I don't know if this is a right place to ask this question, but a community dedicated to Data Science should be the most appropriate place in my opinion.
I have just started with Data Science and Machine learning. I am looking for long term project ideas which I can work on for like 8 months.
A mix of Data Science and Machine learning would be great.
A project big enough to help me understand the core concepts and also implement them at the same time would be very beneficial.
I would try to analyze and solve one or more of the problems published on Kaggle Competitions. Note that the competitions are grouped by their expected complexity, from 101 (bottom of the list) to Research and Featured (top of the list). A color-coded vertical band is a visual guideline for grouping. You can assess time you could spend on a project by adjusting the expected length of corresponding competition, based on your skills and experience.
A number of data science project ideas can be found by browsing Coursolve webpage.
If you have skills and desire to work on a real data science project, focused on social impacts, visit DataKind projects page. More projects with social impacts focus can be found at Data Science for Social Good webpage.
Science Project Ideas page at My NASA Data site looks like another place to visit for inspiration.
If you would like to use open data, this long list of applications on Data.gov can provide you with some interesting data science project ideas.
Take something from your everyday life. Create predictor of traffic jams in your region, craft personalised music recommender, analyse car market, etc. Choose real problem that you want to solve - this will not only keep you motivated, but also make you go through the whole development circle from data collection to hypothesis testing.
Introduction to Data Science course that is being run on Coursera now includes real-world project assignment where companies post their problems and students are encouraged to solve them. This is done via coursolve.com (already mentioned here).
More information here (you have to be enrolled in the course to see that link)
