APPARATUS FOR POST ACTION PLANNING AND METHOD OF USE

1 . An apparatus for post action planning, the apparatus comprising:

at least a processor;

a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to;

receive an user experience data from an input device;

identify at least a learning datum as a function of the user experience data;

generate growth data;

determine at least one post action plan as a function of the at least a learning datum and the growth data;

create a user interface data structure, wherein the user interface data structure comprises the at least one post action plan; and

transmit the at least one post action plan and the user interface data structure.

2 . The apparatus of claim 1 , wherein receiving the user experience data further comprises receiving from the input device through an experience smart assessment.

3 . The apparatus of claim 1 , wherein the apparatus further comprises an input device, the input device configured to receive the user experience data.

4 . The apparatus of claim 1 , wherein identifying the at least a learning datum as a function of the user experience data further comprises receiving the at least a learning datum from a user through a learning smart assessment, wherein the processor is configured to generate the learning smart assessment a function of the user experience data.

5 . The apparatus of claim 4 , wherein generating the learning smart assessment as a function of the user experience data comprises generating the learning smart assessment using a machine learning model, wherein generating the learning smart assessment using the machine learning model comprises:

receiving assessment training data comprising a plurality of user experience data correlated to a plurality of smart assessments;

training an assessment machine learning model as a function of the assessment training data; and

generating the learning smart assessment as a function of the trained assessment machine learning model.

6 . The apparatus of claim 1 , wherein the learning datum comprises positive learning datum and negative learning datum.

7 . The apparatus of claim 1 , wherein identifying the at least a learning datum comprises identifying the at least a learning datum using a machine learning model.

8 . The apparatus of claim 1 , wherein the growth data comprises a growth score, the growth score comprising a numerical score of a user.

9 . The apparatus of claim 1 , wherein the at least one post action plan contains a plurality of individual action plans, wherein each of the plurality of individual action plans contains an individual predictive growth score.

10 . The apparatus of claim 1 , further comprising a graphical user interface (GUI) communicatively connected to the at least a processor, the GUI configured to:

receive the user interface data structure; and

display the at least one post action plan as a function of the user interface data structure.

11 . A method for post action planning, the method comprising:

receiving by at least a processor, user experience data pertaining to a user;

identifying, by the at least a processor, learning datum as a function of the user experience data;

generating, by the at least a processor, growth data;

determining, by the at least a processor, at least one post action plan as a function of the at least a learning datum and the growth data;

creating, by the at least a processor, a user interface data structure, wherein the user interface data structure comprises the at least one post action plan; and

transmitting, by the at least a processor, the at least one post action plan and the user interface data structure.

12 . The method of claim 11 , wherein receiving, by the at least a processor, the user experience data further comprises, receiving, by the at least a processor, the user experience data from an input device.

13 . The method of claim 11 , wherein the input device is configured to receive at least audio data.

14 . The method of claim 11 , wherein identifying, by the at least a processor, the at least a learning datum as a function of the user experience data further comprises receiving the at least a learning datum from a user through a learning smart assessment, the learning smart assessment generated, by the at least a processor, as a function of the user experience data.

15 . The apparatus of claim 4 , wherein generating the learning smart assessment as a function of the user experience data comprises generating the learning smart assessment using a machine learning model comprising:

receiving assessment training data comprising a plurality of user experience data correlated to a plurality of smart assessments;

training an assessment machine learning model as a function of the assessment training data; and

generating the learning smart assessment as a function of the assessment machine learning model.

16 . The method of claim 11 , wherein the learning datum comprises positive learning datum and negative learning datum.

17 . The method of claim 11 , wherein identifying, by the at least a processor, the at least a learning datum comprises identifying the at least a learning datum using a machine learning model.

18 . The method of claim 11 , wherein growth data comprises a growth score, the growth score comprising a numerical score of a user.

19 . The method of claim 11 , wherein the at least one post action plan comprises a plurality of individual action plans, wherein each of the plurality of individual action plans comprises a predictive growth score.

20 . The method of claim 11 , wherein transmitting, by the at least a processor, the user interface data structure further comprises, transmitting, by the at least processor, the user interface data structure the to a graphical user interface (GUI) communicatively connected to the at least a processor, wherein the GUI is configured to:

receive the user interface data structure; and

display the at least one post action plan as a function of the user interface data structure.