Courtesy: Nayem Sharker, Batch-191, Dept. of EEE, Green University of Bangladesh

When we hear someone's CGPA and it is excellent, everyone thinks how is that possible! So, through this article I will try to tell you how you can perform better in academics (Specifically for Green University EEE department's curriculum) and put you ahead from other.

We have to know the basic structure of our courses. So, we have total 144 credit, some of these we call non departmental and some we called core course like circuit analysis, electronics I & II etc. and some are the major courses like power system, power plant engineering, power system protection etc. If we take a look at our course outlines which are provided by our course teachers at the beginning of semester, there is a part that called pre-requisite. Mainly in this article I will try to show you the points you have to focus on.

MATH 101- In this course you can see the basic algebra, function, some theorem regard finite and infinite form, ordinary and partial differential and integral (Volume and Surface integral, summing series, Gamma function and Beta function etc. This course is completely helpful for the MATH 103 course. Because all of the topic you learn from MATH 101 are interrelated with MATH 103. We can say the advance version for MATH 101 is MATH 103. If you lack in MATH 101, you have to suffer in MATH 103 course and this is the toughest math course, I think.

The pre-requisite course of MATH 205 is MATH 103. It’s all about matrix and series analysis. Note that this is the most effective course for AC circuit analysis, Continuous Signal and Linear system and Digital Signal Processing. MATH 207 is Geometry and Vector Analysis course. At the beginning of the course it is easier but after some classes it will be complex for the vector analysis. It will be mostly helpful to catch up the most common hard course ever in your graduation that is Engineering Electromagnetics. Also, MATH 207 have the Laplace transformation which can help you in Continuous Signal and Linear system and Digital Signal Processing [DSP]. MATH 209 is an interesting course for whom, they are going to research with massive data. This course will teach you how to lookup a data set & how much beautiful they are. This course is divided into two parts- Statistics and Probability. It can be helpful in research and forecasting with machine learning or data science. MATH 301 [Numerical Method] is one kind of machine learning course. This course shows you some effective algorithms and the principle of iteration to find an appropriate solution. The lab section will teach you to build the algorithm in MATLAB. The theory of math 301 will help you to understand power system I course, where some iteration methods are directly connected (like Gauss Seidel, Newton Raphson etc.)