python - ai, data analysis, ml in each area, just come up with a few example programs you've done on your own. eg. data sets for just about anything are available online free. Amount of fruit produced in an area. Number of people of different incomes. Whatever. Then, you simply grind through and produce a few examples. eg. Fruit production dataset + analysis. Which areas produce more oranges? which areas produce less? Can you map these differences? Yes, you can go crazy and analyze fruit production based on air (pm 2.5 quality, ozone, sunshine + clouds + sunlight per day, etc), watering, fertilizer, slope of land, soil composition, etc, but you don't need all that. You just need the example code (nice, clean, documented) + output (graphs, charts, etc), so that you can clearly explain how you got the data analyzed and results published so the recruiter knows you know the basics of data analysis. same for AI, ML. You don't need it to do a ton, just the basics. eg. I've taken a database of 'anime cat faces' and fed it thru my ML app that I programmed to differentiate between the faces and identify instantly which anime it belongs to. Again, clean code + data output as well as explain the training cycles and methods you have used. ... A ton is going online nowadays because of the compute power, so even add Azure + python cloud programming + Power BI analysis just to show you can do it in the cloud as well. ... Aside from that, really take advantage of internships - basically a straight path to a hired entry level job without going through the hassle of competing against ALL the other adults applying for jobs. You'll compete against a smaller subset of college students.