About ACM India Summer/Winter Schools

ACM India Summer/Winter School Objectives:

  • Inculcating problem solving as a skill, which is not emphasised much in the undergraduate curriculum
  • Providing exposure to leading experts, advanced topics and taste of research to motivated students
  • Exposing students to research opportunities in the career, whether in academia or industry

Salient Features of the Schools:

  • Organized at multiple geographical regions in the country
  • Conducted by faculty comprising leading experts from academia and industry on advanced topics in computing
  • Target audience:
    • senior undergraduate students or those enrolled in Masters or higher degree programs
    • around 40 students per school: from nationwide applicants, selected based on academic performance, Statement of Purpose etc. criteria
  • 1 to 2 weeks full-time course in June-July or December-January
  • Hosted at an academic institution

Testimonials from earlier Summer Schools:

"The three-week ACM Summer School on Graph Theory and Graph Algorithms explored various topics, providing me a holistic view of the subject and its applicability. Starting from basic concepts like Depth First Search, the school went on to cover deep concepts such as Parameterized Complexity. The classes were scheduled in such a way that enough time was provided for us to understand the concepts and solve the tutorial problems posed to us at the end of each day. Personally, the school proved to be highly beneficial for me since it introduced me to an algorithmic technique that I could exploit to derive a significant result in my research work.

"Looking from the non-academic point of view, the school was well organized in all aspects. The hospitality extended by the organizers was warm and welcoming. The campus infrastructure provided us with various amenities such as gym, library, etc. that we could explore during our free time. There were also some fun activities such as bird watching which boosted networking amongst the diverse participants of the school.

"Overall the school has provided me an experience with numerous takeaways both academically and otherwise."
S. Vaishali, Summer School 2017 on Graph Theory and Graph Algorithms at IIT Gandhinagar

"I liked this summer school very much. It built a good base about graph theory and then slowly moved towards the advanced topics. It helped me in clearing the interview of TIFR and also in GATE exam. Thank you very much for the school."
Raj Rajvir, Summer School 2017 on Graph Theory and Graph Algorithms at IIT Gandhinagar

View Videos of Summer Schools 2019

Videos of five of the courses held during the ACM India 2019 Summer Schools are now available via the National Programme on Technology Enhanced Learning platform. Click on the links below to view them:

ACM India Announces First Winter Schools, 5 December 2019 to 14 January 2020

ACM India is pleased to announce ACM India Winter Schools 2019-2020, targeted at students in final year Bachelor's program or above. These schools will cover High Performance Computing, Cybersecurity, Geometric Algorithms, and Hybrid Cloud.

ACM India Summer Schools 2019, 3 June to 18 July

ACM India is pleased to announce ACM India Summer Schools 2019, targeted at pre-final year undergraduate or masters students. In exceptional cases, PhD students or students in other years may also be considered. Geometric Algorithms, Compiler Design and Construction, Machine Learning, Malware, Graph Theory and Algorithms, Game Theory, and Cybersecurity and Data Analytics will be covered. 

CSpathshala

ACM India started the education initiative CSpathshala in 2016, to teach computing as a science in all schools. The key objectives are to popularise CT and influence education policy to enable its introduction into the curricula. A two-pronged approach has been undertaken, developing a CT curriculum along with teaching aids and working at grassroot levels with schools, training teachers, executing pilot projects and collecting data to demonstrate the feasibility and efficacy of teaching CT.