kafka-connect-twitter VS mongo-kafka

I'm reading O'Reilly's "Mastering Kafka Streams and ksqlDB" to start learning Kafka, it was suggested for me on an ad by Confluent. Unsurprisingly it uses Confluent's software throughout the book. One of the first projects is a simple app that does sentiment analysis on tweets. The book uses kafka-console-producer and a sample .json file for the tweets, but for my app I wanted to read actual tweets. To do that I've been reading about Kafka Connect and looking at this repository, but I'm having a hard time understating how to best deploy this for my local setup. So far I've been using docker-compose.yml files provided by the book, which in turn uses Confluent's docker images for kafka, zookeeper, etc. As for this Twitter Connect repository, it seems the recommended way of setting it up is to use Confluent's platform and its CLI tool to automagically install it, which is fine, but I wanted to learn how things work under the hood (to some extend) and if possible not rely so heavily upon Confluent's software. Is it a good idea to just stick with Confluent and the book, or should I be reading a different material for a first Kafka project and working with a different kind of setup? Perhaps I'm getting ahead of myself trying to use Kafka Connect at this point?

I am working on a custom Kafka-Mongo sink connector (specifically, a custom WriteModelStrategy to be used with the official Mongo sink connector here: https://github.com/mongodb/mongo-kafka ). My code is not a standalone, executable Java application but rather a JAR that augments the functionality of another Java application.

To create a connection between MongoDB and Apache Kafka, MongoDB has build official framework MongoDB Kafka Connector.