Just dig into a bit more in the google, there are multiple instances that show how to run cufflinks on your aligned bam files. Check the below links
There are different output files for cufflinks run. The genes.fpkm_tracking should be the one you should be looking for. When you run cufflinks on your bams at the end for each of your samples you will have a genes.fpkm_tracking file. You can then write a script to fetch out the fpkm for all the genes across all your samples to generate a FPKM matrix which you can farther utilize for your visualization. Note: Never perform any statistics on FPKM. Your differential expression will be done on counts by cuffdiff.
However there are now some amazing fast methods like Salmon/Kallisto or even STAR which will provide you will read counts and TPM(transcripts per million- normalized counts slowly replacing FPKM). You can use the read counts formulate matrix for your samples and feed them to edgeR/DESeq2/limma for differential expression analysis. While the TPM data will behave as alternative to FPKM for visualization. Embrace the change and evolution of the RNA-Seq world and better get acquanted to it. Good luck!