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The Python Bootcamp: Data Science, Analytics & Visualisation

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MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 138 lectures (12h 22m) | Size: 6.4 GB
Learn From Scratch!

Learn From Scratch!


What you’ll learn:
How to navigate and utilise ‘Jupyter Notebooks’ for Python coding
Understanding the different data types in Python
How to carry out mathematical and string slicing operations on the respective data
The different series and data structures which are used in Python and how to run operations on them
How to use different Python statements to apply conditions to your code
Creating loops and iterations to drive Python operations
How to create your own Python functions
The basics to object orientated programming
The structure of arrays and how to operate on them by using the ‘Numpy’ module
How to carry out data analysis and analytics operations by using the ‘Pandas’ module
How to explore and understand data sets
How to apply operations on data sets to obtain useful information which provides meaningful insights
Understanding how to introduce relationships between multiple data sets
How to identify and resolve data quality issues
How to create visualisations in Python by using the ‘Matplotlib’ and ‘Seaborn’ modules
How to utilise statistical applications to identify potential anomaly instances in a data set
An introduction to Data Science applications
How to utilise linear regression and multiple linear regression models to make predictions
How to utilise the k-nearest neighbours’ model to make predictions
How to utilise the decision tree model to make predictions

Requirements
None! Everything will be taught from scratch!
You will be using Jupyter Notebooks in this course, but all the installation steps will be covered in the course

Description
Add one of the most sought-after skills to your skill set!

This course will build your Python skills from scratch! The teaching methods used in this course will build on the foundation with you will gain to a high enough level where you will possess the ability to write Python code confidently and independently. As a result, you will be able to open multiple doors in the current job market!

If you want to learn Python operations, data analysis & analytics, data visualisation and the basics to data science, then this course is for you! All of these topics will be covered in Python 3!

This course contains more than 12 hours of lectures consisting of upwards spiral learning, so that you keep revisiting previous topics in the course. This will organically ensure that you are building your knowledge in all of the sections in this course, in addition to revising in the quizzes. There practical examples and applications are layered so that the complexity which you come across is easily digestible!

You will get lifetime access to this course and we will provide you with additional support if needed!

This course is broken down in the following manner:

(A) Python Operations:

Data Types

Numeric Operations

String Operations

Lists

Tuples

Dictionaries

Sets

‘If’ statement operations

‘While’ loop operations

‘For’ loop operations

List comprehensions

Creating your own functions

Object orientated programming (classes)

(B) Arrays (Numpy)

Structure of arrays (one and two dimensional)

Array operations

Applying filters to arrays

Analysing arrays

(C) Data Analytics (Pandas)

Importing data

Data frame operations

Filtering data

Sorting data

Bucketing data

Replacing data

Aggregations

Dealing with null values

Dealing with duplicate values

Appending data frames

Joins

Cumulative operations

Row number

Rankings

(D) Data Visualisation (Matplotlib)

Bar charts

Line charts

Pie charts

(E) Data Visualisation (Seaborn)

Scatter charts

Distribution plots

(F) Data Science

Anomaly testing

Linear regression

Multiple linear regression

K-nearest neighbours

Decision trees

This course is suitable for the following students:

Beginners who have no past coding or Python experience

SQL users who want to learn about how processes are carried out in Python

Intermediate users who have experience in Python that want to learn about Data Analysis/Analytics, Data Visualisation and an introduction to Data Science

Who this course is for
Beginner Python users
Students who want to learn how to use Python for data analysis & data analytics
Students who who want to gateway into the world of coding

The Python Bootcamp: Data Science, Analytics & Visualisation

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