diff --git a/notebooks/src/301-priprava_pregled.ipynb b/notebooks/src/301-priprava_pregled.ipynb
index 31af8aa..4742e59 100644
--- a/notebooks/src/301-priprava_pregled.ipynb
+++ b/notebooks/src/301-priprava_pregled.ipynb
@@ -65,28 +65,24 @@
       "source": [
         "### Podatki\n",
         "\n",
-        "V nalogi boste pregledali in pripravili podatke gledanosti Hollywoodskih filmov\n",
-        "zbirke [MovieLens](https://grouplens.org/datasets/movielens/) v obdobju **1995-2016**.\n",
+        "V nalogi boste pregledali in pripravili podatke gledanosti filmov zbirke [MovieLens](https://grouplens.org/datasets/movielens/).\n",
         "\n",
-        "Iste podatke boste uporabili v vseh nalogah, zato jih dodobra spoznajte. Gre za podatkovno zbirko za\n",
-        "vrednotenje priporočilnih sistemov, ki vsebuje gledalce ter njihove ocene za posamezni film na lestvici 1 do 5. \n",
-        "Poleg osnovne matrike uporabnikov in ocen vsebuje še dodatne podatke o filmih (npr. žanr, datum, oznake,\n",
-        "igralci).\n",
+        "Iste podatke boste uporabili v vseh nalogah, zato jih dodobra spoznajte. Gre za podatkovno zbirko za vrednotenje priporočilnih sistemov, ki vsebuje gledalce ter njihove ocene za posamezni film na lestvici 1 do 5. \n",
+        "Poleg osnovne matrike uporabnikov in ocen vsebuje še dodatne podatke o filmih (npr. žanr, datum, oznake, igralci).\n",
         "\n",
-        "Podatki so v mapi `./podatki/ml-latest-small`. Podatkovna zbirka vsebuje naslednje datoteke:\n",
+        "Podatke poberite [s spleta](https://files.grouplens.org/datasets/movielens/ml-32m.zip) in jih odpakirajte v mapo `./data`, kjer vas že čaka datoteka `cast.csv`. Podatkovna zbirka vsebuje naslednje datoteke:\n",
         "\n",
         "* ratings.csv: podatki o uporabnikih in ocenah,\n",
         "* movies.csv: podatki o žanrih filmov,\n",
         "* cast.csv: podatki o igralcih,\n",
-        "* tags.csv: podatki o oznakah (ang. \\emph{tags}),\n",
+        "* tags.csv: podatki o oznakah (ang. *tags*),\n",
         "* links.csv: povezave na sorodne podatkovne zbirke.\n",
         "\n",
+        "Pred pričetkom reševanja naloge si dobro oglejte podatke in datoteko **README.txt**. \n",
         "\n",
-        "Pred pričetkom reševanja naloge si dobro oglejte podatke in datoteko **README.txt**. Podrobnosti o zbirki lahko preberete na [spletni strani](http://files.grouplens.org/datasets/movielens/ml-latest-small-README.html).\n",
+        "Pripravite metode za nalaganje podatkov v ustrezne podatkovne strukture. Te vam bodo prišle prav tudi pri nadaljnjih nalogah.\n",
         "\n",
-        "Pripravite metode za nalaganje podatkov v ustrezne podatkovne strukture. Te vam bodo prišle\n",
-        "prav tudi pri nadaljnjih nalogah.\n",
-        "Bodite pozorni na velikost podatkov."
+        "Podatkov **NE** nalagajte na svoje repozitorije"
       ]
     },
     {
@@ -99,26 +95,24 @@
       "source": [
         "### Data\n",
         "\n",
-        "In the task you will review and prepare Hollywood movie ratings from\n",
-        "the [MovieLens](https://grouplens.org/datasets/movielens/) collection from the period **1995-2016**.\n",
+        "In the task you will review and prepare movie ratings from the [MovieLens](https://grouplens.org/datasets/movielens/) collection.\n",
         "\n",
-        "The same data is used in all assignments, so you should get to know the data well. This is a database for\n",
-        "evaluating recommendations systems that include viewers and their ratings on a scale of 1 to 5.\n",
-        "In addition to the basic user and rating matrix, it includes also movie information (e.g., genre, date, tags, players).\n",
+        "The same data is used in all assignments, so you should get to know the data well. This is a dataset for evaluating recommendations systems that include viewers and their ratings on a scale of 1 to 5.\n",
+        "In addition to the basic user and rating matrix, it includes also movie information (e.g., genre, date, tags, actors).\n",
         "\n",
-        "The dataset is in folder `./podatki/ml-latest-small`. The database contains the following files:\n",
+        "Download the dataset [from the web](https://files.grouplens.org/datasets/movielens/ml-32m.zip) and unpack it in the folder `./data`, where you already have the file `cast.csv`. The dataset contains the following files:\n",
         "\n",
         "* ratings.csv: user data and ratings,\n",
         "* movies.csv: movie genre information,\n",
-        "* cast.csv: player information,\n",
-        "* tags.csv: tag information (\\emph{tags}),\n",
+        "* cast.csv: actors information,\n",
+        "* tags.csv: tag information,\n",
         "* links.csv: links to related databases.\n",
         "\n",
         "Before starting to solve the task, take a good look at the data and read the **README.txt** file. You can learn about the details on the [website](http://files.grouplens.org/datasets/movielens/ml-latest-small-README.html).\n",
         "\n",
-        "Prepare methods for loading data into the appropriate data structures. They will come in handy\n",
-        "also for further tasks.\n",
-        "Pay attention to the size of the data."
+        "Prepare methods for loading data into the appropriate data structures. They will come in handy also for further tasks.\n",
+        "\n",
+        "**Don't** uplod the data to you repositories."
       ]
     },
     {