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Introduction to Python, Anaconda 3 and Jupyter Notebook

What you will learn

Downloading and Installing Anaconda 3 for Python

Hands on pythonic commands with Jupyter Notebook

Introduction to Python Pandas Data Science library kit

Introduction to Data structures in Python

Description

Today, we are all surrounded with full of data.

Data can be in the form of structured data(eg: Tables, worksheets), or unstructured data (free text fields or comments from social media).

Data can be also in the form of a bi-product that is produced during day-to-day transactions.

For example, when we are buying something from supermarkets, we are being issued a resit upon payment. The resit is a bi-product as our intention is not to collect the resit but to retrieve all the goods that we purchased from the supermarket. If we take a look at the resit, it has sufficient data as evidence that we bought the specific product from the supermarket. It has all the required data to perform a return when the product bought has defects. It has the date purchased, the location of the store, and the list of products, unit cost, and quantities that have been purchased.

The question is:

1. How can we further increase our revenue with the data that we have?

2. How can we predict customer purchasing behavior?

3. How can we know what are all the necessary products that the customer would buy if they had purchased a certain product?

Data is the core of an AI model, which utilizes data input for the model to train, test, and learn from the data.

The usage of Machine Learning has allowed computers to perform predictions and provides suggestions to humans based on the data input that has been fed into the machine.

The AI Model would predict what is the next purchase of the customer, based on the data that has been fed into the model.


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Join now to know more about Python as a basic step towards Data Science.

The Objective of the course:

To provide a very understanding of the basic functionality of Python.

Learning Outcomes:

1. How to install and configure Python.

2. Python Function and Class Objects.

3. Data Types – String and Numeric.

4. Python Data Structure – List and Data Dictionary.

Python Tutorials, Anaconda 3, Jupyter Notebook, Python 3

English
language

Content

Introduction
Welcome Aboard!
What is Python?
Downloading and Installing Python
Python Function, Class & Data Structures
Creating a New ipynb file
Defining Functions
Extending Functions with Keyword Arguments
Class Objects
List
List – Append vs Extend
Numeric List
Dictionary
Converting List to Dictionary
Introduction to Python Pandas
Importing Pandas
Removing Columns
Column Transformation
Row Transformation : Apply Lambda
Groupby : Agg
Conclusion
Thanks for Enrolling!
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