The Python Bootcamp: Data Science, Analytics & Visualisation

The Python Bootcamp: Data Science, Analytics & Visualisation

Reviews

"Perfect pace , clear and concise explanation on topics" - Deepak K

"This is my fourth Data Civilisation course I have undertaken, and I can assure you this will not be my last (if they continue to create the top end courses!)

From start to finish the course was delivered with such high standard and precision, building on every concept learnt as every section continued.

For someone (myself) who is looking to enter the data analysis sector, these guys have really built the confidence in me to do so and I am certain so many others who are in my position will benefit from this course..." - Imran Khan

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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

Learn From Scratch!

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What you will 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

Rating: 3.85

Level: All Levels

Duration: 12.5 hours

Instructor: Data Civilisation