@Vaporiser Just to add what @DataScience mentioned, I have a similar background (In my 30s and have an accounting degree doing audit work before I made a mid-career switch. Currently a data analyst). Sharing some pointers:
1. You highlighted valid points on lacking SQL, Python and other direct work experience, which hiring companies would usually move on to other candidates who can pass their initial technical test. So brushing up on SQL, Python and getting real data hands-on experience will increase your interview chances, and land a job, leading to my next point below.
2. On getting real data hands-on exposure, one forum member mentioned: "Industry Connect" (see the forum post by clicking the link here) which is more towards the Microsoft tech stack. It does match closely what I do for my current work using Microsoft Business Intelligence ("BI") tools. Another training provider which I have a friend doing with now is Generation Singapore, the focus is more on BI and data engineering (link is here).
Or else, your next best bet is to go for an internship or traineeship to acquire relevant experience.
Click here for a sample of an analytics traineeship role that is open to mid-career switchers and fresh graduates.
3. The term "entry-level" is actually misleading as most hiring companies are not willing to accept people with zero relevant experience, except for internships, traineeships or companies willing to give chance to let one become a data professional. Refer to Point 2 on getting the required experience.
4. On data bootcamps, I had taken Heicoders AI200: Applied Machine Learning last October, which I found the contents industry-relevant and the learner's notes are very well created, serving as a good reference. If you do not have Python programming knowledge, taking both AI100 and AI200 may be your starting point. Or else, you can go for AI200 module directly.
Do feel free to ask if you need further clarifications.
1. You highlighted valid points on lacking SQL, Python and other direct work experience, which hiring companies would usually move on to other candidates who can pass their initial technical test. So brushing up on SQL, Python and getting real data hands-on experience will increase your interview chances, and land a job, leading to my next point below.
2. On getting real data hands-on exposure, one forum member mentioned: "Industry Connect" (see the forum post by clicking the link here) which is more towards the Microsoft tech stack. It does match closely what I do for my current work using Microsoft Business Intelligence ("BI") tools. Another training provider which I have a friend doing with now is Generation Singapore, the focus is more on BI and data engineering (link is here).
Or else, your next best bet is to go for an internship or traineeship to acquire relevant experience.
Click here for a sample of an analytics traineeship role that is open to mid-career switchers and fresh graduates.
3. The term "entry-level" is actually misleading as most hiring companies are not willing to accept people with zero relevant experience, except for internships, traineeships or companies willing to give chance to let one become a data professional. Refer to Point 2 on getting the required experience.
4. On data bootcamps, I had taken Heicoders AI200: Applied Machine Learning last October, which I found the contents industry-relevant and the learner's notes are very well created, serving as a good reference. If you do not have Python programming knowledge, taking both AI100 and AI200 may be your starting point. Or else, you can go for AI200 module directly.
Do feel free to ask if you need further clarifications.
