Hi Aniroodh,
I can understand that you want to prepare data to predict a multi-step future estimate of a certain parameter using previously logged time-series data.
For Question 1: You can try a different approach where for each training example, you select 500 consecutive values as the input and the subsequent 200 values as the output. Slide this window through your time series to create multiple such pairs. By preparing data like this you can train an LSTM network for multi-step time series forecasting.
Please refer to the prepare data section of the following documentation for more details.
Regarding Question 2: The ability to predict multiple steps at once without looping depends on how you've structured and trained your network. If your network is trained for one-step predictions, you'll need to use a loop or retrain your network to predict multiple steps at once.
I hope this was helpful.
Regards,
Shivam Lahoti.
