Machine Learning - A Tool for Smart Manufacturing

This course will provide necessary theoretical foundations in mathematics, computer science and systems engineering on diverse set of machine learning tools while providing training on modern tools such as Azure Machine Learning Studio or equivalent. Demonstrate the strengths of supervised learning, unsupervised learning and semi-supervised learning to industry professionals and manufacturing practitioners using case studies.

Learning Outcomes

Participants will be able to learn Machine Learning fundamentals: Regression, Classification and Clustering. Recognize where to use machine learning, select the most appropriate Machine Learning algorithm or technique, effectively use Microsoft's Azure Machine Learning Studio or Python.

Click here to view the complete course outline.

Course Fee: PKR 40,000/-

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 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?? 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.

Currently not available