Centre for Quantitative Learning and Applications - SSE

Centre for Quantitative Learning and Applications

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Centre for Quantitative Learning and Applications

About

The Center for Quantitative Learning and Application at Symbiosis School of Economics is dedicated to advancing the frontiers of quantitative knowledge in economics. Established on the pillars of academic excellence, research impact, and practical application, the center aims to shape the next generation of economists and analysts.

VISION:

To be a pioneering hub for quantitative excellence, driving innovation, and fostering a deep understanding of economic phenomena through cutting-edge research and application.

  1. Centralized Access to Quantitative Learning Resources: Facilitate seamless access to a comprehensive repository of materials on quantitative learning, consolidating valuable resources at a centralized hub for the benefit of students.
  2. Interactive Learning Through Periodic Code Blogs: Enhance student engagement by regularly publishing blogs containing codes for data extraction and analysis, catering specifically to their dissertation requirements and promoting interactive learning experiences.
  3. Timely Updates on Data Releases with Insightful Commentary: Keep CQLA users informed about the latest data releases by providing timely updates accompanied by concise commentaries, ensuring a well-rounded understanding of the findings.
  4. Supportive Guidance for Students Facing Quant Challenges: Extend a supportive hand to students grappling with challenges related to modeling, data, or other quantitative aspects in their dissertations, offering assistance and guidance to foster their academic success.

MISSION:

  • Advanced Quantitative Education: Provide rigorous and contemporary education in quantitative methods, econometrics, and data science to empower students with the skills necessary for analytical decision-making.
  • Interdisciplinary Collaboration: Foster a collaborative environment that encourages interdisciplinary research, bringing together experts from economics, mathematics, computer science, and other relevant fields to address complex societal challenges.
  • Applied Research Impact: Conduct impactful research at the intersection of quantitative methods and economics, translating theoretical insights into practical solutions with real-world applications.
  • Industry Engagement: Establish strong ties with industry partners to facilitate internships, projects, and collaborations, ensuring that our students gain practical experience and exposure to current industry practices.
  • Global Outreach: Engage in international partnerships and collaborations to stay at the forefront of global developments in quantitative economics, promoting cross-cultural exchange and learning.
  • Ethical Data Use: Instill a commitment to ethical practices in data collection, analysis, and application, emphasizing the responsible use of quantitative methods for the betterment of society.

Key Features:

  • Comprehensive Curriculum: Our programs offer a comprehensive curriculum that blends theoretical knowledge with hands-on experience in quantitative methods, econometrics, and data science.
  • Cutting-edge Research: The center is committed to conducting high-impact research that addresses contemporary economic challenges, with a focus on practical solutions and applications.
  • Industry Integration: Through strategic partnerships with industry leaders, students have the opportunity to apply their quantitative skills in real-world scenarios, preparing them for successful careers in various sectors.
  • Global Perspective: We embrace a global perspective, encouraging international collaborations, research exchange programs, and a diverse student body to enrich the learning experience.
  • Ethical Practices: Upholding the highest standards of ethics in quantitative research and data application, we instill in our students a strong sense of responsibility in using their skills for the greater good.

Team

Director’s Message

Welcome to the Centre for Quantitative Learning and Application (CQLA) at Symbiosis School of Economics!

Explore the Centre for Quantitative Learning and Application – your gateway to a wealth of data that will create new knowledge! We are committed to advancing learning through data dissemination and open codes, promoting transparency and empowering our community with accessible resources. Join us in unlocking the potential of quantitative learning for a future of informed decision-making and collaborative innovation.

I am delighted to extend a warm welcome to the Centre for Quantitative Learning and Application at Symbiosis School of Economics, Pune. It brings me great pleasure to introduce this innovative initiative, aimed at fostering a culture of data collation and sharing, quantitative excellence and application within our academic community.

In an era characterized by the rapid evolution of technology and data, the ability to navigate, analyse, and draw insights from quantitative information is more crucial than ever. CQLA is dedicated to equipping our students with the skills and knowledge necessary to thrive in this data-driven world.

Our centre is committed to providing a dynamic and supportive environment where students can engage with quantitative concepts, methodologies, and applications across various disciplines. Through a combination of rigorous coursework, hands-on projects, and collaborative research opportunities, we aim to empower our students to become adept problem solvers and critical thinkers.

At the Centre for Quantitative Learning and Application, we recognize the importance of bridging the gap between theory and practice. We are actively cultivating partnerships with industry leaders, research institutions, and experts in the field to ensure that our students gain real-world exposure and practical insights that will set them apart in their future endeavours.

