The goal of this 3-day workshop is to introduce data analysis with the Python programming language, and is aimed at beginners. We introduce how to work with different data structures in Python. We cover the most popular modules including Numpy, Scipy, Pandas, matplotlib, Seaborn, and ggplot for data analytics and visualization. This workshop is the first in the sequence of four workshops that make up Data Science for Analysts.
- WORKSHOP #1: Python for Data Analysis (3 days)
- WORKSHOP #2: Introduction to Machine Learning (1 day)
- WORKSHOP #3: Scaling Data Analysis with Spark (3 days)
- WORKSHOP #4: Enterprise Data Warehousing & Analytics with Hadoop and Tableau (3 days)
WHAT YOU’LL LEARN:
- Introduction to Python: Basic objects in Python, Variables and self-defining functions, control flow, and advanced data structures
- Deep dive with Python: Object-oriented programming, deal with files, run Python scripts, and handle and process strings
- Scientific computation tools – Understand and apply three modules for scientific computation that make Python as powerful as Matlab: numpy, matplotlib and scipy.
- Data Visualization – Generate graphics by using appropriate tools like Seaborn.
- Data manipulation with Pandas – Understand and apply provides rich data structures and functions designed to make working with structured data fast, easy, and expressive. The DataFrame object in pandas is just like the data.frame object in R. Pandas makes data manipulation (filter, select, group, aggregate, etc.) as easier as in R.
After this workshop, analysts/developers will get familiar with the Python language including object-oriented principles, understand the use of various packages for data wrangling and cleaning, and perform exploratory data analysis. Students should be able to take advantage of iPython notebook as a resource to demonstrate the results of code and code changes interactively.
Students will receive a digital certificate for display on their LinkedIn profiles with links back to the content and verification details to allow anyone to connect to their learning.
When & Where