Data Analytics and Visualisation with Python

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Christ Raharja

2:49:09

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1. Introduction to Data Analytics and Visualisation with Python

1. Introduction Welcome to Data Analytics and Visualisation Course.mp4

04:32

2. Whom the course is intended for.mp4

07:20

2. Lets begin our journey!

1. Introduction to Kaggle.mp4

05:48

2.1 DataAnalyticsPresentation.pdf

2. Tools, Python libraries, and datasets preparation.mp4

05:05

3. Lets get started exploring and picking datasets from Kaggle.mp4

09:07

3. Google Colab Set Up

1. Set Up your Google Colab.mp4

04:34

4. Dataset 1 Practice

1.1 Uber Request Data.csv

1.2 uberdataanalysis.zip

1. Dataset 1 get overview of the dataset.mp4

08:50

2. Dataset 1 practice part 1.mp4

22:05

3. Dataset 1 practice part 2.mp4

27:58

5. Dataset 2 Practice

1.1 imdbmovies.zip

1.2 movies.csv

1. Dataset 2 get overview of the dataset.mp4

06:13

2. Dataset 2 practice part 1.mp4

17:54

3. Dataset 2 practice part 2.mp4

12:32

4. Dataset 2 practice part 3.mp4

19:20

6. Data Analytics Common Practice Guide

1. Data Analytics Common Practice Guide.mp4

08:21

7. Kaggle Data Competition

1.1 Full Guide for Kaggle Data Competition.html

1. Kaggle Data Competition How to Participate.mp4

09:30

Description

Learn data analytics and visualisation with Pandas and Matplotlib

What You'll Learn?

Learn basic data analytics and data visualisation concepts
Be familiar to use Pandas and Matplotlib
Learn how to perform statistical analysis on dataset
Learn how to generate scatterplot and bar plot
Learn how to explore datasets on Kaggle

Who is this for?

Python beginners who are interested in data analytics

Entry level job seekers who want to build up their data analytics and visualisation portfolio

More details

Description
In this Data Analytics and Visualisation with Python course, you will learn basic concepts of data analytics and data visualisation utilising several different Python libraries such as Pandas mainly for reading our dataset and performing statistical calculations whilst Matplotlib mainly for data visualisation, including but not only limited to generating scatter plot and bar plot. We will obtain our datasets from Kaggle data bank and later on in this course, we will also discuss Kaggle data competition as our learning motivations. Since this course was designed for beginners, hence, I tried my best to teach and explain all materials from the perspective of someone who has limited knowledge in Python and data analytics. As the nature of this course which was intended for beginner, it will not make you an expert in a night, instead, it will provide you a strong and solid understanding of data analytics concepts, multiple different statistical methods like mean, max, min, median, mode, as well as be comfortable operating Pandas and Matplotlib which hopefully enables you to start experimenting, exploring and building your data analytics portfolio. Last but not least, this course will also train you to have a mindset that needs to be had by a professional data practitioner, understanding data analytics cycle and data acumen which in my personal opinion are very important skills to be had enabling you to communicate your solution with others who come from non technical background.
Who this course is for:
Python beginners who are interested in data analytics
Entry level job seekers who want to build up their data analytics and visualisation portfolio

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Hi all, my name is Chris Raharja. I graduated from University of Washington with BS in Mathematics. I used to work as a technology consultant in one of Big 4 firms and now I have been running several different business models such as print on demand, affiliate marketing, drop shipping, ads traffic arbitrage. I have been always passionate about teaching since my first time as a volunteer math tutor in high school. My goal on Udemy is to share my knowledge and build a wonderful community to study many different things together.

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