Professor at the Department of Electrical Communication Engineering, IISc. His research areas include ML, AI, and statistical inference for Data and Network Sciences.
Analyse how industry uses computational data science through real-world use cases
Showcase your data science journey in the programme through various experiments, projects and hackathons in a compelling manner.
Classes start in May 2021
1 Campus Visit of 3 Days
Dates will be decided keeping the safety of participants in mind. Fees will be based on actuals.
Education: Bachelors (four years or equivalent) or Masters in Science/Engineering/Management
Work Experience: Minimum 1 Year
Coding Experience: Programming Knowledge Required
Note: Exceptional engineering students and engineering graduates may apply for special selection on a case to case basis.
The selection for the programme will be done by IISc and is strictly based on the education, work experience, and motivation of the participants.
"I have architected solutions across enterprise applications and transformed process and data models to bring valuable business outcomes. This programme will help me level up my existing capabilities and streamline the firm's operations in a much better way."
"I am looking forward to applying Data Science expertise in developing marketing models that analyze big datasets to measure consumer's product preferences and use it to determine future sales."
"I believe this programme is a perfect headstart towards my goal of becoming a Data Scientist."
"I wish to apply my Data Science expertise in Supply Chain operations and later in other fields."
"The programme covers a section, 'Data Stories' which aligns with my learning needs. Further, this programme allows me to learn and grow as a 'Data & Analytics Manager'."
"This programme will enable me to apply Data Science knowledge in areas like Material Screening, Process Improvement and Closed Loop Manufacturing."
"The use of Data Science in banking is increasing day by day. I wish to be well-informed and be at the forefront of its implementation in my organization."
"I want to leverage my AI/ML knowledge and use it to innovate in the areas of imaging and video platform. It is going to pave a new direction for my career."
"The programme will train me in different methods of statistical analysis, and programming knowledge needed to continue with my goal to provide research for companies."
Note: These are edited versions based on the details submitted by various programme applicants.
|Details||Domestic Participants||International Participants|
Early Bird Fee
|18-month interest-free EMI
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 state-of-the-art digital delivery platform delivers unique online and onsite experiences that help build cutting-edge expertise, for today and tomorrow. Funded by Nexus Venture Partners and 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 www.talentsprint.com.
Computational Data Science helps you analyse data effectively and enable data-driven decisions. It harnesses your mathematical, analytical and technical skills to interpret and understand big complex data sets and their relevance to real-life decisions. Armed with this knowledge you become an expert at communicating data insights to key stakeholders within and outside your organization. The learnings help you deliver practical and actionable insights for leveraging customer behaviour, business intelligence, operations and much more.
IISc (Indian Institute of Science) is India's foremost academic institution that offers world-class education in science, engineering, design, and management. The programme will be delivered by IISc’s Centre for Continuing Education (CCE). CCE delivers courses suitably designed to meet the requirements of various target groups, eg: research & development (R&D) laboratories and industries, research scientists and engineers, to enable them to grow into competent managers of technology-intensive and data-driven organizations.
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 state-of-the-art digital delivery platform delivers unique online and onsite experiences that help build cutting-edge expertise, for today and tomorrow.
Given its in-depth understanding of the deep technologies, access to industry experts, and a state of art technology platform, IISc has chosen TalentSprint as its partner for executive education programmes in disruptive and emerging technologies.
The 10-month programme will be taught by world-class faculty from a global institution and supplemented with industry learnings.
Meet the faculty here.
Yes, this is a hands-on programme. The sessions are accompanied by practical industry-oriented exercises to help assimilate theory into practice. Online lab assignments will help you master the concepts with the help of mentors. Physical labs sessions will be opened once it is safe for participants and faculty.