I encourage all students, faculty, and staff to embrace the opportunities offered by the Centre for Quantitative Learning and Application. Whether you are a seasoned expert seeking to enhance your quantitative skills or a newcomer eager to explore the world of data-driven decision-making, our centre provides a platform for continuous learning and growth.

As we embark on this exciting journey together, I am confident that the Centre will play a pivotal role in shaping the future of our students and contributing to the advancement of knowledge in the field of quantitative sciences.

I look forward to witnessing the accomplishments and successes that will undoubtedly emerge as an outcome of our association with varied stakeholders, helping us enhance our research and offer consultancy services

Warm regards,

Dr. Jyoti Chandiramani

Director,

Symbiosis School of Economics &

Dean Faculty of Humanities and Social Sciences

Team members

Dr Nawazuddin Ahmed,
Head (CQLA)
Assistant Professor (Economics), SSE, SIU


Dr Sudipa Majumdar,
Member (CQLA)
Senior Fellow


Dr Ranjan Kumar Dash,
Member (CQLA)
Associate Professor (Economics), SSE, SIU


Mr. Shailesh Bharati,
Member (CQLA)
Adjunct Faculty (Economics), SSE, SIU



Repository

Important Data Sources

  1. Epidemic-Macro Model Data Base https://www.epi-mmb.com/
  2. World Bank: Poverty and Inequality Platform https://pip.worldbank.org/home
  3. Large-scale, cross-national, probability-based web panel: Published by the European Social Survey (ESS) bit.ly/3PLSidn
  4. World Bank: World Development Indicators https://databank.worldbank.org/source/world-development-indicators
  5. Open Government Data (OGD) Platform India https://data.gov.in/
  6. Ministry of Statistics and Programme Implementation: National Accounts Data https://www.mospi.gov.in/data
  7. Ministry of Statistics and Programme Implementation: Microlevel Data (NSO, ASI, PLFS, Economic Census, Employment and Unemployment, etc) http://microdata.gov.in/nada43/index.php/catalog/central/about

E-Books

  1. London School of Economics https://press.lse.ac.uk/site/books/
  2. Openstax: The future of education https://openstax.org/subjects/social-sciences
  3. National Digital Library of India https://ndl.iitkgp.ac.in/
  4. Directory of Open Access Books https://doabooks.org/
  5. OAPEN: Online library and publication platform https://www.oapen.org/home
  6. Project Gutenberg https://www.gutenberg.org/
  7. World Bank Book Repository https://openknowledge.worldbank.org/
  8. Internet Archive: Digital Library https://archive.org/

Important Discussion and Working Paper Series

  1. The Centre for Economic Policy Research (CEPR) https://cepr.org/publications/discussion-papers
  2. The IZA – Institute of Labor Economics https://www.iza.org/publications/dp
  3. NBER https://www.nber.org/papers?page=1&perPage=50&sortBy=public_date
  4. NATIONAL COUNCIL OF APPLIED ECONOMIC RESEARCH https://www.ncaer.org/publication-category/working-papers 
  5. Asian Development Bank https://www.adb.org/publications/series/economics-working-papers
  6. Repec Working Paper Repository https://econpapers.repec.org/paper/
  7. OECD https://www.oecd.org/economy/economicsdepartmentworkingpapers.htm

Latest AI Tools

  1. The Ultimate Chatgpt Browser Extension: http://Alicent.ai
  2. Create Designs: http://Stockimg.ai
  3. Code Writer – BlackBox: https://www.useblackbox.io/
  4. Video Creator – HeyGen: https://www.heygen.com/
  5. Presentations - Decktopus AI: https://www.decktopus.com/
  6. Search Engine - Franks AI: https://franks.ai/
  7. AI Business Strategist – Vizologi: https://vizologi.com/
  8. Emails: https://inboxpro.io
  9. Online Meetings: https://tldv.io
  10. Chat with PDF: http://chatpdf.com
  11. Create Designs: https://stockimg.ai
  12. Scan GitHub Repositories:
  13. Discover The Newest AI Tools - AI Valley: http://aivalley.ai
  14. Create AI videos from just text - Elai: http://elai.io
  15. Take Your Meeting Notes - tldv: http://tldv.io

