Introduction to Data Science

Over the decades, data science has been the major field of study for building data analytics solutions.  In recent years, with the advent of Big Data, it has become the central approach to deal with data-heavy problems in both business and other sectors such life science. It is essential to develop an intensive understanding of a complex ecosystem of tools and platforms, as well as the communication skills that are necessary to explain advanced analytics. This is an introductory course of data science which covers a comprehensive overview of data science with a specific focus on introducing different techniques and technologies of data science for building and implementing analytical models for extracting knowledge from data. This course will articulate the statistical and mathematical foundations that power the data-scientific approach to problem solving.

Course Objectives

  • Describe the history and context of data science.
  • Explain the fundamental concepts of data science.
  • Describe different data science process models and provide an understanding how to use these models.
  • Explain statistical and machine learning techniques for building data analytics model.
  • Evaluate the utility of the models against requirements, and their trade-offs
  • Provide the landscape of relevant systems.

What is in it for the Participants?

  • Gaining an understanding of data science process models and an ability to apply these models to design and develop an analytics.
  • Gaining an understanding of machine learning and statistical techniques.
  • Gaining knowledge of the usage of ML and statistical techniques.
  • Being familiar with the process of using machine learning or statistical methods to create a model for business problems.
  • Learning data science relevant technologies and their usage.
  • Being able to provide basic guidelines to a data science team and communicate with the team members.