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Quick Facts

Medium Of Instructions	Mode Of Learning	Mode Of Delivery
English	Self Study	Video and Text Based

Course Overview

The Accounting Data Analytics with Python Programme by Coursera has been developed for the candidates who are looking to build proficiency in the Python language, especially for business intelligence and analytics. Provided in partnership with the University of Illinois, the programme aims to utilize Python’s robust computational capabilities and libraries. It focuses heavily on working with multiple domains of accounting data, be it EDGAR financial statement data, stock data, or point-of-sale data.

The Coursera Accounting Data Analytics with Python Training covers fundamental Python programming skills like functions, conditional statements, loops, and mathematical operators. Moreover, since the course is a part of UIUC’s Master of Business Administration Degree, a greater emphasis is placed on data visualization and presentation. Furthermore, certification training also covers data structuring and manipulation, along with Python and SQL integration.

Lastly, the Accounting Data Analytics with Python Training Course is a 100 percent online learning experience that allows you to learn and train at your convenience. Along with the video lectures, you will have a collection of reading material carefully curated by Coursera at your disposal. Upon course completion, you will receive an industry revered Coursera Certificate.

The Highlights

Shareable Certificate
100% online
Flexible deadlines
Intermediate Level
Free enrolment
Approx. 41 hours to complete

Programme Offerings

Self Paced Online Learning
community forum
Course completion certificate
lifetime access to course material

Courses and Certificate Fees

Certificate Availability	Certificate Providing Authority
yes	Coursera

You can opt for Accounting Data Analytics with Python course free of cost if you choose the option of auditing the course during application. Some content, like graded tests and lessons, may be locked if you audit the course. Also, you won’t receive the course completion certificate while auditing the course. To unlock such content, you need to purchase the course.

Accounting Data Analytics with Python Fee Structure:

Course	Fees in INR
1 Month	Rs. 6,451 (plus GST)
3 Months	Rs. 12,903 (plus GST) ₹4,301/month
6 Months	Rs. 19,354 (plus GST) ₹3,226 /month

Eligibility Criteria

You need to pass all the assigned tasks in the curriculum or secure a cumulative graded course passing threshold to earn a Coursera certificate for the Accounting Data Analytics with Python Programme. In addition, you need to buy a subscription. The deadline to earn the certification is 180 days, and failing to do so means you will have to buy the course for certification again.

What you will learn

Knowledge of PythonSQL knowledgeKnowledge of Data Visualization

On completion of the Accounting Data Analytics with Python Training Course, you will have:

Comprehensive knowledge of the Python fundamentals, data types, loops, and its various use cases in the field of accounting
Proficiency in writing Python code and visualizing one- and two-dimensional data using libraries such as Matplotlib and Seaborn
Mastery in working with Pandas Dataframe to read and save Dataframes, filter functions, apply pivot table functions, and calculate descriptive statistics
Knowledge of working with SQL data in Python
Expertise in manipulating and structuring data using Python Libraries like NumPy and Pandas
Expertise in creating and utilizing a group of functions, which are also known as modules
Working knowledge of creating and interacting with relational databases (RDBMS) in Python

Who it is for

Data AnalystData ScientistMarket Research AnalystQuantitative AnalystPython ProgrammerData Engineer

Admission Details

To enroll in the Accounting Data Analytics with Python course follow these steps:

Visit the Course page.
When the page opens, log in through your credentials, or Google or Facebook account
On the top left, you’ll find the “Enroll for free” button. Click on it.
Make a choice between Purchase Course and Audit only options
Auditing the course will take you to course lessons. If you choose the “Purchase course” option, it will take you to a payment gateway. Make the payment and open the course.

Application Details

To join the Accounting Data Analytics with Python Programme by Coursera, sign up on Coursera with your Facebook/Google account. Access the free to audit option to view the course material. Enroll in the course for free and then upgrade to view graded assignments and to earn a course certificate.

The Syllabus

Videos

Course Introduction
About Ronald Guymon
About Linden Lu
Learn on Your Terms

Readings

Syllabus
Glossary
About the Discussion Forums
Learn More About Flexible Learning Paths
Update Your Profile

Videos

Module 1 Introduction
1.1 Introduction to Data Analytics
1.2 Jupyter Notebook
Python and Integrated Development Environments (IDEs)
Installing and Running Python Using the Anaconda Distribution
Installing and Running Python Without Anaconda
Navigating Jupyter Notebook
Navigating JupyterLab
Using Notebook Files
Navigating Spyder
Comparison of Jupyter Notebook, JupyterLab, and Spyder
1.3 Introduction to Markdown
Markdown Basics
Module 1 Review

