Hi, I am a Sr. Software Engineer currently working full-time with Java, Python, and React/Preact. I have a Master’s degree in Computer Science and possess a decent knowledge of Math.
I am interested in entering the AI field in the near future. I am currently enrolled in the ‘Deep Learning Specialization’ and will soon complete it.
I have noticed there are multiple specialized courses available, and I am trying to decide on my next course. Some options I am considering are the ‘Machine Learning Specialization’ and the ‘TensorFlow Developer Professional Certificate’ from DeepLearning.AI.
I would appreciate some advice on which course I should take to transition from a full stack engineer to an AI engineer
The usual sequence is Machine Learning Specialization (an introductory course), then the Deep Learning Specialization (an intermediate course), then one of the advanced courses like TensorFlow Developer.
I do not see an advantage in taking MLS after you complete DLS. It will all be review.
Sorry, I don’t have any career advice, other than all the excitement is in Generative models at the moment. There are several courses in that area.
I have changed fields multiple times (hardware engineer → software QA → test automation → Linux kernel engineer → Linux sival engineer → firmware sival engineer) within my ~15 year career. The easiest way to switch is always internally within your company. It’s pretty hard to get an interview (let alone pass that interview) if your experience does not match the new field you are applying for. Internally within your company it is much easier, where while you might not have the experience in the field, you can make it up knowing the company and product/system already.
For example, if there are any processes at your current job that collect a lot of data, and no one is putting it to good use, that’s a great place to start contributing to your current employer in a new role.