Python 102: Introduction to Data Analysis

Stack Overflow data indicates the increasing use of Python. Possibly spurred by its data science friendliness - a couple decades worth of scientific packages have made Python an incredibly productive and versatile.

This beginner course will guide you through the core libraries in PyData ecosystem: Numpy, Pandas, and matplotlib(optional). By taking the course, you will be familiar with the fundamental data analysis methods in Python using NumPy and Pandas.

What you will learn:

• Understand the data analysis ecosystem in Python.

• Learn how to use the pandas data analysis library to analyze data sets

• Analyze real datasets to better understand techniques for data analysis

• Create basic plots of data using MatPlotLib (bonus)

Course Syllabus:

Part 1 Python Data Analysis Libraries

• Data Analysis Components

• Data Analysis Steps

• Python Data Analysis Libraries

Part 2 Numpy Overview

• Array

• Functions

• Selecting and Slicing ,Filtering Array

• Transforming Array

Part 3 Data Analysis with Pandas

• Data structure

• Import/Export Data - CSV, Excel, Internet

• Data cleaning

• Data manipulation

Part 4 Data Visualization with Matplotlib & Seaborn(bonus)

Who Should Attend?

• Those are interested in learning data analysis.

• Analysts who want to better understand a technical approach to analyzing data.

Prerequisites

• Students should know how to run, at a minimum, basic program in python.

About the Instructor:

Ocean Li Haiyang has 7 years’ of experience writing Python code. Currently working as a software engineer in an investment bank, he helps to build the corporate in-house risk management system. To meet the requirements of the front office user, the job entails trade capturing, risk & regulation reports generation/automation, market data retrieving, time series analysis and visualization. As a senior developer, he is also required to teach Python Foundations to junior developers.