Welcome to Introduction to Data Science page. This lecture will be given by Assoc.Prof.Dr.Tugba Taskaya Temizel. The assistant who will be doing the applied portion of the course is Mehmet Ali Akyol.
This page will contain the lab codes for the class as RMarkdown documents. You can go to the Github repository for the full Rmarkdown files to use in your local environment.The entirety of materials will be available through ODTU-Class. This blog only aims to provide a collection of rendered RMarkdown files.
The syllabus for this year’s lecture is as follows:
- Week 1: Introduction to Data Science: Basic Concepts
- Week 2: Platforms & Workbenches
- Week 3: Probability & Statistics Review
- Week 4: Understanding Data: Exploratory Data Analysis
- Week 5: Understanding Data: Descriptive Analytics & Visualization
- Week 6: Data Acquisition and Preprocessing: Part I
- Week 7: Data Acquisition and Preprocessing: Part II
- Week 8: Practical Machine Learning: Part I
- Week 9: Practical Machine Learning (ML): Part II
- Week 10: Model Evaluation and Performance Metrics
- Week 11: Data Storytelling
- Week 12: Current Topics in Data Science: Part I – Big Data, ML Advance Topics & Data Mining
- Week 13: Current Topics in Data Science: Part II – Prescriptive Analytics & Decision Support Systems
- Week 14: Data Driven Organizations, Ethics and Legal Issues in Data Science
The contents for the applied portion are as follows: