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Course Overview
Learn how to make a genuine difference in your life by taking our popular Python Data Science with Numpy, Pandas and Matplotlib. Our commitment to online learning and our technical experience have been put to excellent use within the content of these educational modules. By enrolling today, you can take your knowledge of Python Data Science with Numpy, Pandas and Matplotlib to a whole new level and quickly reap the rewards of your study in the field you have chosen.
We are confident that you will find the skills and information that you will need to succeed in this area and excel in the eyes of others. Do not rely on substandard training or half-hearted education. Commit to the best, and we will help you reach your full potential whenever and wherever you need us.
Please note that Python Data Science with Numpy, Pandas and Matplotlib provides valuable and significant theoretical training for all. However, it does not offer official qualifications for professional practice. Always check details with the appropriate authorities or management.
Learning Outcomes
Your Path to Success
By completing the training in Python Data Science with Numpy, Pandas and Matplotlib, you will be able to significantly demonstrate your acquired abilities and knowledge of Python Data Science with Numpy, Pandas and Matplotlib. This can give you an advantage in career progression, job applications, and personal mastery in this area.
Is This Course Right for You?
This course is designed to provide an introduction to Python Data Science with Numpy, Pandas and Matplotlib and offers an excellent way to gain the vital skills and confidence to start a successful career. It also provides access to proven educational knowledge about the subject and will support those wanting to attain personal goals in this area. Full-time and part-time learners are equally supported, and the study periods are entirely customisable to your needs.
Assessment Process
Once you have completed all the modules in the Python Data Science with Numpy, Pandas and Matplotlib course, you can assess your skills and knowledge with an optional assignment. Our expert trainers will assess your assignment and give you feedback afterwards.
Show off Your New Skills with a Certification of Completion
The learners have to successfully complete the assessment of this Python Data Science with Numpy, Pandas and Matplotlib course to achieve the CPD accredited certificate. Digital certificates can be ordered for only £10. Learners can purchase printed hard copies inside the UK for £29, and international students can purchase printed hard copies for £39.
Course Introduction and Table of Contents | |||
Course Introduction and Table of Contents | 00:10:00 | ||
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 | 00:07:00 | ||
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 |
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