Introduction to Data Science

Welcome to Intro to Data Science! You are joining a global learning community dedicated to helping you learn and thrive in data science.

Course Description

Data science is applicable to a myriad of professions, and analyzing large amounts of data is a common application of computer science. This course empowers students to analyze data, and produce data-driven insights. It covers the foundational suite of concepts needed to solve data problems, including preparation (collection and processing), presentation (information visualization), and analysis (statistical and machine learning).

Data analysis requires acquiring and cleaning data from various sources including the web, APIs, and databases. As a student, you will learn techniques for summarizing and exploring data with tools like Spreadsheets, Google Colab, and Pandas. Similarly, you'll learn how to create data visualizations using Power BI and Seaborn, and practice communication with data. Likewise, you'll be introduced to machine learning techniques of prediction and classification, and explore Natural Language Processing (NLP). Lastly, you'll learn the fundamentals of deep learning, which will prepare you for advanced study of data science.

Throughout the course, you will work with real datasets and attempt to answer questions relevant to real-life problems.

Course Objectives

At the end of the course, student should be able to:

  • Explain the basics of data science, its relevance, and applications in 21st century.
  • Describe various data collection and cleaning techniques, using necessary tools.
  • Apply different visualization tools to generate insights that drive business decisions.
  • Demonstrate understanding of machine learning concepts, and its application to real-world problems.

Instructor

Live Class Time

Note: all times are shown in GMT.

  • Wednesday at 3:00 PM - 4:30 PM GMT

Office Hours

  • Thursday at 2:00 - 3:00 PM GMT