You can do it this way:

UPDATE table_users
    SET cod_user = (case when user_role = 'student' then '622057'
                         when user_role = 'assistant' then '2913659'
                         when user_role = 'admin' then '6160230'
                    end),
        date = '12082014'
    WHERE user_role in ('student', 'assistant', 'admin') AND
          cod_office = '17389551';

I don't understand your date format. Dates should be stored in the database using native date and time types.

Try either multi-table update syntax

UPDATE config t1 JOIN config t2
    ON t1.config_name = 'name1' AND t2.config_name = 'name2'
   SET t1.config_value = 'value',
       t2.config_value = 'value2';

Here is a SQLFiddle demo

or conditional update

UPDATE config
   SET config_value = CASE config_name 
                      WHEN 'name1' THEN 'value' 
                      WHEN 'name2' THEN 'value2' 
                      ELSE config_value
                      END
 WHERE config_name IN('name1', 'name2');

Here is a SQLFiddle demo

UPDATE mytable SET
    fruit = CASE WHEN id=1 THEN 'orange' ELSE 'strawberry' END,
    drink = CASE WHEN id=1 THEN 'water'  ELSE 'wine'       END,
    food  = CASE WHEN id=1 THEN 'pizza'  ELSE 'fish'       END
WHERE id IN (1,2);

Personally, using CASE WHEN THEN END looks clumsy.

You could code this using the IF function.

UPDATE mytable SET
    fruit = IF(id=1,'orange','strawberry'),
    drink = IF(id=1,'water','wine'),
    food  = IF(id=1,'pizza','fish')
WHERE id IN (1,2);

Give it a Try !!!

CAVEAT : CASE WHEN THEN END is only handy when dealing with multiple values (more than 2)

You could use the MERGE statement which is in the SQL:2003 standard and available in Transact-SQL since SQL Server 2008:

MERGE mytable
USING (VALUES (23, 'FOD'),
              (47, 'ASD'),
              (83, 'FGH'),
              (88, 'JKL'),
              (92, 'QWE'),
              ( 9, 'BAR')) AS pairs(id2, data2)
     ON id = id2 
WHEN MATCHED 
     THEN UPDATE SET data = data2

The USING clause allows to specify a derived table using a table value constructor (See example under point D on that page).

Alternatively, the more commonly implemented SQL:92 standard syntax to do this would be:

UPDATE mytable
SET    data = 
       CASE id
            WHEN 23 THEN 'FOD'
            WHEN 47 THEN 'ASD'
            WHEN 83 THEN 'FGH'
            WHEN 88 THEN 'JKL'
            WHEN 92 THEN 'QWE'
            WHEN  9 THEN 'BAR'
       END
WHERE  id IN (23, 47, 83, 88, 92, 9);

The obvious downside is that you end up specifying the id values twice. You could do without the WHERE clause and add ELSE data in the CASE construct, but then you would actually update all rows, which is inefficient and may have undesired side-effects (via triggers).

update employee
set salary = 300
where [employee id] in (1,2,5)

or

update employee
set salary = 300
where [employee id] = 1
   or [employee id] = 2
   or [employee id] = 5

Couldn't find a SQL Server 2008 fiddle engine so I had to opt for a SQL Server 2014 ... so not sure if the following will work in SQL Server 2008, but fwiw ...

Setup some sample data:

create table Table1(id int, Date datetime null);
create table Table2(id int, Date datetime);

insert Table1 values (1,null)
insert Table1 values (1,null)
insert Table1 values (2,null)
insert Table1 values (2,null)
insert Table1 values (2,null);

insert Table2 values (1,'2013-01-29 08:50:00.000')
insert Table2 values (1,'2013-01-29 15:28:00.000')
insert Table2 values (2,'2013-01-31 11:56:00.000')
insert Table2 values (2,'2013-03-11 16:08:00.000')
insert Table2 values (2,'2013-01-31 14:04:00.000');

Keeping in mind that we haven't been provided (yet) with any means to determine which rows to match between Table1 and Table2 for a given id value, I'll just let row_number() generate a 'matching' rowid.

