Create Learning_Plan.md

Learning_Plan.md

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+I have found multiple online courses and I have decided to base my learning on the path given in the Algorithmic Trading course on Udacity.
+
+Step 1 is identifying which stock statistics are actually important to visualize and what they mean. It is also important to get accustomed with the very 
+powerful Pandas Library and other complementary libraries such as Matplotlib and NumPy and SciPy and Seaborn.
+
+Step 2 is understanding the widely used Financial Strategies and the basic financial concepts that govern the everyday trading process. It also important 
+to understand what the key indicators are while making a decision and also crucial to know that no-one should rely on a single indicator to make any decision.
+I have resorted mainly to the Bloomberg Marketing Concepts and other few online educatoinal courses to get a good hang and understanding 
+of some of the basic concepts.
+
+Step 3 is learning and understanding the underlying machine-learning techniques and trying to recognize which one is more effective and what kind of data 
+is to be fed in which kind of model.
+
+As of June 2020, I am still on steps 1 and 2 and am trying my best everyday to gain as much knowledge as possible. I will continue to push files that summarize 
+my learning of the key concepts and the underlying code with commented explaination. Many of these files contain functions that have been used in further 
+files so the code duplication is to bare minimum. This is a great resource mfor aosmone starting off in financial data visaulisation and does not want code all the
+bsics from scratch. 
+Anyone is welcome to download these files and import and use them in their own endeavours. Anyone interested can learn from this or contribute to it to make this repository 
+a valuable resource.