I completed the Post Graduate Diploma in the field of Computer Science and Artifical Intelligence.
Detailed Curriculum: IIIT Delhi Course Curriculum.pdf
The course consisted of the following modules:
i) Programming with Python - In this course, the proficiency in Python was developed as it applies to Data Science - the common functions, libraries, related packages, and techniques to visualize and make inferences about the data.
ii) Data Structures & Algorithms - In this course, the common data structures and algorithms concepts that are used in solving various computational problems were taught, with an emphasis on what's needed for AI & Data Science problems
iii) Design & Analysis of ALgorithms - The instructional blueprints allow us to solve any problem using calculation, data processing, and reasoning tasks. Algorithms also tend to be a lot more useful if they are efficient both in terms of time and space. The design and analysis of such algorithms, emphasizing methods of application
iv) Databases - SQL & NoSQL - The objective of this course was to make us proficient with the querying, accessing and working with the data across both SQL and NoSQL databases.
v) Machine Learning - Machine learning algorithms use computational methods to “learn” information directly from data without relying on a predetermined equation as a model. Some of the most popular Machine Learning algorithms, their applicability and implementation and concepts were taught in this module
vi) Advanced Machine Learning - In this course, the understanding of Machine Learning combining techniques (ensemble techniques) using decision trees and random forest algorithms were taught. We were also taught how to improve the model performance of machine learning models while dealing with issues of model complexity
vii) Deep Learning for AI - Deep Learning, a specialized and advanced family of machine learning algorithms, works well when massive volumes of data, typically unstructured and disparate, is available. Deep Learning models are capable of solving such complex tasks such as recognizing objects within an image and translating speech in real time. In this course we were taught about Deep Learning and Neural Networks, and how to implement them in the real world.
viii) Capstone Project - Through a comprehensive Capstone project, we designed and developed an end-to-end solution to a problem that reflects existing challenges in the real world
The course was taught by university professors and some industrial experts. It deep-dived into each of the concepts that helped me fill my gaps, as I belonged from a non-computer science background. The projects were designed from the industry perspective and really helped me create a good portfolio. Not only that it also helped me understand the concepts in depth and improved my problem solving skills along with increment in my skillsets.
This repo consists of all the projects that I have completed during the course. Also, the marksheet of each module has been provided in the Readme inside each module folder