Explore the Exciting World of Data Science

Enroll in this training and receive a one-month complimentary e-learning subscription with access to 40+ courses.

This course is provided by Big Data Trunk for Stanford Technology Training Program but a limited few seats available to the public.

Students of this class may have opportunity to be considered for Internship with Big Data Trunk.
This lecture will give a broad overview of Data Science. We will clarify the relationship between Data Science and Machine Learning and explore the Data Science process.
In this session, we will talk about identifying an effective data analysis question that is actionable, and how to get the right data to answer the question. We will discuss data exploration and the importance of clean data, complete data, and the quantity and variety of data. We will also cover how to effectively apply and evaluate Machine Learning models.
The lecture will briefly demonstrate how to work through a Data Science project using Pandas and Scikit-learn, highlighting the variety of choices that need to be made throughout the process that determines its success.
Structured Activity/Case Studies:
Demonstration -- the Data Science process using pandas and scikit-learn

Learning Objectives

• Understand the relationship between Data Science and Machine Learning
• Become familiar with the Data Science process
• Identify effective data analysis questions that are actionable
• Identify effective data sources
• Understand the importance of clean, complete, and quantity of data
• Understand how Machine Learning is applied and evaluated within the Data Science process
• Become familiar with some of the tools used throughout the process

Topic Outline

• Introduction to lecture
• Data Science vs. Machine Learning
• The Data Science process
• The importance of data
• Exploring and transforming data
• Creating and evaluating Machine Learning models
• Developing an effective Data Science strategy
• Demonstra