Booking options
£10.99
£10.99
On-Demand course
6 hours 20 minutes
All levels
Dive deep into the vast realm of Python data science with our meticulously crafted course: 'Python Data Science with Numpy, Pandas and Matplotlib'. Explore the intricate details of Python, setting the stage with Pandas and Numpy, before delving into the power of Python data structures. With topics ranging from Python Strings to Matplotlib Histograms, you'll gain a holistic insight, ensuring that every dataset you touch unveils its story compellingly. So, if you're keen on transmuting raw data into visual masterpieces or insights, this journey is tailor-made for you.
Learning Outcomes
Grasp foundational knowledge of Python and its data structures like strings, lists, and dictionaries.
Understand the potential of NumPy, from basic array operations to handling multi-dimensional arrays.
Master the versatility of Pandas, encompassing everything from dataframe conversions to intricate operations like aggregation and binning.
Efficiently manage, manipulate, and transform data using Pandas' diverse functionalities.
Create visually striking and informative graphs using the power of Matplotlib.
Unlimited access to the course for forever
Digital Certificate, Transcript, student ID all included in the price
Absolutely no hidden fees
Directly receive CPD accredited qualifications after course completion
Receive one to one assistance on every weekday from professionals
Immediately receive the PDF certificate after passing
Receive the original copies of your certificate and transcript on the next working day
Easily learn the skills and knowledge from the comfort of your home
After studying the course materials of the Python Data Science with Numpy, Pandas and Matplotlib there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60.
Beginners eager to jumpstart their journey in Python data science.
Analysts looking to enhance their data manipulation skills using Python.
Statisticians keen on expanding their toolset with Python-based libraries.
Data enthusiasts desiring a deep dive into Python's data libraries and structures.
Professionals aiming to upgrade their data visualisation techniques.
This Python Data Science with Numpy, Pandas and Matplotlib does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Python Data Science with Numpy, Pandas and Matplotlib was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection.
Data Scientist: £40,000 - £80,000
Python Developer: £35,000 - £70,000
Data Analyst: £30,000 - £55,000
Business Intelligence Analyst: £32,000 - £60,000
Research Analyst: £28,000 - £52,000
Data Visualization Engineer: £33,000 - £65,000
Course Introduction and Table of Contents | |||
Course Introduction and Table of Contents | 00:09:00 | ||
Introduction to Python, Pandas and Numpy | |||
Introduction to Python, Pandas and Numpy | 00:07:00 | ||
System and Environment Setup | |||
System and Environment Setup | 00:08:00 | ||
Python Strings | |||
Python Strings - Part 1 | 00:11:00 | ||
Python Strings - Part 2 | 00:09:00 | ||
Python Numbers and Operators | |||
Python Numbers and Operators - Part 1 | 00:06:00 | ||
Python Numbers and Operators - Part 2 | 00:07:00 | ||
Python Lists | |||
Python Lists - Part 1 | 00:05:00 | ||
Python Lists - Part 2 | 00:06:00 | ||
Python Lists - Part 3 | 00:05:00 | ||
Python Lists - Part 4 | 00:07:00 | ||
Python Lists - Part 5 | 00:07:00 | ||
Tuples in Python | |||
Tuples in Python | 00:06:00 | ||
Sets in Python | |||
Sets in Python - Part 1 | 00:05:00 | ||
Sets in Python - Part 2 | 00:04:00 | ||
Python Dictionary | |||
