The training course “Artificial Intelligence (AI) for Social Scientists” is designed to equip individuals with the fundamental concepts and practical skills required to leverage AI in their respective fields. The program will be aimed at professionals and university students who wish to develop foundation in AI and learn how to apply it solving real-world problems. This course consists of three days (03 Hours * 03 Days). The training program will commence with an introductory session on the first day, wherein participants will be equipped with the foundational knowledge of Artificial Intelligence alongside the basics of the Python programming language. The subsequent two days will involve the practical application of AI methodologies in addressing pertinent economics questions through the examination and analysis of data. Participants will explore prevalent AI techniques and conduct a comprehensive predictive analysis of the gathered data to provide well-informed solutions.
LEARNING OUTCOMES
Upon the completion of three days training course, the participants will be able to:
- Gain a comprehensive understanding of AI concepts & their applications in social sciences
- Effective use of ChatGPT
- Learn the basics of the Python programming language
- Enhance analytical & problem-solving skills for effective implementation of AI methodologies
- Learners to integrate AI-generated insights into decision making while acknowledging the limitations and potential biases of these technologies.
- Create predictive models to provide insights into future trends & patterns based on historical data
- Work on real-world projects to gain experience & communicate findings to diverse audiences
TENTATIVE SCHEDULE
| Day | Time | Topics | Resource Person(s) |
| Monday
29th Jan |
10:00 | Introduction to AI | Izzah Salam & Fakhera Nazir |
| 10:30 | Applications of AI in Social Sciences | ||
| 11:00 | ChatGPT | ||
| 12:00 – 13:00 | Python Basics | ||
| Tuesday
30th Jan |
10:00 | Recap Day 1 | Ayyaz Hussain |
| 10:15 | Data Pre-processing | ||
| 11:00 – 13:00 | Regression using AI Models | ||
| Wednesday
31st Jan |
10:00 | Recap Day 2 | Ayyaz Hussain |
| 10:15 – 13:00 | Classification & Clustering |
RESOURCE PERSONS
| 1. Ayyaz Hussain
Professor of Computer Science at the Quaid-i-Azam University, Islamabad. He worked as Research Professor at the Gwangju Institute of Science and Technology, South Korea during 2013-2014. His expertise includes Artificial Intelligence, Neural Network, Theory of Computation, and Digital Image processing. |
| 2. Fakhera Nazir
Lecturer at the University of Gujrat. She completed her MS in Computer Science from the NUST in 2018. Her main expertise is Programming Languages like C# and Python, Her research interest are Machine Learning, Deep Learning and AI. |
| 3. Izzah Salam
Data Scientist at the Pakistan Institute of Development Economics, Islamabad. She completed her MPhil in Computer Science from the Quaid-i-Azam University, Islamabad, in 2021. She is professional trainer and caries expertise in Machine Learning, Social Network Analysis, Deep Learning, and Data Mining. |
HOW TO REGISTER
| Who should attend this course? | This training is specifically designed for researchers, academicians, university students, and practitioners with background in social sciences. |
| How to register | Interested individuals are required to fill out the online Google Form https://forms.gle/CtEyniuHSs5jozHo8 latest by Sunday 20th January 2024.
There are only 30 seats available for in-person training. Preference will be given to mid-career researchers, academicians, and practitioners on a first come first serve basis. |
| Course Fee | There is NO course fee. The course is sponsored by the RASTA program at PIDE.
Selected participants will be required to bring official consent letter from their organizations (in case of professionals) or Recommendation Letter from their research supervisor/ HoD (in case of university students). |
CONTACT:
Ms Izzah Salam
Data Scientist, PIDE
Email: [email protected]
Ms Amina Qureshi
Assistant Chief (Policy), PIDE
Email: [email protected]
Tel: 051 9248026
