Python Tutorials for Beginners

Introduction to Python, Anaconda 3 and Jupyter Notebook
Rating: 4.0 out of 5 (7 ratings)
750 students
English
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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

Requirements

  • No programming experience needed. You will learn everything you need to know

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.

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

Who this course is for:

  • IT Fresh Graduates
  • Data Scientist Beginners

Instructor

BI Developer
Arthur Fong
  • 4.1 Instructor Rating
  • 28 Reviews
  • 1,497 Students
  • 9 Courses

I have been in BI Industry for 4 years. In my past experience, I have being with a Qlik partner organization which helped me in gaining experience on developing some of the Qlik products, namely QlikView, Qlik Sense, and NPrinting. And I would like to share my knowledge as a developer with everyone here. Hopefully you will find my class informative for your learning.