input: def sentiment_analysis(tweets: List[str]) -> List[str]:
      """ Analyze the sentiment of given tweets and classify them as 'Positive' or 'Negative'.
      >>> sentiment_analysis(['I love this!', 'I hate this.'])
      ['Positive', 'Negative']
      >>> sentiment_analysis(['What a beautiful day', 'Everything is awful'])
      ['Positive', 'Negative']
      """
output:     positive_words = {'love', 'beautiful', 'great', 'awesome', 'happy'}
      negative_words = {'hate', 'awful', 'terrible', 'bad', 'sad'}
      
      result = []
      for tweet in tweets:
          words = set(tweet.lower().split())
          if positive_words.intersection(words):
              result.append('Positive')
          elif negative_words.intersection(words):
              result.append('Negative')
          else:
              result.append('Neutral')
      
      return result