input: def sentiment_analysis(tweets):
      """
      Classify positive and negative sentiment in tweets.
  
      >>> sentiment_analysis(['I love this product!', 'This is terrible, do not buy.'])
      ['Positive', 'Negative']
  
      >>> sentiment_analysis(['Life is great', 'Worst day ever'])
      ['Positive', 'Negative']
      """
output:     positive_keywords = ['love', 'great', 'awesome', 'happy', 'good']
      negative_keywords = ['terrible', 'worst', 'hate', 'bad', 'awful']
      
      result = []
      
      for tweet in tweets:
          tweet_lower = tweet.lower()
          if any(keyword in tweet_lower for keyword in positive_keywords):
              result.append('Positive')
          elif any(keyword in tweet_lower for keyword in negative_keywords):
              result.append('Negative')
          else:
              result.append('Neutral')
      
      return result