As others said in the comments above, pass all bam files to featureCounts, then its output will contain all counts in one file, which is simpler to parse. However, there should be no differences in counts, regardless you pass one file at a time or all files together.
I don't understand which differences between your and the tutorial counts are puzzling you: 1) the actual counts; 2) the column names; 3) the missing length column.
The actual counts are different because you and the tutorial are analysing different data sets: cancer cell lines (C33A and HeLa) versus "basal stem-cell enriched cells (B) and committed luminal cells (L) in the mammary gland of virgin, pregnant and lactating mice". By the way, are you using a human or mouse reference genome?
Column names can be easily changed with
colnames( seqdata ) <- c( "name1", "name2", "name3" ).
And the length column can be additionally parsed from the featureCounts output file.