The Python Bootcamp Data Science, Analytics & Visualisation

Posted in: Tutorials | By: voska89 | 2-11-2020, 13:34 | 0 Comments

The Python Bootcamp Data Science, Analytics & Visualisation
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 138 lectures (12h 22m) | Size: 6.4 GB
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 'MatDescriptionlib' 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
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
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
'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
Dealing with null values
Dealing with duplicate values
Appending data frames
Cumulative operations
Row number
(D) Data Visualisation (MatDescriptionlib)
Bar charts
Line charts
Pie charts
(E) Data Visualisation (Seaborn)
Scatter charts
Distribution Descriptions
(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

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