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The Python Bootcamp: Data Science, Analytics & Visualisation

Learn From Scratch!
(13 reviews)
68 students
Created by


CourseMarks Score®







Platform: Udemy
Video: 12h 22m
Language: English
Next start: On Demand

Table of contents


“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
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 (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

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
✓ 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


• 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

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
Technology-based analytics company
Data Civilisation is a technology-based analytics company, aiming to bring keen and curious learners together.
We aim to provide only the best quality content, to help our learners along their journey of becoming experienced data analysts.
Data Civilisation was founded by two data analysts who started their careers in the largest professional service consultancy firms. They work with various tools, such as SQL, PowerBI, and Python and have over ten years of combined experience in analytics.
Browse all courses by on Coursemarks.
Platform: Udemy
Video: 12h 22m
Language: English
Next start: On Demand

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