Ementorhub

What you'll learn

Know how to operate software that will help you create and run Python code.

Execute Python code for wrangling data from different structures into a Pandas dataframe structure.

Run and interpret fundamental data analytic tasks in Python including descriptive statistics, data visualizations, and regression.

Use relational databases and know how to manipulate such databases directly through the command line, and indirectly through a Python script.

Skills you'll gain

Seaborn

Data Processing

Matplotlib

Databases

Accounting

Data Visualization Software

Data Manipulation

Business Analysis

Jupyter

Programming Principles

Statistical Machine Learning

Descriptive Statistics

Relational Databases

NumPy

SQL

Pandas (Python Package)

Regression Analysis

Python Programming

Data Structures

Data Modeling

There are 9 modules in this course

The first half of the course picks up where Introduction to Accounting Data Analytics and Visualization left off: using in an integrated development environment to automate data analytic tasks. We discuss how to manage code and share results within Jupyter Notebook, a popular development environment for data analytic software like Python and R. We then review some fundamental programming skills, such as mathematical operators, functions, conditional statements and loops using Python software. The second half of the course focuses on assembling data for machine learning purposes. We introduce students to Pandas dataframes and Numpy for structuring and manipulating data. We then analyze the data using visualizations and linear regression. Finally, we explain how to use Python for interacting with SQL data.

Module 1: Foundations

Module 2: Introduction to Python

Module 3: Introduction to Python Programming

Module 4: Python Programming

Module 5: Data Analysis With Python

Module 6: Introduction to Visualization in Python

Module 7: Production Data Analytics

Module 8: Introduction to Databases in Python