From the many questions you posted already, I see you have tried different things, when people seem to suggest you do something, you just open another question.

Let's try this again.

Step 1) Download this package: http://sourceforge.net/projects/bowtie-bio/files/bowtie2/2.2.4/bowtie2-2.2.4-mingw-win64.zip/download

Step 2) Unzip it. Place it in a folder you can navigate to, something simple, such as C:\bowtie2_win64

Step 3) Assuming you have windows 7 (you should say what operating system you are using), open "cmd.exe", this is command prompt, you can open it by pressing WindowsKey+R and typing cmd.exe + enter

Step 4) In command prompt (black windows), navigate to where you have unzipped your bowtie, in Step2 I told you to put it in C:\bowtie2_win64, so write in command prompt cd C:\bowtie2_win64.

Now you need to test whether the precompiled windows binary works for you, so:

Step 5) Index example fasta file, type bowtie2-build-s.exe example/reference/lambda_virus.fa lambda_virus

Step 6) If all goes well, next you need to align the sample reads provided bowtie2-align-s.exe -x lambda_virus -U example/reads/reads_1.fq -S eg1.sam

If all went well, you should see:

10000 reads; of these:
  10000 (100.00%) were unpaired; of these:
    596 (5.96%) aligned 0 times
    9404 (94.04%) aligned exactly 1 time
    0 (0.00%) aligned >1 times
94.04% overall alignment rate

And if all went well, you are ready to try it on your own data.

As Adrian has said above, you should really use a linux environment to do this kind of analysis. It would also make installing software easier.

Bio-Linux is a linux environment and has bioinformatics software already installed so you can download it to a usb, put it in your computer and start doing bioinformatics. It won't change your computer, unless you decide you want to install it permanently.

You can get it here: http://environmentalomics.org/bio-linux/

There is also full documentation on using the linux environment and running bioinformatics programs (there's not an RNA-seq section, but the genome assembly section would probably be useful).