Hello All, I want to know about the list of data science projects for beginners. I am in my final year and want to build a career in data science and looking for data science projects with source code. I have checked on GitHub and google and found this list (https://www.interviewbit.com/blog/data-science-projects/) and looking for more new trending projects. Can anyone help me out?

Hey Shivam,I would suggest to create your own source code instead of relying on others and doing copy-paste.Sometimes copying a code snippet is ok as long as it meets your requirement and you understand it.In todays works there are multiple ways to get the Dataset in the domain you are interested, please get and start working on those, could refer to UCI Machine Learning Repository (https://archive.ics.uci.edu/ml/index.php), or Kaggle.com for datasets. Working on a dataset from scratch will give you confidence and you will learn a lot.Also for end-to-end project you could use Flask / Django etc or some API's and then host that website for real-world, with this you will be able to work on Data Science Project end-to-end.Incase you stuck anywhere then post here in DSF, and we are always here to help.I know this may not be easy, but take a baby step and then we are here to hold the hands.All the Best.

Hello Everyone, I am very confused to choose a career in Data Science. I have 1 year of experience in R programming and want to switch careers in data science. I have to spend a lot of time on research on how to become a data scientist and what’s the average salary. According to this post https://www.interviewbit.com/blog/data-scientist-salary/ the average salary for a data scientist is Rs.698,412 per year. With less than a year of experience, an entry-level data scientist can make approximately 500,000 per year. Data scientists with 1 to 4 years of experience may expect to earn about 610,811 per year. Can anyone suggest me, Is data science is the highest paying job?

Data has become an essential topic in the corporate world these days. Everyone needs to talk about the knowledge and quality that can be extracted from the results. There is a good explanation for this—data is among the essential tools available to today's advertisers, agencies, marketers, media organizations, and much more.

Have you come across Data Science jargon and buzzwords such as Artificial intelligence (AI); Machine Learning (ML); Deep Learning (DL); Neural Network (NN) etc.. want to know more about them and how each of them differ? If so then checkout this article, which will give you a brief idea what these are.

Brilliant work.Very well-written article. Yes, I have heard a lot about this "buzzword" around me and thinking it is the only "buzzword" you need to adopt and survive in the IT industry.Is it true?

The application of piecewise hazard model in mortality data becomes more useful in survival methods. This method is used to find the number and location cut points and to estimate the hazard model. The objective of this paper is to illustrate the piecewise constant hazard model and to find significant factors for under-five child mortality.

Dear team, I am working on a research based on content-based package selection in the telecom industry. So I want to get a data set based on customer usage of their package. I mean internet usage, voice usage etc. Can you please give me a support. Anyone have that type of a data set, can you please share with me.

I have a Data Cloud Lab and Github too, Ready to contribute someone like you. please send me your resume at darrajit@gmail.com. I will find out your solution. Thank you

Many times, I have seen data science professionals who know very well what is p-values but they struggle to explain it. I have also seen many professionals who don’t want to get into technical details but want to know more and understand why it is so important.

Gulp is used by software development teams as the streaming build system with which a number of tasks can be programmed and automated in an effective way.

This article is very informative and the steps which are been soon can be easily approcable .A lit more effective and efficient way the author tries to summarise the step here.

What is the correlation between Data Science and Econometrics.I have been thinking to find out if Data Science can stand alone without Econometrics. Will it rather be wise to say Econometrics forms a better modelling blocks on which Data Science thrive. I will like to know the correlation between this two fields. Thanks

As the volumes of data increase each day, organisations are begining on Data Science and Data Analytics to make sense of it. This article is a basic introduction to those new to the field