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?

People analytics is raising the agenda for companies worldwide. Technology that provides companies with many more methods of collecting data from people is projected to accelerate by using this data to enhance insight into the workforce, increase business efficiency, and enhance employee experience.

Data is an important basis for people to judge something. If the data is analyzed accordingly, people will further understand the essence of something and make it used by people.

Data blending is a recently developed approach used mainly by those working in big data analytics. It's a method of integrating data from different sources into a single structure. Blending offers a relatively fast and straightforward way to access several disparate data sources and identify correlations between them without the trouble and costs of conventional data integration.

Usually, the generation of a result is influenced by many factors in a specific environment. The data collection of factors and results is the basis of analysis.

Data Visualization is no longer an art. With evolving cognitive frameworks, multifaceted imaging, and intelligence; data visualization is exploring different horizons to perceive vast chunks of complex data. As a digital replacement for visual communication, Data Visualization has made it easier for companies to make decisions.

The state of things is transformed into data, which is convenient for electronic devices to store. On the contrary, the stored data is visualized, which is convenient for intuitive understanding of the process state of things.

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.

Dear All,Recently I have completed a course on the Internet of Things (IoT) by Cisco.Cisco Networking Academy transforms the lives of learners, educators, and communities through the power of technology, education, and career opportunities. Available to anyone, anywhere. I found it very useful.

Deep learning is a part of AI which was founded on artificial neural organizations, as neural organization will reflect the human thoughts. Deep learning which a subset of Machine Learning is is making revolutions in each field it comes into play. It decreases the human work and accomplishes the work precisely than people do. It emulates the human Brain with artificial neural organizations and dom

Thanks for the article, nicely explained along with covering the basic aspects.Also I was working on the dataset (from kaggle) on to predict covid through X-Rays, but seems using CNN or others not getting good score or prediction.After reading the article, seems got more details, and will try to implement in the EDA part and then train the model. Hope this should increase the prediction probability.

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.