Free Online Courses

  1. Computer Science https://pll.harvard.edu/course/cs50-introduction-computer-science?delta=0%E2%80%A6
  2. Programming with Scratch https://pll.harvard.edu/course/cs50s-introduction-programming-scratch?delta=0%E2%80%A6
  3. Web Programming with Python and JavaScript https://pll.harvard.edu/course/cs50s-web-programming-python-and-javascript?delta=0…
  4. Artificial Intelligence https://pll.harvard.edu/course/cs50s-introduction-artificial-intelligence-python?delta=0… 
  5. Programming with Python https://www.edx.org/learn/python/harvard-university-cs50-s-introduction-to-programming-with-python
  6. Mobile App Development with React Native https://pll.harvard.edu/course/cs50s-mobile-app-development-react-native?delta=0%E2%80%A6
  7. Introduction to Data Science with Python https://pll.harvard.edu/course/introduction-data-science-python?delta=0%E2%80%A6
  8. Introduction to Game Development https://pll.harvard.edu/course/cs50s-introduction-game-development?delta=0
  9. Mathematics For Computer Science https://ocw.mit.edu/courses/6-042j-mathematics-for-computer-science-spring-2015/
  10. Introduction to Machine Learning https://ocw.mit.edu/courses/6-036-introduction-to-machine-learning-fall-2020/

Updates in Economics (Events, Calls for Papers, Conferences and Opportunities)

  1. Economics Network https://economicsnetwork.ac.uk/
  2. IHDS Monthly Update https://ihds.umd.edu/publications-and-research/monthly-forum-newsletter
  3. NCAER Monthly Review of the Economy https://www.ncaer.org/newsletter-category/monthly-review-of-the-economy
  4. CRISIL Economy First Cut https://www.crisil.com/en/home/our-analysis/views-and-commentaries.html

Urban Corner

  1. MIT: Mapping Cities https://news.mit.edu/2023/mapping-cities-motion-book-0613
  2. Book Announcement
    The Middle Class in Neo-Urban India: Space, Class and Distinction By Smriti Singh https://www.routledge.com/The-Middle-Class-in-Neo-Urban-India-Space-Class-and-Distinction/Singh/p/book/9781032248370
  3. Open City: Urban Data Portal https://opencity.in/

Learn Data: Websites and Blogs

  1. https://alberts-newsletter.beehiiv.com/
  2. Curve fitting in R:https://finnstats.com/index.php/2022/04/02/curve-fitting-in-r/?utm_source=ReviveOldPost&utm_medium=social&utm_campaign=ReviveOldPost
  3. For Learning R:https://rfortherestofus.com/
  4. R News and Tutorials:https://www.r-bloggers.com/

Data and Econometric Notes

  1. TIME SERIES ANALYSIS: Alexander Aue, University of California, Davis https://t.co/BnxeEN4IBd
  2. Stanford University open source econometrics notes https://web.stanford.edu/~doubleh/eco270/
  3. Introduction to cleaning data with R https://pyoflife.com/introduction-to-cleaning-data-with-r-pdf/

Coding and Data: E-Books

  1. The Python Workbook https://pyoflife.com/the-python-workbook-pdf/
  2. Qualitative Data Analysis https://researchdesignreview.com/2020/05/07/qualitative-data-analysis-16-articles-on-process-method/
  3. Data Science for Economics and Finance: Sergio Consoli, Diego Reforgiato Recupero and Michaela Saisana (Editors) https://link.springer.com/content/pdf/10.1007/978-3-030-66891-4.pdf

Softwares

  1. Gretl
  2. R
  3. PSPP

Blogs

Working with World Development Indicators (WDI) from the World Bank Databank

Nawazuddin Ahmed | 25 December 2023 | Stata, WDI

Creating Rotational Panels from Periodic Labour Force Survey (PLFS) Rounds

Nawazuddin Ahmed | 25 December 2023 | Employment, PLFS, Rotational Panel, Stata Codes



Events

• In collaboration with The Indian Econometric Society (TIES), a workshop on Time Series Econometrics took place from March 20 to 23, 2023. Professor Ramachandran, an esteemed Economics professor from Pondicherry University, played a crucial role as a resource person during this event.

• On Jan 08, 2024 Mr Inder Majumdar, Ph.D. Scholar from the University of Wisconsin Urbana, IL, delivered a research talk on "Examining the Accuracy of Indian Inflation Estimates: Evidence from Engel Curves”. This event was jointly organized by CQLA and QIC.

• Symbiosis School of Economics, in collaboration with the Symbiosis Centre for Urban Studies and the National Institute of Urban Affairs (NIUA), organized a round table discussion addressing the subject "Measuring City-GDP: A Case Study of Pune City." Notable experts in urban studies, data analysis, and individuals closely associated with the Indian Statistical System actively joined the discussion, contributing their valuable insights and perspectives.