A Beginner’s Educational Guide to ML/AI for Pakistani Students

An educational guide on how to get started in Machine Learning (ML) and Artificial Intelligence (AI) as documented from the Pakistan.ai group.

An educational guide on how to get started in Machine Learning (ML) and Artificial Intelligence (AI) as documented from the Pakistan.ai group. Many such guides already existent on the internet however the circumstances of Pakistan are different and hence require a customized guide. This guide assumes that readers have some exposure to programming and understand high school level math (inter/metric level math across all path divisions).

Getting Started

Most of the greatest feats of AI today (Alpha Go, Google Search Engine and etc) are possible due to a sub-domain in AI called Machine Learning. This specific domain focuses on machines teaching themselves how to do a certain task (as defined by the programmer) based on input data i.e. the machine learns from the data hence the name “Machine Learning”. Due to the mathematical nature of ML this guide involves mathematical courses as well. It is strongly recommended that students complete them for a better understanding of the subject.

Above course (by Andrew Ng, Adjunct Professor of Computer Science at Stanford University) is Highly Recommended by the global community for its best introduction to machine learning for it’s simplicity and conceptual learning.

This particular course is shorter substitute for Andrew Ng’s machine learning course, because students are not required to code themselves as in Andrew Ng’s but more focused on explanation of algorithms and use of Libraries. Instructors are not using MATLAB as programming language but python, a well used language in the data science community, is being used all over the assignments.

These courses are easily accessible through Audit / Financial aid (2–3 weeks approval time) / Payment from coursera.org

Mathematics

Mathematics plays an import role in ML/AI or Data Science. As the method of teaching in mathematics within Pakistan requires great improvement, it is strongly recommended that the following courses are taken by all participants. Linear Algebra, Probability theory and Statistics, Multivariate Calculus, Algorithm and complex Optimization and others are the minimum level of mathematics needed to be a ML Scientist.

You can find more details about mathematics in below posts.

This entry was originally published on Anas Ayubi’s Git Hub page. I have taken from there and with few modification updated here.