Week 3 : Data Collection and Data Processing, Exploratory Analysis
Objectives
Course Objectives:
- Understand the fundamental concepts and principles of data science, including data collection, preprocessing, analysis, and interpretation.
- Apply data analysis and visualization techniques to derive insights from diverse datasets.
- Develop proficiency in using data science tools and programming languages.
- Explore the ethical considerations associated with data-driven decision-making.
Learning Outcomes:
- Convert a raw data source into a version appropriate for downstream analysis using Python.
- Demonstrate awareness of bias and ethics in data science.
Lectures
3.2 - Data Collection (Part 1 of 2)
3.3 - Data Collection (Part 2 of 2) & Data Processing (Part 1)
Activities
Homework
Weekly Checkin
- Weekly Checkin for Week 2 : Due 5 pm, June 25th, Sunday.
- Weekly Checkin for Week 3 : Due 5 pm, July 2, Sunday
Summary ( Plan versus Achievements):
- Strikethrough text is changes in plan.
- Green is new items added after planning.
- Checked boxes are completed items.
Week 3 ( June 18 to June 25 June 27)
Lectures
Topic: Statistics and Probability - Lecture 4 (Part 2)Will continue in Week 8- Lecture 2.x.1 Binomial Distribution
- Topic: Data processing and exploratory Analysis ( 2 or 3 Lectures ):
- 3.1 - Introduction to Pandas
- 3.2 - Data Collection (Part 1 of 2)
- 3.3 - Data Collection (Part 2 of 2) & Data Processing (Part 1)
Homeworks
- Homework 1 due
June 25June 26, 5 pm- Homework 1 Question 3.2 dropped.
Weekly Check-in
- Check-in for week 2 is due on June 25, 5 pm.
- Check-in for week 3 opens.
Assigned Reading
- Week 3’s assigned reading will be announced and available on D2L on or before Monday.