input: Write a function to pre-process natural language data by removing stopwords using nltk.
  assert process_data("This is a simple test case for nltk processing.") == ['This', 'simple', 'test', 'case', 'nltk', 'processing', '.']
  assert process_data("Natural Language Processing with Python and nltk.") == ['Natural', 'Language', 'Processing', 'Python', 'nltk', '.']
  assert process_data("Can we remove all the stopwords effectively?") == ['Can', 'remove', 'stopwords', 'effectively', '?']
output: def process_data(text):
      import nltk
      from nltk.corpus import stopwords
      from nltk.tokenize import word_tokenize
      
      nltk.download('punkt')
      nltk.download('stopwords')
      
      stop_words = set(stopwords.words('english'))
      
      word_tokens = word_tokenize(text)
      filtered_sentence = [word for word in word_tokens if word.lower() not in stop_words]
      
      return filtered_sentence