Fundamentals of Python for Data Mining

Want to learn data mining with Python? This course offers fundamentals of Pythons with examples and than data mining.

3.55 (16 reviews)
Udemy
platform
English
language
Data Science
category
instructor
2,250
students
3 hours
content
Jun 2018
last update
$19.99
regular price

What you will learn

Python fundamentals, using Python libraries for data mining (pandas, scipy, matplotlib, ...)

Description

Why learn Data Analysis and Data Science?


According to SAS, the five reasons are


1. Gain problem solving skills

The ability to think analytically and approach problems in the right way is a skill that is very useful in the professional world and everyday life.


2. High demand

Data Analysts and Data Scientists are valuable. With a looming skill shortage as more and more businesses and sectors work on data, the value is going to increase.


3. Analytics is everywhere

Data is everywhere. All company has data and need to get insights from the data. Many organizations want to capitalize on data to improve their processes. It's a hugely exciting time to start a career in analytics.


4. It's only becoming more important

With the abundance of data available for all of us today, the opportunity to find and get insights from data for companies to make decisions has never been greater. The value of data analysts will go up, creating even better job opportunities.


5. A range of related skills

The great thing about being an analyst is that the field encompasses many fields such as computer science, business, and maths.  Data analysts and Data Scientists also need to know how to communicate complex information to those without expertise.


The Internet of Things is Data Science + Engineering. By learning data science, you can also go into the Internet of Things and Smart Cities.


This course aims to cover the fundamentals of Python programming through real-world examples, followed by a touch on Data Science. Python programming basics such as variables, data types, if statements, loops, functions, modules, object,s and classes are very important and this course will try to teach these with a Console Calculator project. 

The course will then run through the popular data mining libraries like pandas, matplotlib, scipy, sklearn briefly on iris dataset to do data manipulation, data visualizations, data exploration with statistics (inferential and descriptives), model, and evaluation. 

You do not need to know to program for this course.  

This course is based on my ebooks at SVBook.

You can look at the following courses if you want to get SVBOOK Certified Data Miner using Python.

SVBook Certified Data Miner using Python is given to people who have completed the following courses:

  • - Create Your Calculator: Learn Python Programming Basics Fast (Python Basics)

  • - Applied Statistics using Python with Data Processing (Data Understanding and Data Preparation)

  • - Advanced Data Visualizations using Python with Data Processing (Data Understanding and Data Preparation)

  • - Machine Learning with Python (Modeling and Evaluation)

and passed a 50 questions Exam. The four courses are created to help learners understand Python programming basics, then applied statistics (descriptive, inferential, regression analysis) and data visualizations (bar chart, pie chart, boxplot, scatterplot matrix, advanced visualizations with seaborn, and Plotly interactive charts ) with data processing basics to understand more about the data understanding and data preparation stage of IBM CRISP-DM model. The learner will then learn about machine learning and confusion matrix, which are the modeling and evaluation stages of the IBM CRISP-DM model. Learners will be able to do data mining projects after learning the courses.

Content

Introduction

Introduction
Getting Started 1
Getting Started 2
Getting Started 3
Getting Started 4
Language Essentials
Language Essentials 2
Object Essentials 1
Object Essentials 2
Object Essentials 3
Data Mining 1
Data Mining 2
Bonus Lecture: Discounted Course Ebook and Other Useful Information

Screenshots

Fundamentals of Python for Data Mining - Screenshot_01Fundamentals of Python for Data Mining - Screenshot_02Fundamentals of Python for Data Mining - Screenshot_03Fundamentals of Python for Data Mining - Screenshot_04

Reviews

Christopher
December 7, 2020
Content & General • Instruction is using an IDE to present. Jupyter Notebook is a better choice for some topics, including the pandas library. • Poor English “Python and R for data science has always been a debatable topics”. “The author feel that for statistics stuffs, R could offer more”. Also unclear with ‘more’ means. • I was never really sure where he was headed … he’s just writing code with no “this is where we are going, and we will take steps x and y and z to get there” • Minimal or no explanation of some of the concepts he is illustrating & code he is writing Video • Presenting out of a text book; not appropriate for presentations, use power point for example and present the highlights, while adding value through audio. Some parts of the textbook were hard to see. • It seems to me that the instructor didn’t review his videos, even once, before finalizing Audio • Lots of ‘aaahhs’ – It seems to me the instructor was not adequately prepared to each the course, but instead was ‘winging’ it • Lots of silence as the instructor was coding. Feels like I’m sitting there watching a college write some code rather than a lecture
Bakkali
February 1, 2019
Not recommended at all, this course present only the very basics of Python, and copy paste course from PDF to IDE. The instructor does not even notice the error in the code, he needs to verify every character from the PDF.

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Related Topics

1694882
udemy ID
5/15/2018
course created date
7/10/2019
course indexed date
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