Regarding what #1 said about "In my experience, you need to stick with..." - definitely listen. Be careful with the C++ hype tho. I spent way too much time on low-level stuff years ago and it barely helped my pivot. Since you only have 4 months, just grab O'Reilly Hands-On Machine Learning with Scikit-Learn Keras and TensorFlow 3rd Edition and grind. Focus on practical libraries, not language theory. It's basically the industry bible.

@Reply #2 - good point! Honestly, I was in a similar boat when I had a tiny window to learn NLP. I was happy to dive into the nitty-gritty, but realized pretty fast that over-engineering was my enemy. I compared Python and Julia for a while; Python's library support is just unbeatable right now, while Julia is fast but the package ecosystem feels a bit thin for a beginner. I found that Manning Publications Deep Learning with Python Second Edition worked well because it focuses on the logic, not just syntax. Since you're watching your budget, dont bother with a fancy GPU. Im very satisfied with Google Colab Pro Monthly Subscription for training models. It gives you access to decent T4 or A100 chips without the upfront cost of hardware. It basically kept me afloat during my pivot... sticking to the path of least resistance is usually the smartest move.

In my experience, you need to stick with Python for a 4-month pivot. Over the years, I've tried many languages, but Python is the only one with the library support you need right now. Grab the DeepLearning.AI Machine Learning Specialization Coursera Subscription for $49 per month. Its the most cost-effective way to get certified and actually understand the math without wasting your $500 budget on fluff.