Data Analytics with Python

Course Description

Course is lectured for AUCA students. The course is devoted to the practice of data analytics in the Python language. First of all, we will learn the basics of Python language in order to manage and analyze data. Then, we will learn the basics of data analytics, such as plotting graphs, pie charts, histograms. We will learn Python libraries such as Pandas, Numpy, SciPy and others. We will cover techniques in modern data analysis: estimation, regression and econometrics, prediction, experimental design, randomized control trials (and A/B testing), machine learning, and data visualization. We will illustrate these concepts with applications drawn from real world examples and frontier research. This course is oriented for social scientists.

Instructor: Ilias Suvanov

Note

There is no need to install Python to your local machine, you can directly use Python through Google Colab Service

Course metadata

Course schedule

Lectures and seminars will be held every Monday at 18:30 Bishkek time.

Course materials

Main materials are taken from:

  • Ben Stephenson - The Python Workbook: A Brief Introduction with Exercises and Solutions
  • Nicola Lacey - Python by Example: Learning to Program in 150 Challenges
  • Python documentation
  • Jake VanderPlas - Python Data Science Handbook: Essential Tools for Working with Data
  • Wes McKinney - Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
  • Joel Grus - Data Science from Scratch: First Principles with Python

Lectures/Seminars

Homework

Grading

Please refer to Gradebook for detailed and uptodate information on the grading.

  • Project Works - 40 points
  • Midterm - 10 points
  • Final - 20 points
Warning

Instructor reserves the right to require any course participant to sit for an individual oral examination (with turned on webcam and mic) before submitting the final grade to the registrar. Refusal to sit for an individual oral examination by a course participant, may result in failing the course. Instructor will notify potential course participants about the oral examination one week prior the course completion.