Week 7 : Supervised and Unsupervised Learning

Objectives

Understand the fundamental concepts and principles of data science, including data collection, preprocessing, analysis, and interpretation.
Gain familiarity with machine learning algorithms and their practical applications.
Develop proficiency in using data science tools and programming languages.
Engage in critical thinking and problem-solving through project-based assignments.
Explore the ethical considerations associated with data-driven decision-making.
Stay informed about current trends and developments in data science and artificial intelligence.

Explain the difference between different measures of centrality and variability (means vs. medians, variance vs. interquartile range, etc.)
Convert a raw data source into a version appropriate for downstream analysis using Python. | Week 4 & 5 .. cont to 7
Select the appropriate evaluation measure for the dataset and task being solved
Articulate the difference between supervised and unsupervised machine learning, as well as select the appropriate methodology for a given problem | Week 6 .. cont to 7
Demonstrate awareness of bias and ethics in data science.

Weekly Checkin for Week 6 | Due 5 pm , July 23, Sunday ( Based on Lecture 6.1,6.2,6.3 )
Weekly Checkin for Week 7 opens