The learning path for a data scientist is full of traps.
It goes something like this:
- Python (or R)
- Algorithms
- Math
- Stats
- Make a Portfolio
- Get some projects under your belt
- More math
- Neural networks
- Deep learning part 2
- More projects (now with cats & dogs)
...And it's a mess.
No wonder why you are struggling.
And it turns out that in this economy, it's even become a lot harder with the "traditional" approach.