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Python Data Science with Numpy, Pandas and Matplotlib

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Course overview Learn about Python Data Science with Numpy, Pandas and Matplotlib quickly and enhance your skills. You will understand …

Course overview

Learn about Python Data Science with Numpy, Pandas and Matplotlib quickly and enhance your skills. You will understand Python Data Science with Numpy, Pandas and Matplotlib and its key areas, covering the fundamentals and beyond. The Python Data Science with Numpy, Pandas and Matplotlib] course is divided into small modules that are easy to grasp even by complete beginners. Plus, the Python Data Science with Numpy, Pandas and Matplotlib course comes with tutor support, so if you have any questions related to Python Data Science with Numpy, Pandas and Matplotlib, you can ask them via live chat or email.

Completing this Python Data Science with Numpy, Pandas and Matplotlib course will give you the confidence to stand out to prospective employers in the Python Data Science with Numpy, Pandas and Matplotlib industry & other relevant sectors, climb up the career ladder and boost your earning potential in no time.

Enrol in the Python Data Science with Numpy, Pandas and Matplotlib course today and invest in your bright future.

What's inside

Who is this course for?

Anyone with an interest in Python Data Science with Numpy, Pandas and Matplotlib will find this course valuable. Whether you are a student/ aspiring professional aiming to explore your opportunities in Python Data Science with Numpy, Pandas and Matplotlib sectors, then this Python Data Science with Numpy, Pandas and Matplotlib] course might just be the perfect opportunity for you.

Certification

After successfully completing the Python Data Science with Numpy, Pandas and Matplotlib course, you can apply for a CPD accredited course in both digital & physical format.

The pricing for the Python Data Science with Numpy, Pandas and Matplotlib course completion certificate is as follows:

Learning outcomes

Career path

Complete your Python Data Science with Numpy, Pandas and Matplotlib course successfully and develop yourself to enhance your chances of succeeding in Python Data Science with Numpy, Pandas and Matplotlib sectors and other relevant fields.

Course Curriculum

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	00:05:00
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	00:07:00
	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

Certificate of Achievement from Institute of Beauty & Makeup

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Certificate of Achievement from CPD Quality Standard

Professionalism and self-improvement are clearly priorities for CPD. Through continuing professional development, an individual might recognize knowledge gaps and fill them in using a recognizable improvement strategy.

Recognition: Having CPD QS Accreditation increases the value of your professional accomplishments and is recognized internationally.
CPD Hours/Points: Your commitment to lifelong learning is demonstrated by the amount of CPD hours or points that are included on each certificate.
Free Course Transcript: Get a thorough transcript of your course that lists all of your accomplishments and the modules you've finished.
Module Breakdown: A breakdown of the course modules you have successfully completed will help you better understand your progress.
Skill Enhancement: Access up-to-date, relevant content that's tailored to your industry, ensuring you're always at the forefront of industry trends.
Career Advancement: A CPD QS Accredited Certificate can open doors to new opportunities and advancement within your field.