Updated: Aug 28
1. Relevant ML Experience Comes First - Put your most relevant and impressive machine learning modeling project description, in the 1st section including a link to your code on GitHub. Such that your 1st section should be titled:
Education - if done as part of your degree
Work Experience - if as part of an Internship
ML Experience - if during your own time. E.g. as a side project.
2. Elevator Pitch - Try to phrase a summary (3-4 sentences) about your experience and skills. And add this section to the top of your CV only if you feel it's written well and adds some key additional information that you haven't mentioned already in other sections. You want to avoid repetition. So for instance, if you studied at a top university abroad and afraid that it isn't a well-known academic institute in the country you are currently searching for a job, here is where you can mention its World ranking. And please try avoiding simply listing your soft skills but rather show that you have them through a description of your experience. For example, Instead of listing good communication skills, say that you have experience working in a multidisciplinary team and perhaps guided others on how to complete their tasks.
3. List of ML Skills - Below the summary section or at the very top, list your Machine Learning Skills. E.g. ML, DL, Python, C++, OOP, Pandas, Seaborn, ScikitLearn, Keras, Pytorch, Git, Linux. I advise not to mention Microsoft Office Tools such as Excel since it's taken for granted that you are familiar with these basic tools.
4. Indicate Specific Programming Packages in your Experience - In the description for your ML experience indicate which programming packages you used. E.g Visualizations using Matplotlib/Seaborn, Cleaned and prepared data using Pandas, ML Modeling using ScikitLearn/Keras/Pytorch.
5. Check your Grammar, Spelling & Content - After you completed your 1st draft read it again a couple of days later and you will notice that you can improve the grammar and punctuation. Afterward, ask a friend to check it for both grammar and content. The more experienced your friend is in the ML field the better they will be able to advise you especially in terms of the content.
* Be honest about your skills and experience. Because while you might have not pass an interview at this stage it doesn't mean that the same company isn't highly impressed by your achievements and personality such that they are looking forward to interviewing you again once you gain more knowledge/experience.
* As long as you keep studying even if it is just for one hour a day, you keep increasing your chances for greater opportunities and at some point, your experience will become valuable enough for those looking to hire.