Readings

Module 1 Overview and Resources
Lesson 1.1 Readings

Practice Exercise

Module 1 Quiz

Videos

Module 2 Introduction
2.1 Introduction to Python
Python Code Basics
Variables, Data Types, and Operators
2.2 Introduction to Python Functions
Built-In Functions
User-Defined Functions
Functions vs Methods
2.3 Conditional Statements in Python
Comparison and Logical Operators
Working with Conditional Statements
Module 2 Review

Reading

Module 2 Overview and Resources

Practice Exercise

Module 2 Quiz

Videos

Module 3 Introduction
3.1 Introduction to Python Data Structures
Introduction to Strings
Introduction to Lists
Introduction to Dictionaries, Tuples, and Unpacking
Common Sequence Operations
3.2 Working with Python Data Structure
Working with Strings
Working with Lists and Tuples
Working with Dictionaries
3.3 Introduction to Python Loops
The For Loop1
The While Loop
Comprehensions
Module 3 Review

Reading

Module 3 Overview and Resources

Practice Exercise

Module 3 Quiz

Videos

Module 4 Introduction
4.1 Writing Python Programs
Python Modules
Errors and Exceptions
4.2 Introduction to NumPy
NumPy Array
NumPy Basic Functions
4.3 Introduction to Pandas
Introduction to Dataframes
Data Selection with Dataframes
Missing Values and Copies with Dataframes
Module 4 Review

Reading

Module 4 Overview and Resources

Practice Exercise

Module 4 Quiz

Videos

Module 5 Introduction
5.1 Python File IO
Reading and Writing Files with Base Python
Reading and Writing Files with Pandas
Preserving Data Types with Pickling
5.2 Working with the Pandas DataFrame
Exploring Dataframes
Copying and Sorting Dataframes
Changing Column and Row Names of Dataframes
Grouping and Aggregating with Dataframes
Stacking and Pivoting Dataframes
5.3 Introduction to Descriptive Statistics
Descriptive Statistics for Dataframes
Module 5 Review

Reading

Module 5 Overview and Resources

Practice Exercise

Module 5 Quiz

Videos

Module 6 Introduction
6.1 Introduction to Plotting with Python
Introduction to Plotting with Pandas
More on Plotting with Pandas
Introduction to matplotlib
More on Plotting with matplotlib
Introduction to Plotting with Seaborn
6.2 Introduction to One-Dimensional Data Visualization
Introduction to Seaborn Histograms
Introduction to Seaborn Box Plots
Introduction to Seaborn Bar Plots
6.3 Introduction to Two-Dimensional Data
Introduction to Scatter Plots
Introduction to Pair Plots
Introduction to Joint Plots
Module 6 Review

Reading

Module 6 Overview and Resources

Practice Exercise

Module 6 Quiz

Videos

Module 7 Introduction
7.1 Introduction to CRISP-DM
7.2 Introduction to Data Preparation Techniques
Pandas Functions to Load Data
Fill in Missing Values with Conditional Means
Manipulating String Columns of a Dataframe
Creating Datetime Values
Split, Apply Combine and More on Datetimes
Lambda Functions
7.3 Linear Regression in Python
Setting up Data for Regression
Creating a Simple Regression Model
Predicting with a Regression Model
Multiple Regression Model
Categorical Variables in Regression
Module 7 Review

Reading

Module 7 Overview and Resources

Practice Exercise

Module 7 Quiz

Videos

Module 8 Introduction
8.1 Introduction to Data Persistence
Introduction to Terminal
Creating a SQLite Database From Terminal
Creating a SQLite Table From a CSV File
Using Dump and Reading in Files to Create Tables
Altering Existing SQLite Tables
8.2 Advanced Concepts
Querying Tables with SQL
SQL Join Queries
8.3 Python Database Programming
Querying Relational Database with Python and SQL
Exploring Databases and Adding Rows to Tables with Python
Module 8 Review
Gies Online Programs

Readings

Module 8 Overview and Resources
Congratulations!
Get Your Course Certificate

Practice Exercise

Module 8 Quiz

Instructors

University of Illinois, Urbana Champaign Frequently Asked Questions (FAQ's)

1: What is the need for Analytics in Accounting?

Analytics can be applied in Accountings to reveal valuable insights, identify avenues to improve and increase a company’s efficiency, and most importantly, manage risks.

2: From when can I access the lectures and assignments?

It entirely depends upon your type of enrollment. Candidates who have opted for auditing the course, might not be able to access some of the course material. They ended up purchasing the certificate to get complete access.

3: What will I get on purchasing the certificate?

If you purchase the certificate, you will get access to all course elements of the Accounting Data Analytics with Python training. Upon successful course completion, you will be awarded a certificate, which will adorn your Coursera accomplishment page. Since the certificate is printable and shareable, you can add it to your LinkedIn profile, CVs, and resume with ease.

4: How can I get financial aid?

Students who can’t afford to pay the course fee get the option of financial aid. They have to apply for the aid by clicking on an option that’s next to the ‘Enroll’ button, fill up the application, and wait for the approval.