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How to Show Data science Project in Resume

In any project, the Data analyst role is to deal with data. The data for data science projects come from multiple sources. This post will explain how to put in data science project in Resume.
Data Science project for Resume The first step for an interview of any project is you need Resume. You need to tell clearly about your resume.

In interviews, you will be asked questions about your project. So the second step is you need to be in a position explain about project.

The third point is you need to explain the roles you performed in your data science project. If you mention the roles correctly, then, you will have 100% chance to shortlist your resume. Based on your experience your resume can be 1 page or 2 pages.
How to show Technologies used in Data science projects In interviews, again they will be asked how you used different tools to complete your data science project.

So, you need to be in a position to explain about how you used different options present in the tools. Sometime…

Python user defined functions real examples

In Python, user-defined functions real use is you can use in scripts You can avoid repeated work. These are very different from C/C++/JAVA. I will give you syntax and example for your quick reference and how to start learning quickly.
udf in python

Python Syntax for User defined function(UDF)

def function_name(list of parameters): 
"docstring" 
statement(s) 
return(parameter)       

  Explanation of each keyword 

  1. The keyword def symbolizes the start of the function header.
  2. A function name to uniquely identify it. Function naming follows the similar rules that are used for writing identifiers
  3. List of parameters also called as a list of arguments through which value is passed to the function. The list of parameters is optional.
  4. A colon (:) to mark the end of function header.
  5. Optional documentation string (docstring) is used to describe the purpose of the function, which is slightly similar to python documentation using comment.
  6. Python statements that perform the intended task for which the user-defined function is made. It is mandatory to maintain the indentation level while writing python statements in the function definition.
  7. In the end, an optional return statement is used to return a value (result) from the function. This statement can contain an optional parameter to return the computed result back to the function call. If there is no parameter in the statement or the return statement is not mentioned at the end of function definition then the function returns the None object.
The above example is a good one. You can start learning Python UDF quickly.

Python Vs Other Languages
Python in analytics
Python is one of the most popular languages in data analytics. There are many other languages that have an option to create UDFs. Even in SQL of any database, you can easily create user-defined functions.

Advantages of Python UDF

  • User-defined functions help to decompose a large program into small segments which make the program easy to understand, maintain and debug.
  • If repeated code occurs in a program. The function can be used to include those codes and execute when needed by calling that function.
  • Programmers working on the large project can divide the workload by making different functions.
References

One practical advice

It is always a good idea to name user-defined functions according to the task they perform.

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