This workshop is designed for educators (e.g., faculty, trainers) who have an interest in teaching and delivering data science courses/programs. Through a careful selection of case studies, datasets, and Python notebooks, this workshop will provide a pedagogical journey of teaching data science at scale. Based on experiences with teaching data science at LUMS, this workshop aims to share a rich set of perspectives about developing data science courses grounded in sound data design, exploratory data science and visualization, causal inference, statistical inference, machine learning, big data analysis, and data ethics.
The workshop will build on the conceptualization of data science as creative problem solving, with a focus on project-based learning. Through examples and case studies, the workshop aims to highlight the benefits of incorporating societally relevant and practical applications of data science in courses to cater to diverse audiences as well as to prepare students for impactful interdisciplinary work. Finally, the ways to scale data science courses while ensuring sound hands-on and classroom learning will be explored in this workshop.
By the end of this workshop, the participants should be able to:
- Conduct and teach sound data analysis using public datasets and appropriate examples and activities
- Develop strategies for integrating data science into existing curricula across different subject areas
- Describe a given dataset and assess its quality
- Build data pipelines (collection, cleaning, EDA, modelling, evaluation, results) for ''repeatable'' work
- Use Python and popular data science libraries such as Pandas, Numpy, Matplotlib, and Scikit-learn to analyze and visualize data.
- Understand the theory behind drawing inferences from data
- Communicate results effectively
Associate Professor of Computer Science at LUMS.
Course Fee: TBA
Please go through Policies & Code of Conduct
Participants must register online through CES website by clicking on their desired course and filling out a one-page form. Before starting the registration process, please ensure that you have a formal scanned picture (for CES smart card) and CNIC details. Incorrect information provided during the registration process will lead towards cancellation of your enrolment at any stage and participants will not be entitled to claim a refund.
Once you have completed your online registration for your desired course, you may proceed to payment section. You have the option to pay online using your bank debit/credit cards through LUMS online payment system??https://pay.lums.edu.pk??OR by downloading the fee vouchers and depositing cash in any branch of designated banks specified on the fee voucher. Once you make your payment, you will receive a confirmation email within 24 to 48 working hours and your payment status will be updated to "PAID" in the online application portal