Overview:

The Data Science and Machine Learning with Python course offers a practical introduction to modern data-driven decision-making. Across 14 sessions, learners build strong foundations in data science, AI, and ML while gaining hands-on experience with Python. The curriculum covers data collection, preprocessing, feature engineering, and statistical analysis, progressing to supervised and unsupervised learning methods such as regression, decision trees, random forests, and clustering. Emphasis is placed on data visualization, storytelling, and real-world case studies in classification and regression. Advanced topics like ensemble methods, SVMs, and neural networks prepare learners for further study or entry-level roles in data science.

Learning Outcomes:

By the end of this course, the students should be able to:

• Learners will be able to understand the foundations of machine learning, including supervised, unsupervised, and basic model evaluation.

• Learners will be able to write Python code to preprocess data, train models, and evaluate results using popular ML libraries.

• Learners will be able to apply appropriate ML techniques to solve beginner-level problems and interpret outcomes

Course Outline

Muhammad Salaar Arif Khan

Muhammad Salaar Arif Khan is an Adjunct Faculty member at the Lahore University of Management Sciences (LUMS), where he is also pursuing a PhD in Electrical Engineering with a specialization in Signal Processing and Artificial Intelligence. He holds a Master's degree in Electrical and Computer Engineering from Auburn University, USA. His academic and research interests lie at the intersection of advanced signal processing techniques and AI-driven solutions

Application Process:

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 smart card. 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 https://pay.lums.edu.pk 

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.

Installment:

KalPay Taleem offers monthly installments for all CES on-campus courses and workshop fees. For more details, contact via WhatsApp at 0328 3044414 (working hours - 9:30 AM to 6:00 PM), or visit taleem.portal.kalpayfinancials.com/sign-up to apply!

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