Python Dictionary - Part 1 | 00:07:00 | ||
Python Dictionary - Part 2 | 00:07:00 | ||
NumPy Library - Introduction | |||
NumPy Library Intro - Part 1 | 00:05:00 | ||
NumPy Library Intro - Part 2 | 00:05:00 | ||
NumPy Library Intro - Part 3 | 00:06:00 | ||
NumPy Array Operations and Indexing | |||
NumPy Array Operations and Indexing - Part 1 | 00:04:00 | ||
NumPy Array Operations and Indexing - Part 2 | 00:06:00 | ||
NumPy Multi-Dimensional Arrays | |||
NumPy Multi-Dimensional Arrays - Part 1 | 00:07:00 | ||
NumPy Multi-Dimensional Arrays - Part 2 | 00:06:00 | ||
NumPy Multi-Dimensional Arrays - Part 3 | 00:05:00 | ||
Introduction to Pandas Series | |||
Introduction to Pandas Series | 00:08:00 | ||
Introduction to Pandas Dataframes | |||
Introduction to Pandas Dataframes | 00:07:00 | ||
Pandas Dataframe conversion and drop | |||
Pandas Dataframe conversion and drop - Part 1 | 00:06:00 | ||
Pandas Dataframe conversion and drop - Part 2 | 00:06:00 | ||
Pandas Dataframe conversion and drop - Part 3 | 00:07:00 | ||
Pandas Dataframe summary and selection | |||
Pandas Dataframe summary and selection - Part 1 | 00:06:00 | ||
Pandas Dataframe summary and selection - Part 2 | 00:06:00 | ||
Pandas Dataframe summary and selection - Part 3 | 00:07:00 | ||
Pandas Missing Data Management and Sorting | |||
Pandas Missing Data Management and Sorting - Part 1 | 00:07:00 | ||
Pandas Missing Data Management and Sorting - Part 2 | 00:07:00 | ||
Pandas Hierarchical-Multi Indexing | |||
Pandas Hierarchical-Multi Indexing | 00:06:00 | ||
Pandas CSV File Read Write | |||
Pandas CSV File Read Write - Part 1 | 00:05:00 | ||
Pandas CSV File Read Write - Part 2 | 00:07:00 | ||
Pandas JSON File Read Write | |||
Pandas JSON File Read Write Operations | 00:07:00 | ||
Pandas Concatenation Merging and Joining | |||
Pandas Concatenation Merging and Joining - Part 1 | 00:05:00 | ||
Pandas Concatenation Merging and Joining - Part 2 | 00:04:00 | ||
Pandas Concatenation Merging and Joining - Part 3 | 00:04:00 | ||
Pandas Stacking and Pivoting | |||
Pandas Stacking and Pivoting - Part 1 | 00:06:00 | ||
Pandas Stacking and Pivoting - Part 2 | 00:05:00 | ||
Pandas Duplicate Data Management | |||
Pandas Duplicate Data Management | 00:07:00 | ||
Pandas Mapping | |||
Pandas Mapping | 00:04:00 | ||
Pandas Grouping | |||
Pandas Groupby | 00:06:00 | ||
Pandas Aggregation | |||
Pandas Aggregation | 00:09:00 | ||
Pandas Binning or Bucketing | |||
Pandas Binning or Bucketing | 00:08:00 | ||
Pandas Re-index and Rename | |||
Pandas Re-index and Rename - Part 1 | 00:04:00 | ||
Pandas Re-index and Rename - Part 2 | 00:05:00 | ||
Pandas Replace Values | |||
Pandas Replace Values | 00:05:00 | ||
Pandas Dataframe Metrics | |||
Pandas Dataframe Metrics | 00:07:00 | ||
Pandas Random Permutation | |||
Pandas Random Permutation | 00:08:00 | ||
Pandas Excel sheet Import | |||
Pandas Excel sheet Import | 00:07:00 | ||
Pandas Condition Selection and Lambda Function | |||
Pandas Condition Selection and Lambda Function - Part 1 | 00:05:00 | ||
Pandas Condition Selection and Lambda Function - Part 2 | 00:05:00 | ||
Pandas Ranks Min Max | |||
Pandas Ranks Min Max | 00:06:00 | ||
Pandas Cross Tabulation | |||
Pandas Cross Tabulation | 00:07:00 | ||
Matplotlib Graphs and plots | |||
Graphs and plots using Matplotlib - Part 1 | 00:06:00 | ||
Graphs and plots using Matplotlib - Part 2 | 00:02:00 | ||
Matplotlib Histograms | |||
Matplotlib Histograms | 00:03:00 | ||
Resource File | |||
Resource File - Python Data Science with Numpy, Pandas and Matplotlib | 00:00:00 |
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