And then we'll make use of SQL Server's ability to update Table1 via a derived table definition:

update T1 
set    T1.Date=T2.Date

from   (select row_number() over(partition by id order by Date) as rowid,
               id,
               Date
        from   Table1 
        where  Date is NULL) T1

join   (select row_number() over(partition by id order by Date) as rowid,
               id,
               Date
        from   Table2) T2

on      T1.id    = T2.id
and     T1.rowid = T2.rowid;

And the results:

select * from Table1;

id  Date
--- --------------------
1   2013-01-29T08:50:00Z
1   2013-01-29T15:28:00Z
2   2013-01-31T11:56:00Z
2   2013-01-31T14:04:00Z
2   2013-03-11T16:08:00Z

And here's a SQL Fiddle for the above.

Remarks

It is possible to update rows based on some condition. It is also possible to update multiple tables in one statement in MySQL.

Whether the latter is a good idea is debatable, though. The target tables would be joined together for the update, and when I say "joined", I mean it in a broader sense: you do not have to specify a joining condition, in which case theirs would be a cross join. In a cross join, when at least one of the tables has more than one row, the other table will inevitably have its rows duplicated in the joined set. If both have multiple rows, both will have them multiplied. Somewhat counter-intuitively, MySQL will still update each affected row just once, yet I would refrain from multi-table updates in such scenarios, even if solely because of the counter-intuitiveness.

Method 1

Anyway, moving on to your specific example, there is indeed no joining condition, only a filter on each table. You can specify those filters in the WHERE clause of the UPDATE. Now in order to select which value to update each column with, you can use a CASE expression. This is what the complete UPDATE statement might look like:

UPDATE
  A, B
SET
  A.col1 = 'abc',
  A.col2 = 'xyz',
  B.col1 = CASE B.col3
             WHEN '1' THEN 'a'
             WHEN '2' THEN 'b'
             WHEN '3' THEN 'c'
           END,
  B.col2 = CASE B.col3
             WHEN '1' THEN 'x'
             WHEN '2' THEN 'y'
             WHEN '3' THEN 'z'
           END
WHERE
  A.col3 = '1'
  AND B.col3 IN ('1', '2', '3')
;

You can see that you have to repeat the same set of conditions in a CASE expression both for B.col1 and for B.col2. Is there a way to avoid that?

Method 2

Yes, there is. You can arrange the target values for B.col1 and B.col2 as well as the filtering values for B.col3 as a derived table and join it to B in the UPDATE clause, like this:

UPDATE
  A,
  B
    INNER JOIN
    (
      SELECT 'a' AS col1, 'x' AS col2, '1' AS col3
      UNION ALL
      SELECT 'b', 'y', '2'
      UNION ALL
      SELECT 'c', 'z', '3'
    ) AS fltr ON B.col3 = fltr.col3
SET
  A.col1 = 'abc',
  A.col2 = 'xyz',
  B.col1 = fltr.col1,
  B.col2 = fltr.col2
WHERE
  A.col3 = '1'
;

The join is also acting as a filter for B, so you can omit the one in the WHERE clause.

You can find a demo for each method at db<>fiddle:

• Method 1
• Method 2

Better way

Finally, as have been remarked both at the beginning of this post and in the comments, you can have a separate UPDATE statement for each table. The result would be clear in intention both to the reader of your script and to the database engine. A simpler script enables the latter to have more options for optimisation.

Use either of the methods above for the table B update, but do both tables separately:

UPDATE
  A
SET
  A.col1 = 'abc',
  A.col2 = 'xyz'
WHERE
  A.col3 = '1'
;

UPDATE
  B
    INNER JOIN
    (
      SELECT 'a' AS col1, 'x' AS col2, '1' AS col3
      UNION ALL
      SELECT 'b', 'y', '2'
      UNION ALL
      SELECT 'c', 'z', '3'
    ) AS fltr ON B.col3 = fltr.col3
SET
  B.col1 = fltr.col1,
  B.col2 = fltr.col2
;

There is also another reason for splitting the updates in separate statements. Since for a single UPDATE statement the tables need to be joined, it is important that both tables have rows intended for the update. If one table has no matching rows, then, even if the other does, neither will be updated. This is because an empty set cross-joined to a non-empty set still results in an empty set.

So, the single UPDATE statement would have no rows to work with if at least one table had no rows matching the condition(s). That would not happen with separate UPDATEs, because each would work with its own table regardless of the contents of the other, therefore, absence of rows in one table would not affect the update of the other.