Final Exam: Raw Data To Insights

WHAT YOU WILL LEARN

• 

  Identify key advantages of using computer vision in predictive analytics pipelines
  

  identify key advantages of using nlp techniques in predictive analytics pipelines
  

  describe the prospects of predictive analytics alongside its most promising fields of study
  

  describe broadly how a neural network works
  

  specify the role of deep learning and artificial neural networks when dealing with data
  

  describe the role of data science and data analysis in modern business
  

  name the steps and processes essential to any data science project
  

  specify the business perspective in relation to data analysis and predictive modeling
  

  list the processes essential to preparing data and specify their role
  

  describe how descriptive analysis can be used to drive business decision making
• 

  define key characteristics and requirements for the data collection pipeline
  

  describe the purpose of the data validation process and name major steps in data validation
  

  specify several ways to clean the dataset and describe why data cleaning is necessary
  

  describe how good visualization of data can become a key business driver
  

  name advanced visualization techniques and describe their use cases
  

  name and define major types of machine learning used in business management
  

  describe broadly how a machine learning algorithm works
  

  compare the roles of machine learning engineers and data scientists
  

  define and compare data science, data analytics and machine learning and their use cases for business management
  

  name the association rules used in data mining and specify their roles