Designing and Delivering Data Science Courses at Scale

May 19, 2023 - May 20, 2023
Application Deadline:
May 18, 2023
2 Days
Friday - 2:00 PM to 6:30 PM
Saturday - 9:00 AM to 1:30 PM
Delivery Method:

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.

Learning Outcomes:

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
Click here to view the complete course outline.
Dr. Ihsan Ayyub Qazi
Principal Investigator at the National Center in Big Data & Cloud Computing (NCBC)
Associate Professor of Computer Science at LUMS.

Course Fee: TBA

Note: CES may cancel or postpone a course due to insufficient enrolment or unforeseen circumstances. In this case, the university will refund registration/processing fee (if any) but will not be responsible for any other related charges/expenses including cancellation/change charges by airline and travel agencies.

Please go through Policies & Code of Conduct

Participants must register online through the 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 the following:

- A passport-sized photograph for the CES smartcard. It should be against a white background.

- Correct 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, you may proceed to the payment section. You have two options:

1. Pay online using your bank debit/credit cards through LUMS online payment system

2. Download the fee voucher and deposit cash in any branch of the designated banks specified on the fee voucher.

Once the payment has been made, you will receive a confirmation email within 24 to 48 working hours, and your payment status will be updated to "ENROLLED" in the online application portal.


KalPay Taleem offers an instalment facility for participants enrolled in CES on-campus courses and workshops. If you want this option, please email or call at 0328 3044414 for more information.