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

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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!