DEV Community: Md Meraj Kausar

How to get an Internship if you are not from a good college

Md Meraj Kausar — Sat, 24 Dec 2022 10:31:00 +0000

If you are in your final year or you are learning some new technologies like Web development ,Data Science , Machine Learning etc you will be looking for Internship. But getting internship is not so much easy .In this article I will share my story of despite not being from a good college how I got my first Internship.Like you, I also used to apply in many Internships but was not getting responses from companies . What I learn from my experience is many things matter to get an Internship in India. So first you should select a platform to apply for the Internship like Linkedin, Internshala. Personally, I like Internshala . First, you have to be good in any one field. You don’t have to be good in many fields but you should master a specialized field and try to apply to these companies which are looking for that person. Other things that matter are you should have a good resume where your project, GitHub profile link should mention. Also, try to write a brief summary about yourself and what you are expecting from the company . After applying don’t sit back and relax but try to message them on different platforms that you have applied for their companies. And if you get a response from the company and they gave some tasks try to do that accurately and be prepared for the interview, Try to learn about their company also. I wish you all the best. Follow me for more articles like this.

Data Preprocessing

Md Meraj Kausar — Sat, 17 Dec 2022 19:27:09 +0000

What is Data Pre-processing?
"Data Preprocessing is a process of converting your raw data into suitable form."
Data Preprocessing Steps Involves
1:Getting Dataset
2:Importing Libraries
3:Importing Datasets
4:Finding Missing Values
5:Encoding Categorical Data
6:Splitting Dataset into Training & Test Set
7:Feature Scaling

Top Sites for Education and Career Enhancement

Md Meraj Kausar — Sat, 03 Dec 2022 18:28:01 +0000

➢ ► FREELANCING
➢(http://www.fiverr.com/
➢http://www.upwork.com/
➢http://www.odesk.com/
➢http://www.elance.com/
➢http://www.99designs.com/
➢http://www.freelancer.com/
➢http://www.guru.com/
➢http://www.peopleperhour.com/
➢http://www.freelanced.com/
➢http://www.ifreelance.com/

)
➢ ► CAREER
➢https://www.linkedin.com/
➢https://www.indeed.com/
➢https://www.naukri.com/
➢https://www.monster.com/
➢https://www.careercloud.com/
➢https://www.dice.com/
➢https://www.careerbuilder.com/
➢https://www.jibberjobber.com/
➢https://www.glassdoor.com/index.html

➢ ► RESUME
➢https://zety.com/
➢https://www.resumonk.com/
➢https://www.resume.com/
➢https://www.visualcv.com/
➢https://www.cvmaker.com/
➢https://resumup.com/
➢https://resumegenius.com/
➢https://www.resumebuilder.com/
➢http://www.resumebaker.com/
➢https://enhancv.com/

➢ ► INTERVIEW PREPARATION
➢https://www.ambitionbox.com/about-us
➢https://www.acetheinterview.com/
➢https://www.geeksforgeeks.org/
➢https://leetcode.com/
➢http://www.gainlo.co/
➢https://careercup.com/
➢https://coder.com/careers
➢https://interviewup.blogspot.com/
➢https://www.livecareer.com/resources/inter
views/prep/interviewbest-blog
➢https://www.indiabix.com/

➢ ► FREE ONLINE EDUCATION
➢https://www.coursera.org/
➢https://www.edx.org/
➢https://www.khanacademy.org/
➢https://www.udemy.com/
➢MIT OpenCourseWare
(https://ocw.mit.edu/index.htm) (Free
Online Course Materials)
➢https://online.stanford.edu/
➢https://www.codecademy.com/
➢(https://github.com/pamoroso/free-python-books)
Learn Python for free

An introductory view of Data Analysis

Md Meraj Kausar — Sun, 27 Nov 2022 12:00:41 +0000

What is Data analysis?
Data analysis is a process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.
Tools used in Data Analysis :
Auto-managed closed tools->
Qwiklabs, Tableau,Looker, Zoho Analytics
The programming language used: Python,R,Julia
Why Python for Data Analysis?
*-very simple and intuitive to learn.
-correct language
-powerful libraries

-free and open source
-Amazing community,docs, and conferences
**When to choose R language?
*- When R studio is needed
-When dealing with advanced statistical methods.
-When extreme performance is needed.
**Data analysis Process:
1:Data extraction->
SQL,Scrapping ,File format(CSV,JSON,XML),Consulting APIs,Buying Data,Distributed database
2:Data cleaning ->
• Missing values and
empty data
• Data imputation
• Incorrect types
Incorrect or invalid
values
• Outliers and non
relevant data
● Statistical sanitization

Data Wrangling->
Hierarchical Data
Handling categorical
data
Reshaping and
transforming
structures
Indexing data for
quick access
Merging,combining
and joining data
4:Analysis->
• Exploration
• Building statistical
models
• Visualization and
representations
. Correlation vs
Causation analysis
• Hypothesis testing
● Statistical analysis
• Reporting
5:Actions->
• Building Machine
Learning Models
Feature Engineering
• Moving ML into
production
• Building ETL
pipelines
• Live dashboard and
reporting
• Decision making
and real-life tests
**PYTHON ECOSYSTEM:
**The libraries we can use ...
pandas: The cornerstone of our Data Analysis job with Python
matplotlib:The foundational library for visualizations.Other libraries we'll use will be
built on top of matplotlib.
numpy:The numeric library that serves as the foundation of all calculations in Python.
seaborn:A statistical visualization tool built on top of matplotlib.
statsmodels:A library with many advanced statistical functions.
scipy:Advanced scientific computing, including functions for optimization,linear
algebra, image processing and much more.
scikit-learn:The most popular machine learning library for Python (not deep learning)