Mathematics has always been a fascinating topic for me to explore. I think it is the most widely used language and is the key to various secrets of the world hidden behind doors, waiting to be opened. In order to satisfy my curiosity and learn more, I took up a few additional courses during and after college to understand more about its various applications.
The course is offered on Coursera by Stanford University. It is taught by one of the pioneers in the field of Machine Learning, Andrew Ng who covered the various nuances of this field at the most basic, mathematical level.
The highly mathematical nature of the course helped me make a strong foundation for multiple topics that are an integral part of the foundation of the science of Machine Learning. A few of the topics covered were as follows:
Supervised and Unsupervised Learning
Linear Regression
Classification using Logistic Regression
Neural Networks
Cost functions and Backpropagation
Apart from this, we also learned how to evaluate models, deal with bias and develop a few practical examples.
https://www.coursera.org/learn/machine-learning/home/welcome
This is a course offered by Harvard University and I had access to it through the infamous edX platform. The course is offered by Juliana Belding, Professor, Boston College and Peter Garfield, Professor, UC Santa Barbara.
The course discusses various areas where Calculus is used to provide a better insight. Various people from the fields of Biology, Economics and Physics shared how integral Calculus is to their work. The topics discussed were as follows:
Introduction to Mathematical Models
Economic Principles- Price and Demand, Price Elasticity of Demand, Revenue Maximization
Biotechnology- X-Rays and CT Scans
Statistical applications
Energy Equation
After completing the course above, I was intrigued to know more about the various fields discussed, in-depth. So I came across this Introductory Biology course that caught my attention. This course was offered by Eric S. Lander, Professor of Biology at MIT. I was able to access this course through edX
While Biology didn't always excite me, Prof. Lander's teaching style and actual classroom lectures intrigued me. The topics taught in the course were as follows:
Biochemistry
Genetics- Mendel and Morgan, Biochemistry and Genetics
Molecular Biology- DNA and Replication, Recombinant DNA
Genomics- Human Genome
Through this course, I was once again fascinated by the reach of Mathematics beyond anything else.
Human genes are a storehouse of information. The Human Genome Project of 1990 took over a decade to come to fruition. However, with the tools at disposal in today's world, the developments since then have been at a rapid pace. There is evidently a massive scope for application of Data Science in this field.
https://www.edx.org/course/introduction-to-biology-the-secret-of-life-3
Another course I did to expand my knowledge was on Economics. I was always interested in Economics because of it's evident dependency on Mathematics and this course helped me understand Economic principles even better. The course was offered by Dr. Peter Navarro of University of California, Irvine on Coursera
The topics covered in the course were:
Aggregate Supply and Demand Model
Keynesian Model- Fiscal and Monetary Policy
Economics Growth and Productivity
Unemployment, Inflation and Stagflation
International Trade
Budget, Trade, Fiscal Deficits
While the course didn't delve into the Mathematics of the subject, I understood the fundamental Economic concepts and once again I was interest to search more about how techniques of Data Science come into picture. I realized the stock market is one of the prime areas, so I explored further by browsing sites like the 'Wall Street Survivor'.
After a few courses, since I realized a developing passion for Data Science, I enrolled in a 2 week long course that would introduce me to a few techniques of ML and AI. The course used Python which suited me since I had used it a couple of times before.
The few topics covered in the course were as follows:
Supervised Learning- Linear Regression, KNN
Web Scrapping
Sentiment Analysis
Deep Learning- CNN, ANN
Introduction to OpenCV
Since the duration was short, we were taught a couple of basic things. We used simple libraries like BeautifulSoup and given datasets like Titanic, Brain-Weight and Iris. Since then, I have explored through websites like Kaggle and tried to practice the techniques I learnt on a few datasets.
C++ was the first object-oriented programming language I came across. It was a part of curriculum and I decided to do an NPTEL course on it to get a solid understanding of the concepts. C++ was also beneficial for me because it is extensively used to program micro-controllers and comes in handy while doing electronics projects. Many electronic circuit boards and PLCs are programmed using programming techniques used in C++.
The course was taught by Dr. Partha Pratim Das of IIT- Kharagpur. The course covered various data types, classes and concept of inheritance as few of the topics. This is where I gained a basic knowledge of concepts of OOPs and after that, learning Python was easier for me.
Control Systems was my favourite subject out of all the subjects taught in my engineering course. I twas probably because of the extensive use of mathematical concepts like Linear Algebra and Transformations. Hence, I decided to do a course that would help me understand the basics a little more in depth.
The course was taught by Prof. Ramakrishna Pasumarthy of IIT- Madras. The course covered topics like Mathematical Modelling of Systems, Block Diagrams, Time and Frequency Analysis, State Space Methods. This course, in contrast to what was taught as a part of my college curriculum, focused deeply on the mathematical aspects and built a sound foundation for me.
Owing to my interest in Control Systems, I decided to do an extension of the course and I enrolled myself in this course provided by Prof. Yogesh Vijay Hote of IIT- Roorkee.
In this course, I added to my existing knowledge about control system concepts and learnt topics like Modelling of Mechanical Systems in State Space, Stability Analysis in State Space, Transformation Matrices and State Feedback Designing. This is where I applied what I had learnt in the Linear Algebra course. It was fulfilling to see such elaborate use of mathematical techniques.
Microprocessors and Micro-controllers form an integral part of Electronics and Instrumentation Engineering. In order to be well versed with all the important concepts, I took this course.
The course was taught by Prof. Santanu Chattopadhyay of IIT- Kharagpur. In this course, I was taught the architecture and programming of 8085 microprocessor and micro-controllers like 8051, ARM and PIC.